thesis chapter 3 content

Dissertation

Chapter 3: Method

This chapter presents the methods and research design for this dissertation study. It begins by presenting the research questions and settings, the LibraryThing and Goodreads digital libraries. This is followed by an overview of the mixed methods research design used, incorporating a sequence of three phases. Each of the three methods—qualitative content analysis, a quantitative survey questionnaire, and qualitative interviews—are then presented in detail. The codes and themes used for analysis during the qualitative phases are discussed next. The chapter continues with sections on the management of the research data for this study; the validity, reliability, and trustworthiness of study findings; and ethical considerations. The invitation letters and informed consent statement; survey instrument; interview questions; a quick reference guide used for coding and analysis; and documentation of approval from LibraryThing, Goodreads, and the FSU Human Subjects Committee are included in appendices.

3.1. Research Questions

As stated in Chapter 1 the purpose of this research, taking a social perspective on digital libraries, is to improve understanding of the organizational, cultural, institutional, collaborative, and social contexts of digital libraries. The following two research questions satisfy the purpose of the proposed study within the approach, setting, and framework introduced in Chapter 1 :

• RQ1: What roles do LibraryThing and Goodreads play, as boundary objects, in translation and coherence between the existing social and information worlds they are used within?
• RQ2: What roles do LibraryThing and Goodreads play, as boundary objects, in coherence and convergence of new social and information worlds around their use?

These two questions explore the existing and emergent worlds that may surround digital libraries in social, collaborative use and behavior. RQ1 focuses on examining how LibraryThing and Goodreads may support existing collaboration, communities, and other social activities and behaviors across social and information worlds, with a specific eye to translation, characteristics indicating coherence of existing worlds, and uses of the digital libraries as boundary objects. RQ2 focuses on examining how LibraryThing and Goodreads may support coherence and convergence of new, emergent social and information worlds and their characteristics, as indicated by use of the digital libraries (as boundary objects) as new, localized standards. The questions focus on the roles of each digital library, be there one role, multiple roles, or possibly no role played by LibraryThing and Goodreads. These roles may or may not include explicit support for collaboration, communities, or social contexts. The research questions use and incorporate the definitions, concepts, and propositions of social digital libraries (see section 2.4.3 ), the social worlds perspective (see sections 2.7.1.1 and 2.8.1 ), the theory of information worlds (see section 2.8.2 ), and the synthesized theoretical framework for social digital libraries (developed in section 2.8.3 ). Coherence and convergence are seen as the same concept in boundary object theory (see section 2.7.1.4 ), leading to overlap between the concepts—and the two research questions—in operational data collection and analysis. The connotations of the two indicate convergence will lead to new, emergent worlds, and this meaning is indicated by its use in RQ2, but not RQ1.

3.2. Setting: Case Studies of LibraryThing and Goodreads

In this dissertation study, the boundary objects of interest are defined and given as two digital libraries: LibraryThing and Goodreads (see sections 3.2.2 and 3.2.3 below). This approach is opposite the procedure used by Star and Griesemer (1989), who first identified the populations of communities, users, and stakeholders in their study, then examined the boundary objects they used. Starting with the boundary objects is in line with Star’s later work (Bowker & Star, 1999; Star et al., 2003). Bødker and Christiansen (1997); Gal, Yoo, and Boland (2004); Henderson (1991); and Pawlowski, Robey, and Raven (2000) have used this approach to varying extents, proving its validity and usefulness as an approach to take for studying social digital libraries as boundary objects.

3.2.1. Case Study Approach

This research takes a case study approach, where "a detailed" and intensive "analysis of … individual case[s]"—LibraryThing and Goodreads—will be performed (Fidel, 1984, p. 274). The research looked to generate "a comprehensive understanding of the event under study"—uses of these digital libraries as boundary objects within and across existing and emergent social and information worlds—and develop "more general theoretical statements about regularities in the observed phenomena" surrounding social digital libraries (p. 274). Case studies often focus on the cycle of research methods which inform each other through a longer, more detailed research process than using a single exploratory method. A case study approach fosters multiple opportunities to revisit and reanalyze data collected earlier in the study, revise the research design as new facets and factors emerge, and combine multiple methods and data sources into a holistic description of each case. The research design used here, employing two qualitative and one quantitative method in a cycle (see section 3.3 ), follows this approach.

Yin (2003) breaks the process of conducting a case study into five phases. The phases "effectively force [the researcher] to begin constructing a preliminary theory" prior to data collection (p. 28), as done in Chapter 2 . Each of Yin’s five steps can be found in sections of this dissertation. First, one must determine the research questions to be asked; these were included in section 3.1 above. Second, one must identify what Yin calls the "propositions," statements "direct[ing] attention to something that should be examined within the scope of study" (p. 22). The theoretical framework developed earlier (see section 2.8) and the purpose of this research as stated in Chapter 1 provide this necessary focus from a conceptual perspective. The operationalization of this focus is discussed for each method in sections 3.4.4 , 3.5.3 , 3.6.4 , and 3.7 . Third, Yin says one must determine the unit of analysis, based on the research questions. In this study, the overall units of analysis are the two social digital libraries under consideration, LibraryThing and Goodreads; other units of interest include communities, groups, and individuals. The specific unit of analysis for each method of data collection is discussed in sections 3.4.1 , 3.5.1 , and 3.6.2 . Fourth, one must connect "data to [theoretical] propositions," matching patterns with theories (p. 26). Using the theoretical framework developed in section 2.8 in data analysis (see sections 3.4.4 , 3.5.5 , 3.6.6 , and 3.7 ) provides for this matching process. For the final step, Yin says one must determine "the criteria for interpreting [the] findings" (p. 27); the criteria chosen for this research are discussed in the data analysis sections ( 3.4.4 , 3.5.5 , 3.6.6 , and 3.7 ) and are considered in light of concerns of validity, reliability, and trustworthiness ( section 3.9 ) and the benefits ( section 1.7 and Chapter 5 ) and limitations ( section 5.6 ) of the study.

This research employed a multiple-case, "holistic" design at the highest level, focusing on LibraryThing and Goodreads as units, but what Yin (2003, p. 42) calls an "embedded" design, with multiple units of analysis considered in each method, at lower levels. Examining two social digital libraries allows them to be compared and contrasted, but commonalities were expected to emerge—and did—across the two cases to allow theoretical and practical conclusions to be drawn (see Chapter 5 ). Yin stated case study designs must be flexible and may change as a result of research not turning out as expected, and subtle changes were made to what was intended to be a flexible plan for case studies of LibraryThing and Goodreads and their use as boundary objects within and across existing and emergent social and information worlds.

3.2.2. LibraryThing

LibraryThing (LT) is a social digital library and web site founded in August 2005 (LibraryThing, n.d.-a), with over 1.8 million members as of June 2014 (LibraryThing, 2014). It allows users to catalog books they own, have read, or want to read (LibraryThing, n.d.-b); these serve as Functional Requirements for Bibliographic Records (FRBR) items (International Federation of Library Associations and Institutions, 2009). Users can assign tags to books, mark their favorites, and create and share collections of books with others; these collections are searchable and sortable. LT suggests books to users based on the similarity of collections. Users can provide reviews, ratings, or other metadata (termed "Common Knowledge"; LibraryThing, 2013) for editions of books (FRBR’s manifestations and expressions) and works (as in FRBR); this metadata and users’ tags are shared across the site (LibraryThing, n.d.-c). LT provides groups (administered by users or staff), which include shared library collection searching, forums, and statistics on the books collected by members of the group (LibraryThing, n.d.-d). Discussions from these forums about individual books are included on each book’s page, as are tags, ratings, and reviews. Each user has a profile page which links to their collections, tags, reviews, and ratings, and lists other user-provided information such as homepage, social networks used (Facebook, Twitter, etc.), and a short biography (LibraryThing, n.d.-c).

Examining LibraryThing in light of the definition of social digital libraries (see sections 1.1 and 2.4.3 ) shows the following:

• LT features one or more collections of digital content collected for its users, who can be considered a community as a whole and part of many smaller communities formed by the groups feature. This content includes book data and metadata sourced from Amazon.com and libraries using the Z39.50 protocol (LibraryThing, n.d.-b); and user-contributed data, metadata, and content in many forms: tags, favorites, collections, reviews, posts in discussions, and profile information.
• LT features services relating to the content and serving its user communities, including the ability to catalog books; create collections; discuss with others; and search for and browse books, reviews, tags, and other content.
• LT is managed by a formal organization and company, and draws on the resources of other formal organizations (Amazon.com, libraries) and informal groupings (LT users) for providing and managing content and services.

As a large social digital library and web site, open to the public and with multiple facets, LibraryThing is well-suited as a setting and case for examining the role of digital libraries within and across communities. The existing research literature on LibraryThing has focused on its roles for social tagging and classification (e.g. Chang, 2009; Lu, Park, & Hu, 2010; Zubiaga, Körner, & Strohmaier, 2011) and in recommendation and readers’ advisory (e.g. Naughton & Lin, 2010; Stover, 2009). This study adds an additional view of the site as an online community and social digital library.

3.2.3. Goodreads

Goodreads (GR), similar to LibraryThing, is a social digital library and web site founded in January 2007 (Goodreads, 2014a). As of June 2014, it has 25 million members. Users can "recommend books" via ratings and reviews, "see which books [their] friends are reading; track the books [they are] reading, have read, and want to read; … find out if a book is a good fit for [them] from [the] community’s reviews" (para. 2); and join discussion groups "to discuss literature" (Goodreads, 2014b, para. 11). As with LibraryThing, Goodreads users can create lists of books (called "shelves"), which act as site-wide tags anyone can search on (para. 5). Searching and sorting are possible for other metadata and content types; metadata can apply to editions (manifestations or expressions) of a book or to whole works (in FRBR terms; International Federation of Library Associations and Institutions, 2009). Groups can be created, joined, and moderated by users (including Goodreads staff); they can include group shelves, discussion forums, events, photos, videos, and polling features. Users have profile pages, which may include demographic information, favorite quotes, writing samples, and events. Users who have greater than 50 books on their shelves can apply to become a Goodreads librarian , which allows them to edit and update metadata for books and authors (Goodreads, 2012d, "What can librarians do?" section). In March 2013—during the early stages of this dissertation research—Amazon.com acquired Goodreads (Chandler, 2013).

Examining GR in light of the definition of social digital libraries (see sections 1.1 and 2.4.3 ) shows the following:

• GR features one or more collections of digital content collected for its users, who can be considered a community as a whole and part of many smaller communities formed by the groups feature. This content includes book data and metadata previously sourced from Ingram (a book wholesaler), libraries (via WorldCat and the catalogs of the American, British, and German national libraries), and publishers (Chandler, 2012), and now from Amazon since their purchase (Chandler, 2013); and user-contributed metadata and content, including shelves, lists, forum posts, events, photos, videos, polls, profile information, and book trivia.
• GR features services relating to the content and serve its user communities, including the ability to catalog books; create shelves; discuss with others; and search for and browse books, reviews, lists, and other content.
• GR is managed by a formal organization and company—Goodreads Inc., although now owned by Amazon—and draws on the resources of other formal organizations (Amazon, Ingram, OCLC via WorldCat, libraries, and publishers) and informal groupings (GR users, the librarians group) for providing and managing content and services.

As with LibraryThing, Goodreads is well-suited as a setting and case for examining the role of digital libraries within and across communities, because it is a large social digital library and web site that is open to the public and has multiple facets. There is little existing research literature on Goodreads, limited to its use in recommendation and readers’ advisory (e.g. Naik, 2012; Stover, 2009) and examining its impact on the practice of reading (Nakamura, 2013). This study adds an additional view of the site as an online community and social digital library.

3.3. Research Design

Use of a mixed methods research design combines qualitative and quantitative methods together to emphasize their strengths; minimize their weaknesses; improve validity, reliability, and trustworthiness; and obtain a fuller understanding of uses of social digital libraries as boundary objects within and across social and information worlds. Definitions of mixed methods research vary but core characteristics can be identified, which Creswell and Plano Clark (2011, p. 5) summarize as

• collection and analysis of both qualitative and quantitative data;
• integration of the two forms of data at the same time, in sequence, or in an embedded design;
• prioritizing one or both forms of data;
• combining methods within a single study or multiple phases of a larger research program;
• framing the study, data collection, and analysis within philosophical, epistemological, and theoretical lenses; and
• conducting the study according to a specific research design meting the other criteria.

This study meets all of these criteria. Qualitative and quantitative data were collected and integrated in sequence; qualitative data was prioritized, but not at the expense of quantitative data collection; multiple methods were used within this one study; and the study was based on the theoretical framework developed and the tenets of social informatics and social constructionism explained in Chapter 2 .

This study took a philosophical view of mixed methods research similar to the view of Ridenour and Newman (2008), who "reject[ed] the [standard] dichotomy" between qualitative and quantitative research methods, believing there to be an "interactive continuum" between the two (p. xi). They stated "both paradigms have their own contributions to building a knowledge base" (p. xii), suggesting a holistic approach to research design incorporating theory building and theory testing in a self-correcting cycle. Qualitative methods, Ridenour and Newman argued, should inform the research questions and purpose for quantitative phases, and vice versa; they termed this process an "interactive" one (p. xi). Research designs should come from the basis of "the research purpose and the research question" (p. 1), what "evidence [is] needed," and what epistemological stance should be taken "to address the question" (p. 18).

Greene (2007) presented a similar argument, stating "a mixed methods way of thinking actively engages with epistemological differences" (p. 27); multiple viewpoints are respected, understood, and applied within a given study. She acknowledged the tensions and contradictions that will exist in such thought, but believed this would produce the best "conversation" and allow the researcher to learn the most from their study and data (p. 27). Creswell and Plano Clark (2011) encompassed multiple viewpoints and potential designs in their chapter on choosing a mixed methods design (pp. 53–104). They considered six prototypical designs: (a) convergent parallel; (b) explanatory sequential; (c) exploratory sequential; (d) embedded; (e) transformative; and (f) multiphase.

The research design for this dissertation study is a variation on a multiphase design incorporating elements of the explanatory sequential and exploratory sequential designs of Creswell and Plano Clark. Three methods were use for data collection, following the process proposed by Ridenour and Newman (2008) and taking the approach to thought suggested by these authors, Creswell and Plano Clark (2011), and Greene (2007). The selection of this design and these methods was based on the research purpose discussed in Chapter 1 , the research questions introduced in section 3.1 , and the research setting explained in section 3.2 . The methods used were

• content analysis of messages in LibraryThing and Goodreads groups ( section 3.4 );
• a structured survey of LibraryThing and Goodreads users ( section 3.5 ); and
• semi-structured qualitative interviews with users of LibraryThing and Goodreads ( section 3.6 ).

The holistic combination of these methods, interrelated in a multiphase design, has allowed for exploratory and descriptive research on social digital libraries as boundary objects incorporating the strengths of quantitative and qualitative methods and the viewpoints of multiple perspectives.

3.3.1. Integrated Design

A sequential, multiphase research design was employed for two reasons. First, each of the methods above required focus on data collection and analysis by the researcher. Trying to use a parallel or concurrent design, conducting content analysis alongside a survey or a survey alongside interviews, could have caused excess strain; a sequential design improved the chances of success, the quality of data collected and analyzed, and the significance of and level of insight in the study’s conclusions. Second, each method built on the methods before it. The design of the survey and interview instruments was influenced by ideas drawn from the literature and theories for the study and by elements of interest uncovered during the content analysis phase. The interviews focused on gathering further detail on and insight into findings from the survey results and the content analysis. This combination of methods allowed for exploring each case through content analysis, obtaining summary explanatory data through surveys, and then detailed descriptive and explanatory data through the interviews, achieving the benefits of both the exploratory and explanatory research designs presented by Creswell and Plano Clark (2011, pp. 81–90).

Creswell and Plano Clark (2011) expressed caution, noting multiphase research designs often require substantial time, effort, and multi-researcher teams. The three phases used here were not lengthy or intensive enough to cause lengthy delays in the completion of this dissertation. This is one coherent dissertation study, instead of the long-term, multi-project research program Creswell and Plano Clark cite as the prototypical multiphase design. While it was known in advance this would not be the speediest dissertation research project, using a sequential design allowed for the results from each phase to emerge as the research proceeded, instead of having to wait for all phases to complete as in a concurrent design. A complete and insightful picture of the findings and conclusions of the dissertation came within a reasonable amount of time and with a good level of effort.

3.4. Content Analysis

Content analysis has been defined as "a technique for making replicable and valid inferences from texts (or other meaningful matter) to the contexts of their use" (Krippendorff, 2004a, p. 19), with emphasis often placed on "the content of communication" (Holsti, 1969, p. 2)—specific "characteristics of messages" (p. 14)—"as the basis of inference" (p. 2). Early forms of content analysis required objectivity and highly systematic procedures (see Holsti, 1969, pp. 3–5, 14). The form of content analysis used in this study considers the meaning and understanding of content to "emerge in the process of a researcher analyzing a text relative to a particular context" (Krippendorff, 2004a, p. 19), a subjective and less rigid approach. Such text or content may have multiple, socially constructed meanings, speaking to more "than the given texts" (p. 23); they are indicative of the "contexts, discourses, or purposes" surrounding the content (p. 24).

There are at least three categories of content analysis, which Ahuvia (2001) labels traditional , interpretive , and reception-based ; other authors and researchers (e.g. Babbie, 2007, p. 325; Holsti, 1969, pp. 12–14) break content analysis into latent (subjective and qualitative) and manifest (objective and quantitative) categories of analysis. Early content analysis was purely objective and generated quantitative summaries and enumerations of manifest content, but qualitative and latent analysis have found greater acceptance over time (Ahuvia, 2001; Holsti, 1969, pp. 5–14; Krippendorff, 2004a). This study used the interpretive approach and focused coding on the latent content—the underlying meaning—of the data gathered. This section discusses the application of content analysis in the first phase of this dissertation research, including (a) the choice of the unit of analysis; (b) the population and sampling method chosen; (c) the sampling and data collection procedures followed, including a pilot test; and (d) how the data was analyzed.

3.4.1. Unit of Analysis

The unit of analysis chosen for the content analysis in this study was the message . LibraryThing’s and Goodreads’ group discussion boards are organized into threads, each of which may contain multiple individual messages. Analysis of these individual messages was aimed at uncovering indications of the roles the two digital libraries play in existing and emergent social and information worlds. Analysis began with the individual messages to ensure details and phenomena at that level were captured, but over time went beyond individual messages to the thread or group levels, since these phenomena served as instantiations of social and information worlds or as sites for interaction and translation.

3.4.2. Population and Sampling

The broader population of messages could be defined as all messages posted in public LibraryThing and Goodreads groups, but the logistics of constructing a sampling frame for such a population were and are all but impossible; it is improbable the two sites would provide data on all messages posted if it is not required of them by law. Recent messages from active groups were of most interest and use for this study. The population of messages was defined as all messages from the most active LibraryThing groups in the past week (taken from http://www.librarything.com/groups/active ) and the most recently active Goodreads groups (taken from http://www.goodreads.com/group/active ) as of April 30, 2013, the day data collection began for the content analysis phase of the study. The sampling frames were restricted to as close to but no more than 100 groups as possible, based on LibraryThing’s list claiming to list the 100 most active groups; the actual frames consisted of 91 LibraryThing groups and 93 Goodreads groups once duplicates were removed. During the planning and design of this study, Goodreads provided a list of "recently popular" groups (at http://www.goodreads.com/group/recently_popular ) that was akin to LibraryThing’s list in nature; that list was taken down sometime in early 2013 due to it causing a server slowdown (Jack & Finley, 2013). Using the most recently active groups did not guarantee consistent popularity or activity over a recent time period (such as a week), but did address the need to collect recent messages from active groups and was deemed the most acceptable source for a sampling frame still available.

To obtain a sample of messages from this population, a stratified random sampling method using the levels of group, thread, and message was employed. From the lists identified above, five groups were selected at random from each digital library (for a total of ten), but with the following inclusion and exclusion criteria applied to help ensure representativeness and allow for meaningful analysis:

(a) At least one group from each digital library with over 100 messages posted in the last week was selected. (b) At least one group from each digital library with under 100 messages posted in the last week was selected. (c) Any group with fewer than 60 messages total was removed and a new group selected. (d) Any group with fewer than two members was removed and a new group selected. (e) Any group used in the pilot study (see below) was removed and a new group selected.

Due to constraints placed on this research by Goodreads and the nature of this digital library, all group selections for Goodreads required approval from at least one group moderator per group. Prior to the collection of any data, such moderators were messaged via the site using the invitation letter found in Appendix A , section A.1.1 , and provided their consent for their group to be included in the research by agreeing to an informed consent statement (see Appendix A , section A.1.2 ). Any groups for which the moderator did not provide consent within two weeks were removed from the sample and a new group selected, using the same procedures and initial list of groups.

Two additional groups, one from LibraryThing and one from Goodreads, were used for a pilot study of the content analysis procedures, selected at random using the same procedure as above but with only criteria (c) and (d) applied. As with the main sample, the moderator for the Goodreads group selected was contacted to obtain his approval and consent prior to data collection; the moderator of the first group did not respond within two weeks, so a new group was selected. These two groups were selected in December 2012, earlier than the main sample, using the two lists of groups as they were at that time. For the pilot, threads were selected systematically and at random from the threads shown on the group’s front page (i.e. the most recent and active threads) until the total messages per group reached between 50 and 60; in both cases only one thread was selected containing 60 messages. Any thread with fewer than two messages was to be excluded from selection. All messages in the selected threads, up to the 60-message limit, were part of the sample for the pilot test, which totaled 120 messages. At 20% the size of the intended sample for the main content analysis phase, the pilot sample provided sufficient data to assess if the proposed procedures were appropriate and how long this phase of the study would take. The pilot study allowed adjustments to be made for the main content analysis phase, based on problems and difficulties observed.

For the main content analysis phase, the ten groups were selected on April 30, 2013, a later date than the two for the pilot test, using the two lists of groups as they were as of that day. A few weeks later, threads were systematically selected at random from the threads shown on each group’s front page (i.e. the most recent and active threads) until the total messages per group reaches between 50 and 60. As with the pilot, any thread with fewer than two messages was excluded from selection. No more than the first 20 messages in each thread selected were part of the sample, a change from the pilot test made to ensure at least three threads per group were selected and improve the representativeness of the sample. This was intended to lead to a total sample of between 500 and 600 messages, about half from LibraryThing and half from Goodreads. The samples in practice consisted of 286 messages from LibraryThing and 233 from Goodreads, for a total of 519 messages (see also Chapter 4 , section 4.1 ). For all random and systematic sampling in the pilot and main data collection stages, the starting point and interval was chosen by generating random numbers using Microsoft Excel’s RANDBETWEEN function.

This stratified random sampling procedure was chosen to encourage representativeness of the resulting sample while ensuring data allowing for meaningful analysis was selected. Messages, threads, or groups could be selected purposively, but such a method could result in a sample biased towards a given type of message, thread, or group. Random sampling of groups and threads from the population deemed useful for analysis produced a sample of messages from LibraryThing and Goodreads that can be judged to be quite representative, if not quite equivalent to one generated from simple random sampling since the sampling frames did not include the entire population of groups. The sizes of the sample at each stratum were chosen to balance representativeness against the time and resources necessary to complete content analysis.

3.4.3. Data Collection Procedures

Messages were collected by using a Web browser to access the LibraryThing and Goodreads web sites, following the sampling procedures discussed above. Once a thread was displayed on the screen, up to 20 messages from the thread—starting with the earliest messages—were copied and pasted into a Microsoft Word document; one such file was maintained per thread. As found in the digital libraries, each message’s author, date/time posted, and message content was saved to that file. Images or other media included were saved in their original context as best as possible. Members’ identities, as indicated by their usernames, were used to allow for identifying common message authors in a thread, for analysis of the flow of conversation, and for identifying potential participants for later phases of the study. Identities remained confidential and were not be part of further analysis, results, or publications; psuedonyms are used in this dissertation (see section 4.1 ). Avatars from Goodreads were discarded, as members’ usernames were sufficient for this purpose. These documents were stored as discussed in section 3.8 on data management.

3.4.4. Data Analysis

For analysis, the documents were imported into NVivo qualitative analysis software, version 10, running on a MacBook Pro via a virtualized Windows 7 installation. Each message was examined and codes were assigned based on its latent meaning and interpretation. The codes to be assigned drew from boundary object theory, the social worlds perspective, and the theory of information worlds, which served as an interpretive and theoretical framework for the content analysis (cf. Ahuvia, 2001). These codes were common to multiple phases of this study, and can be found in section 3.7 below. So-called "open" codes, not included in the list but judged by the researcher to be emergent in the data and relevant to the study’s purpose and research questions, could be assigned during the content analysis and coding process, as recommended by Ahuvia (2001) for interpretive content analyses and others for general qualitative data analysis (e.g. Charmaz, 2006). Findings from the data as coded and analyzed, including open codes, are included in Chapter 4 , section 4.1 .

3.4.4.1. Pilot test

These coding and analysis procedures were piloted first, using data from two of the groups, prior to their use in the main content analysis phase. Two volunteer coders, doctoral students at the FSU School of Information [1] , applied the coding scheme and procedures developed for analyzing qualitative data in this study, presented in greater detail in section 3.7 below. The researcher applied the same scheme and procedures. Measures were in place to ensure the validity, reliability, and trustworthiness of the data and analysis, as discussed in section 3.9 below. Both intercoder reliability statistics and holistic, qualitative analysis of the results were used to clarify the scheme and procedures after each round of coding. Changes that were made to procedures and the coding scheme, and issues encountered with intercoder reliability statistics, are discussed at length in section 3.7 below.

3.5. Survey

Surveys are a common research method in the social sciences, including library and information science. They allow characteristics of a population to be estimated, via statistics, through analysis of the quantified responses given to questions by a small sample of the population (Fowler, 2002; Hank, Jordan, & Wildemuth, 2009; Sapsford, 1999). Surveys consist of "a set of items, formulated as statements or questions, used to generate a response to each stated item" (Hank et al., 2009, p. 257). The data collected may describe the beliefs, opinions, attitudes, or behaviors of participants on varied topics, although most research surveys have a special purpose and focus (Fowler, 2002). This is true in the case of the survey used here, which focused on obtaining data on uses of LibraryThing and Goodreads by a sample of its users, in the specific context of their usage as boundary objects within and across social and information worlds.

The following sections cover the components of survey research methods cited by Fowler (2002, pp. 4–8) and Hank et al. (2009) as they apply to the survey used in this study. These include discussion of the unit of analysis, population, and sampling (sections 3.5.1 and 3.5.2 ); concept operationalization and survey question design (sections 3.5.3 ); pretesting and data collection ( section 3.5.4 ); and data analysis ( section 3.5.5 ). The survey was designed as a coherent whole—as recommended by Fowler (2002, p. 7)—and in relation to the content analysis and interview methods used in other phases of the study.

3.5.1. Unit of Analysis

For the survey phase of this dissertation study, the unit of analysis was the individual LibraryThing or Goodreads user . These users were—and are—understood to be members of one or more communities, social worlds, or information worlds, and to be members of or frequent one or more LibraryThing or Goodreads groups. Analysis of their responses to questions about these groups and other communities they were part of allowed for greater understanding of the roles the digital library plays for them in context of these worlds. Tentative conclusions could be made about the nine groups from which users were surveyed and about the communities associated with these groups, but generalization to LibraryThing and Goodreads as a whole was not possible, as explained in section 3.5.2 below.

3.5.2. Population and Sampling

The broader population of LibraryThing and Goodreads users totals over 26 million people, and the logistics of constructing anything resembling a sampling frame—i.e. a complete list of all users of the two sites—are all but impossible. Given the focus in the content analysis phase on nine groups (five from LibraryThing, four from Goodreads), narrowing the population to include any user who visits, frequents, or is a member of one or more of these groups made the task of sampling possible and the population compatible with the population of messages used in the content analysis phase. This narrowing of population led to a less representative population than that of all LibraryThing and Goodreads users, limiting the kinds of analysis that could be done of the survey (further details below and in Chapter 4 , section 4.2 ,).

Two sampling methods were used to select potential survey participants from this population:

• A purposive sample, consisting of all LibraryThing users who posted a message within the five LibraryThing groups selected for the content analysis phase. The pool of messages included the messages selected for the main sample in the content analysis phase. (Goodreads did not consent to messaging of Goodreads users for this purpose, so Goodreads users were excluded from this sample.)
• A convenience sample, consisting of all LibraryThing and Goodreads users who responded to an invitation to participate posted to each of the nine groups selected for the content analysis phase (procedures detailed in section 3.5.5 below).

All users who met the criteria (having posted a message or responded to the invitation) and human subjects requirements for age (between 18 and 65) were allowed to participate, helping to increase the responses collected and the representativeness (as best as possible) of the results obtained.

A true random sample, even from the narrower population, could not be drawn because the researcher could not generate a complete list of visitors to and members of the selected groups. Obtaining such a list from LibraryThing and Goodreads—or the group moderators, should they have access to one for their group—would have placed an unreasonable burden on the digital libraries and could have jeopardized their cooperation in and the successful completion of this study. Such a list would have violated the privacy rights of the members of these groups. A random element is included in the sampling process by using the random groups selected during the content analysis phase, but the sample still lacks much of the representativeness of a true random sample. Users could choose to participate or not and not all users of the nine groups were guaranteed to see the invitation, making it impossible to infer beyond the sample due to selection bias. One may assume survey respondents are at least moderately representative of the population of users of the nine LibraryThing and Goodreads groups, and so conclusions can be inferred about those users through nonparametric statistics. Further details are given in Chapter 4 , section 4.2 .

3.5.3. Operationalization of Concepts and Instrument Design

The phenomena of interest for the survey were similar to the phenomena of interest in the content analysis and interview phases of the study: the concepts of boundary objects, translation, coherence, information worlds, social norms, social types, information values, information behaviors or activities, social worlds, organizations, sites, and technologies. Conceptual definitions for these are found in boundary object theory, the social world perspective, the theory of information worlds, and the synthesized theoretical framework for social digital libraries (see Chapter 2 ). For the purposes of the survey and in the context of answering the research questions of this study, these concepts were operationalized through a set of Likert scaled questions (Brill, 2008; McIver & Carmines, 1981), adapted from the conceptual definitions found in the literature, theories, and synthesis thereof. These questions can be found as part of the survey instrument in Appendix B , section B.1 .

Four to six Likert items (Brill, 2008; McIver & Carmines, 1981) for each of the concepts and phenomena of interest were included in the survey. A symmetric five-point scale was used for each item, as is traditional for Likert items (Brill, 2008); five response choices provides for higher levels of reliability without offering respondents too many choices (Brill, 2008), and questions can be re-scaled without significant loss of statistical validity (Dawes, 2008). Each item used the following labels for response choices: Strongly Agree(5), Agree, Neutral, Disagree, and Strongly Disagree(1). In analysis, each of the items was assigned a numeric rating (5–1) and summed to form Likert scales for each phenomenon (Brill, 2008; McIver & Carmines, 1981). Statistical analysis checked the internal consistency and reliability of each scale, with items dropped that contributed to lower levels of reliability (see sections 3.5.5 and 3.9 below, and Chapter 4 , section 4.2.1 ). Using at least four items per scale allowed for appropriate statistical analysis to proceed.

Questions were developed, based on the literature and theoretical framework reviewed in Chapter 2 , to measure each of the phenomena of interest. Hank et al. (2009, pp. 257–258) provided a list of suggestions for constructing survey instruments and writing questions: ensure questions are answerable, stated in complete sentences, use neutral and unbiased language, are at an appropriate level of specificity, and are not double-barreled. They suggested participants should not be forced to answer any one question. Fowler (2002, pp. 76–103) included a chapter on designing questions that are good measures in his book on survey research methods. He cautioned researchers to be careful questions are worded adequately; mean the same to and can be understood by all respondents; can be answered given the respondents’ knowledge and memory; and do not make respondents feel uncomfortable and desire not to give a true, accurate answer. According to Fowler, researchers should not ask two questions at once. Sapsford (1999, pp. 119–122) agreed and suggested care should be taken to ensure questions are precise, lack ambiguity, and are easy to understand and in colloquial language. The questions developed for the survey in this study, found in Appendix B , section B.1 , were developed by the researcher and reviewed by the researcher and his supervisory committee in light of this advice.

An additional set of demographic and usage questions was part of the survey instrument, in a separate section at the end as recommended by Peterson (2000, as cited in Hank et al., 2009, p. 258). These questions allowed for collection of data on other variables of potential relevance to and having possible impact on the phenomena of interest, including use of the Internet, LibraryThing and Goodreads, the groups feature of the sites, and other social media and social networking web sites; and demographic factors such as age and gender. These demographic questions can be found in Appendix B , section B.1 .

3.5.4. Data Collection Procedures

3.5.4.1. pretest.

The first stage of data collection was to pretest the survey instrument to help ensure its reliability and validity (Hank et al., 2009, p. 259). A convenience sample of graduate students and graduate alumni of Florida State University was invited to pretest the survey and answer a few short, open-ended questions about their experience. Recruitment took place via face-to-face discussion, e-mail, and Facebook messages. All pretesters came from the School of Information; initial attempts were made to have this sample represent multiple departments from the university, but no students from other departments contacted (Business and Communication) volunteered. Flyers were posted later in the pretest period and the survey opened up via a direct link, to see if undergraduate or graduate students from other departments would be interested, but no responses were received through the link. One School of Information faculty member did volunteer his time to pretest the survey, and his input was welcomed alongside the students. Minor changes were made as a result, reducing the number of questions slightly to reduce perceived repetitiveness and clarifying other questions that pretesters reported getting stuck on. The pretest helped confirm the length of time for completion of the survey.

3.5.4.2. Main survey

The second stage of data collection was to select the samples discussed in section 3.5.2 and send invitations to participate to them. A couple of weeks before this began, the researcher contacted LibraryThing and the moderators of each Goodreads group to inform them of the beginning of the survey. A staff member from LibraryThing posted a short message in each group to let users know that the research would be taking place and had been given LibraryThing’s approval, to ensure invitations were not seen as spam. (LibraryThing required this step as part of their approval of the research; see Appendix E , section E.1 .) Goodreads moderators were welcome to inform their groups of the upcoming research.

The purposive sample was drawn from LibraryThing users who posted messages collected during the content analysis phase. Each of these users was sent an invitation letter, included in Appendix A , section A.2.1.1 . The private message features of LibraryThing were used to send the invitations to the selected users; while LibraryThing users can include an e-mail address in their profile, not all did so. Reminder invitation letters ( Appendix A , section A.2.1.2 ) were re-sent two weeks and four weeks after the beginning of data collection to remind individuals who had not completed the survey and thanking users who had. The convenience sample was drawn by posting an invitation, included in Appendix A section A.2.2 , to each of the LibraryThing and Goodreads groups selected during the content analysis phase. This invitation was re-posted to the same groups two weeks and four weeks after the beginning of data collection, to help ensure as many group members and visitors as possible saw it and had a chance to respond. Permission was granted by LibraryThing and Goodreads staff for this method of data collection (see Appendix E , sections E.1 and E.2 ).

Participants were given a total of six weeks to complete the survey from August 26th, 2013, the date data collection first began for this phase of the study. The survey was expected to take users about 15 to 20 minutes, an estimate confirmed by the pretesters—with more subject knowledge—taking between 7 and 16 minutes. The reminders at two and four weeks, number of visitors to and members of the nine groups, and number of users directly invited on LibraryThing led to sufficient data for analysis (see Chapter 4 , section 4.2 ), although snowball sampling and other techniques were held in reserve in case they were necessary.

3.5.4.3. Compensation

To encourage participation, compensation was offered in the form of a drawing for one of ten $25 Amazon.com, Barnes and Noble, or Books-A-Million gift cards. These stores were selected since they include the most popular online bookstore—Amazon.com, who after this selection was made acquired Goodreads—and the two most popular brick-and-mortar bookstores (which also have an online presence). Participants were given a choice of which store they would prefer, increasing the potential usefulness of the gift card to them and reducing potential bias created by supporting only one store. Other bookstores are smaller, do not offer online gift cards, or have few locations; offering gift cards from every possible store would present logistical challenges. The e-mail addresses of all participants who completed the survey and included an e-mail address in their response were entered into a Microsoft Excel spreadsheet (maintained under the data management procedures detailed in section 3.8 ). Gift card codes were e-mailed to 10 random e-mail addresses—selected by using Excel’s RANDBETWEEN function to generate 10 random numbers between 1 and the number of users who took the survey, then selecting those users from the spreadsheet—for the store they selected as preferred; these were sent on November 9 th , about one month after the survey was closed. Funds for the gift cards came from a Beta Phi Mu Eugene Garfield Doctoral Dissertation Fellowship, which I acknowledge and am thankful for.

3.5.4.4. Online hosting

The survey instrument was hosted online using Qualtrics online survey software, made available by FSU to all students and faculty. An online, Internet-based survey provided the greatest chance of reaching users of LibraryThing and Goodreads in the context of their use of the site and their interactions with other users. It cost less—survey hosting for a questionnaire of any length is provided free by Qualtrics in association with FSU—and took less time than a self-administered paper survey was expected to, while providing for honest answers and requiring less direct researcher involvement compared with an administered paper or telephone survey (Fowler, 2002, pp. 71–74). Participants completed the survey by following a link in the invitation letters; two separate links were used for users of LibraryThing and Goodreads, so that the survey could be personalized to refer to each digital library by name.

3.5.4.5. Consent and follow-up

The first page of the survey included an informed consent statement, included in Appendix A , section A.2.3 , which participants had to agree to before they could begin answering the survey questions. As seen by the last few questions in Appendix B section B.1 , participants were asked for their e-mail address for purposes of compensation, if they were interested in participating in a follow-up interview, and if they desired a report of the findings of the research once the study was complete. These e-mail addresses are being kept confidential and are stored in a secure, password-protected encrypted volume, the password known to the researcher but no one else. Details of data management are discussed in section 3.8 .

3.5.5. Data Analysis

The survey results were analyzed using SPSS statistical analysis software running on Windows, accessed through a virtual lab environment supported by FSU. First, the Likert scales were analyzed to determine the internal consistency and reliability of the scales via Cronbach’s alpha, following the procedures related by George and Mallery (2010). Individual items were dropped from a scale if their removal would increase the Cronbach’s alpha (and the reliability) of the overall scale. This procedure and its results are detailed in Chapter 4 , section 4.2.1 . The average of the remaining items in the scale was then taken, resulting in one value ranging from one to five for each of the concepts being measured. Combined with the demographic variables collected in the second half of the study, these were analyzed using appropriate, mostly nonparametric statistics including chi-square analysis, Mann-Whitney U tests, median tests, Kruskal-Wallis tests, Wilcoxon signed rank tests, and Kendall’s τ correlations (see Chapter 4 , section 4.2 for details).

3.6. Interviews

Qualitative interviewing, used in the third phase of this study, is a descriptive and interpretive research method that seeks meaning (Kvale & Brinkmann, 2009). While interviewers may seek basic facts, explanations, and statistics, nuanced explorations and descriptions of phenomena are of core interest. Interviews in qualitative and mixed-methods research projects are used "to understand themes of the lived daily world from the [participants’] own perspectives" (p. 24), through researcher interpretation of "the meaning of the described phenomena" (p. 27). Interviews for research purposes are often seen as a form of "professional conversation" (p. 2; see also Lincoln & Guba, 1985a, p. 268; Sutton, 2010, p. 4388) between the interviewer and the interviewee, on given themes introduced by the interviewer but assumed to be of mutual interest to the interviewee. The two "act in relation to each other and reciprocally influence each other" (Kvale & Brinkmann, 2009, p. 32). Interviewees choose specific instances, examples, or areas within the chosen theme(s) to discuss with the interviewer.

Interviews serve as a source of data on phenomena from the past, present, or (potential) future of interviewees, including "persons, events, activities, organizations, feelings, motivations, claims, concerns, … other entities" (Lincoln & Guba, 1985a, p. 268), and the complex interrelations between all of these. Interviews can help to verify ("member check"), extend, and triangulate data and information already obtained via other methods (Creswell & Plano Clark, 2011; Lincoln & Guba, 1985a). They allow for the gathering of research data when the researcher or his/her colleagues cannot conduct an ethnographic participant observation due to time, location, language, or other constraints (Sutton, 2010).

This dissertation study used semi-structured qualitative interviews employing the critical incident technique (Fisher & Oulton, 1999; Flanagan, 1954; Woolsey, 1986) to explore and describe the phenomena surrounding the roles of LibraryThing and Goodreads, as boundary objects, within and across social and information worlds. Interviews helped find nuances and details that were not possible to determine through the survey questionnaire and were missed, glossed over, or not observable during content analysis. The following sections discuss the strengths of interviews for this study, the chosen unit of analysis, population and sampling procedures, design of the interview instrument, procedures used for conducting the interviews, and data analysis.

3.6.1. Strengths of Interviews

The strengths of qualitative interviews are a good fit with the framework and perspective taken in this dissertation. These strengths are evidenced by many of the studies of social digital libraries reviewed in Chapter 2 using interviews (Bishop, 1999; Bishop et al., 2000; Chu, 2008; Farrell et al., 2009; Marchionini et al., 2003; Star et al., 2003; Van House, 2003; You, 2010) and the frequent use of interviews in studies of social and information worlds and of boundary objects (see Burnett, Burnett, et al., 2009; Burnett, Subramaniam, et al., 2009; Chatman, 1992; Clarke & Star, 2008; Gal et al., 2004; Gibson, 2011, 2013; Kazmer & Haythornthwaite, 2001). Thick, nuanced description of meanings, close to users’ thoughts (Forsythe, 2001; Geertz, 1973; Kvale & Brinkmann, 2009), was intended to help expose the social construction of these meanings and of the phenomena of social and information worlds, which happened (see Chapter 4 , section 4.3 ). Since true ethnographic observation would be difficult to arrange and could miss the social elements of interest, qualitative interviews were the best choice for returning rich, descriptive data on participants’ social and information worlds and the roles LibraryThing and Goodreads play in them. The qualitative interviewing literature states that its flexibility as a technique addresses the different contexts interviewees—with varying interests and backgrounds—come from, allowing the interviewer to adjust (Kvale & Brinkmann, 2009; Westbrook, 1997); this was true in practice in this case. The development of rapport can build opportunities for future follow-up, longitudinal research with the same participants, exploring the results of this study in greater detail (Westbrook, 1997). The understanding of participants of the roles of LibraryThing and Goodreads in the social and information worlds they are part of is at the core of this study, and the obtaining of descriptions and perspectives of participants’ "lived worlds" and their "understanding of the meanings in their lived world" was an appropriate use of interviews and played to their strengths (Kvale & Brinkmann, 2009, p. 116).

3.6.2. Unit of Analysis

The unit of analysis chosen for the interview phase of the study was the individual user of LibraryThing or Goodreads. These users were understood, as in the survey phase, to be part of one or more social or information worlds, and their participation in and responses to the interview informed analysis of the roles of LibraryThing and Goodreads in their experiences, in these existing worlds, and in the potential emergence of new worlds. As discussed above and in Chapter 2 , while individuals were interviewed the theoretical framework underlying this proposed study allowed for multi-leveled analysis, taking advantage of the strengths of interviews over other methods while minimizing their weaknesses.

3.6.3. Population and Sampling

The broader population of LibraryThing and Goodreads users totals over 26 million people; as with the survey phase of the study, sampling from this large population would present major logistical challenges. Given the existing sample of users selected to take the survey, restricting the sample of potential interview participants to this subgroup of the population—a ready-made sampling frame—provides a manageable task, if perhaps not anything approaching a true random sample. This method of sampling is appropriate in this case since data is available from the survey about these users, their social and information worlds, and the roles LibraryThing and Goodreads may play in them, leading to more insightful interview data.

The interview phase used purposive sampling of users whose survey responses indicated they could provide insightful data on the roles of LibraryThing and Goodreads in existing and emergent social and information worlds. Determination of this indication was done by looking at the content analysis and survey findings and prioritizing which scores on which variables were most of interest. Users who indicated they would be willing to participate in follow-up research served as the sampling frame, from which participants were sampled and chosen with an eye towards obtaining thick description (Geertz, 1973) of the picture of the phenomena under study, given other constraints such as time and availability. As interviews continued towards saturation, these criteria were reviewed and revised, and ensuring that interviewees were at least moderately representative of the group of survey participants became a concern. True and complete representativeness is not necessary when using qualitative interviewing, but saturation of findings is a necessary requirement (Bauer & Aarts, 2000; Gaskell & Bauer, 2000; Westbrook, 1997), and so sampling continued "until further exemplars"—interviewees in this study—"fail[ed] to add new nuances or to contradict what is understood" from the existing collected data (Westbrook, 1997, p. 147). This sampling method was chosen to obtain data to answer the research questions—from the interviews and in combination with findings from the other two methods—and to provide an accurate representation of LibraryThing and Goodreads in the context of the communities of users from the nine groups selected at the beginning of the content analysis phase.

Participants who were selected due to expectations they would provide insightful data through an interview were invited to take part via the e-mail addresses they provided when confirming their willingness to participate in an interview. The letter prospective interviewees were sent is in Appendix A , section A.3.1 . An initial sample of six prospective interviewees—three from each digital library—was e-mailed at first, to allow interviews to be arranged within a week or two of the contact date and not be forgotten about by participants if scheduled too far in advance. Further prospective participants were invited every week or two thereafter, when necessary to increase the sample size. If and when selected users did not respond to the initial request, a second request was made one to two weeks later, except in the cases at the end of the interview data collection when saturation had been reached. New users replaced the original ones in the sample if the latter did not respond after two to three weeks.

3.6.3.1. Pretest

Prior to collection of actual interview data, the interview instrument and procedures (as discussed in the next two sections) were pretested with an additional convenience sample of two FSU School of Information alumni and one FSU School of Information faculty member who helped pretest the survey. The procedures for this were identical to the procedures discussed below for the main interview phase. Pretesting allowed for potential refinement of the instrument and procedures, ensuring questions are understandable by a broader population, and making any necessary adjustments to the sampling method for the main interviewing process. No transcriptions or data analysis from this pretest took place, and audio recordings that were made to test procedures were only used to refine the interview instrument and procedures; they were deleted once the main interviews began. No specific changes were made to the instrument, although the potential need for additional prompting in association with a few questions was observed; quirks and foibles of the recording software were discovered, leading to tighter and more careful following of recording steps for the main set of interviews.

3.6.4. Instrument Design

The interviews were semi-structured; they used an instrument as a guide, but were treated as a conversation guided by the interviewer’s questions and the interviewees’ personal responses and reflections (Kvale & Brinkmann, 2009; Lincoln & Guba, 1985a). The instrument, included in Appendix C, provided pre-planned questions and themes, but additional follow-up questions and prompts not included in the instrument emerged from the conversation and its natural progression. This allowed key themes related to the research questions to be discussed and focused on without restricting the interview to no more than a given set of questions in advance (cf. Suchman & Jordan, 1990).

Key themes explored in the interviews included

• participants’ use of LibraryThing or Goodreads, focusing on use as a boundary object;
• the social and information worlds of participants, and their relationship to LibraryThing or Goodreads;
• the characteristics of these social and information worlds—their social norms, social types, information values, information behaviors, activities, organizations, sites, and technologies—and their impact on the user and their use of LibraryThing or Goodreads;
• translation between, coherence across, and convergence of social and information worlds, via LibraryThing or Goodreads; and
• the emergence of new social or information worlds through translation, convergence, or related activities and behaviors of LibraryThing or Goodreads users.

Focusing on critical incidents (Fisher & Oulton, 1999; Flanagan, 1954; Woolsey, 1986) of times when users interacted with others using the LibraryThing or Goodreads digital libraries helped provide a rich environment and context for exploration of these themes in detail with each interviewee. Among the interviews the degree of focus by individuals on the critical incident versus the broader spectrum of their use varied, but this was accepted as a natural, emergent element of the interviews, and follow-up questions and prompts were used to ensure sufficient data was elucidated on the incidents. The questions included in the instrument and in prompts and follow-ups used drew from the advice set down by Kvale and Brinkmann (2009, pp. 130–140) in their discussion of scripting interviews and types of interview questions, including

• introducing themes before asking detailed questions;
• focusing on descriptions of what occurred and how during critical incidents, instead of why it happened (at least to begin with);
• following up on responses as appropriate;
• seeking projection of interviewees’ opinions or the opinions of others in their social and information worlds; and
• checking the researcher’s interpretation of previous findings and interview responses.

3.6.5. Data Collection Procedures

As mentioned above, prior to collection of actual interview data the interview instrument and procedures was pretested with two FSU iSchool graduate alumni and one FSU iSchool faculty member.

3.6.5.1. Preparation and recording

After participants agreed to be interviewed by replying to the invitation discussed in section 3.6.3 , a specific date and time was arranged for the interview to take place. Since no participants were at locations close to Tallahassee (and few were expected to be), face-to-face interviews would have been difficult to accomplish. For this reason, it was planned that interviews would take place using online audiovisual media, as popular in studies of "Internet-based activity … where the research participants are already comfortable with online interactions" (Kazmer & Xie, 2008, pp. 257–258). Interviewees were offered a choice of Skype (skype.com), Google Hangouts (accessible via plus.google.com), Apple FaceTime (apple.com), or telephone. Interviews were audio recorded, with interviewee permission; GarageBand (apple.com/ilife/garageband) and Soundflower (cycling74.com/products/soundflower) software were used to record Skype and Apple FaceTime calls, while telephone calls were recorded via Google Hangouts, Google Voice (voice.google.com), GarageBand, and Soundflower software. No users chose Google Hangouts, and more than expected chose telephone calls; while online audiovisual media were the intended plan, interviewees’ preferences were attended to, and this did not cause any major issues with collecting interview data.

The interviewer took any notes he felt necessary on his impressions of the interview as soon as the interview has concluded, to not distract the interviewee with note taking but help ensure an accurate capturing of the interview process. Most interviews took between 40 and 55 minutes; full details are given in Chapter 4 , section 4.3 . These interview procedures allowed for a level of data equivalent to or greater than face-to-face interviews to be gathered, eliminating any potential weaknesses from a non-traditional interview setting while maintaining the strengths of synchronous interviews (Kazmer & Xie, 2008).

3.6.5.2. Introduction and informed consent

The interview process began with introductions, thanking the interviewees for participating, explaining the logistics of the interview, and ensuring that informed consent was obtained. Since obtaining written consent in person was not possible, participants were e-mailed a link to a page (the content for which is shown in Appendix A , section A.3.2 ) requesting their consent for the interviews, including the interview informed consent form, a couple of days before the interview. (This used the same FSU-partnered Qualtrics system as for the survey.) I requested interviewees to review this page and ask any questions they had. Before the interview recording began, consenting participants clicked an "I consent" button at the bottom of the page; some did this before audio or video contact was made, others waited until I directed them there just before the interview began. I then reviewed "the nature and purpose of the interview" with the interviewee, to ensure they knew the overall theme and topic of discussion (Lincoln & Guba, 1985a, p. 270). Prior to the critical incident portion of the interview, I asked a general, "grand tour"-type question (with follow-up prompts as necessary) to explore participants’ use of LibraryThing or Goodreads, the reasons for this use, and the groups they participate in.

3.6.5.3. Critical incident technique

The biggest portion of the interview employed the critical incident technique, a flexible interviewing technique intended to obtain "certain important facts concerning behavior in defined situations" (Flanagan, 1954, p. 335). First developed for use in aviation psychology, it has become a popular interviewing technique in the social sciences, education, and business, including LIS (Butterfield, Borgen, Amundson, & Maglio, 2005; Fisher & Oulton, 1999; Urquhart et al., 2003; Woolsey, 1986). It is often used in exploratory research to build theories, models, or frameworks for later testing and refinement, as typified by Savolainen’s (1995) research establishing his Everyday Life Information Seeking (ELIS) model. Flanagan (1954) outlined five main stages in the technique. The first two stages are to provide further operational definitions and structure for interviews, which have been discussed in the sections above. The fourth and fifth, procedures for analysis and interpretation of data gathered from interviews, are discussed in sections 3.6.6 and 3.7 below.

The third stage is the actual collection of a critical incident from each interviewee. In a critical incident interview, after initial introductions and formalities, the interviewer asks the interviewee to recall an incident where given situation(s) or behavior(s) occurred, as defined during the previous stages. Per Flanagan (1954), these incidents should be recent enough to ensure participants have not forgotten the details of them. Specific language is used to get interviewees to think of such an incident. In this study, the following language was used, with slight changes incorporated in the context of a given interview:

Now I’d like you to think of a time within the past few weeks where you interacted with others, either people you already knew or people you did not know, while using [LibraryThing / Goodreads]. (Pause until such an incident is in mind, or gently prompt the interviewee if they have trouble recollecting one.) Could you tell me about this interaction and how it came about?

This initial question allowed interviewees to refresh their memory of the incident by going over it in their mind, and provided data on their overall impressions of the interaction and how it came about. After this initial discussion, I guided the conversation with gentle prompts and follow-up questions designed to steer the conversation about the incident to the themes mentioned in section 3.6.4 above. Main questions were included in the interview instrument (see Appendix C ); prompts were not. All questions and prompts were aimed at eliciting "the beliefs, opinions, … suggestions … thoughts, feelings, and [reasons] why participants behaved" that way during their interaction (Butterfield et al., 2005, p. 490), in the context of LibraryThing or Goodreads and the social and information worlds at play in the incident.

3.6.5.4. Finishing up

Once the critical incident had been explored at length, the interview concluded with final questions intended to help validate and generalize the findings obtained from the critical incident portion of the interview, a process often called "member checking" (Lincoln & Guba, 1985a). I gave an overall impression of the role or roles I felt LibraryThing or Goodreads played in the incident and in the interviewee’s overall use of the site, and would ask if the impression seemed correct to the interviewee or—if they responded before I could get to that part—engaged them in further reflective conversation. Interviews confirmed if the incidents participants shared matched their overall experiences. The interview concluded by me thanking interviewees for their time and participation, and answering any questions they had (as a couple did about where the research was going or when they would hear about the overall findings). As mentioned above, as soon as the interview was over I took time to write up any notes I felt were necessary, to capture any elements of the experience that risked being lost due to fading memory. Interviewees were then thanked again for their participation and help via e-mail follow-ups a few days to a week later.

3.6.6. Data Analysis

All interview audio was transcribed by the researcher, who used Audacity software (audacity.sourceforge.net) to play back the interview and Microsoft Word to enter the transcription. Parts found to be difficult to understand could be slowed down or amplified in volume using the built-in features of the Audacity software; it provided noise reduction features that were helpful for one or two interview recordings. Any notes taken not already in digital form were transcribed. All notes, audio, and transcriptions were stored as discussed in section 3.8 .

Data analysis proceeded in a similar fashion to the content analysis phase of the study. Transcripts and notes were imported into NVivo 10 qualitative analysis software, which was used to look over each file and assign codes to sentences and passages. As with the earlier qualitative method, the codes assigned draw from boundary object theory, the social worlds perspective, and the theory of information worlds, which served as an interpretive and theoretical framework for analyzing the meaning of interview responses. They can be found in section 3.7 below. Open codes not included in the list but judged to be emergent in the data and relevant to the study’s purpose and research questions could be assigned during the coding process, as recommended by Charmaz (2006) and Kvale and Brinkmann (2009, p. 202), among others; these codes included open codes from the content analysis phase. Measures to ensure the trustworthiness of the data and analysis were taken as discussed in section 3.9 .

3.7. Qualitative Data Analysis

All qualitative data—consisting of the messages collected for the content analysis and transcripts and notes from the interviews—were imported into NVivo 10 qualitative analysis software, which was used to look over each transcript and assign codes.

For analysis, an approach similar to grounded theory (Charmaz, 2006; Strauss & Corbin, 1994) and its constant comparative method was taken, but without the same focus on open coding. Codes were first applied to sentences in messages or in participants’ interview responses (as transcribed). Only the lowest, most detailed level of codes, as presented in the codebook (as 3.7.2 and 3.7.3 below), were applied. Two exceptions to sentence-level coding were allowed. For the content analysis phase, no more than two codes could be applied to an entire message if there was clear evidence for them throughout the message. For the interview phase, no more than two codes could be applied to a paragraph, answer to a question, or short exchange (no more than half a page) if there was clear evidence for them throughout the paragraph, answer, or exchange. No other exceptions were allowed to this rule; codes could not be applied to units smaller than sentences (to provide sufficient context), and were required to be applied individually to multiple messages, answers, or exchanges. Memos and annotations were made to explain any cases where code(s) were applied across multiple sentences within a message or interview transcript at once, and to explain codes in greater detail where deemed necessary; a general rule of "if in doubt, add an annotation" was followed throughout analysis. These rules were refined and clarified after initial pilot testing, details of which are given in section 3.7.1 below.

After initial analysis, higher levels of analysis looked at the coding in the context of paragraphs, entire messages, message threads, and larger portions of interview transcripts, considering these in light of other threads, messages, and interviews. Throughout the coding and analysis process, consideration of the social and information worlds was explicitly multi-leveled: worlds of multiple sizes, shapes, and types were considered throughout the processes of collecting and analyzing data. The boundaries of these worlds, and where these worlds fell on the continuum of existing and emergent worlds, was considered emergent from the data, based on the conceptual, theoretical, and operational definitions given in earlier sections and in the coding scheme below. Memos and annotations were provided to explain the levels of social and information worlds under consideration, especially when boundary-related codes were applied.

The search, query, and report features of NVivo were used in further analysis and the writing of sections 4.1 and 4.3 of Chapter 4 . While messages and individual interviews (as the units of analysis) and sentences within them were coded as individual units, higher level units—passages, threads, groups, social and information worlds, and LibraryThing and Goodreads—were considered as the analysis proceeded. This allowed findings and conclusions to be drawn at multiple levels, as can be seen in Chapters 4 and 5 .

3.7.1. Pilot Testing and Resulting Changes

Pilot testing of the coding scheme and analysis procedures was conducted prior to the content analysis phase. Two fellow FSU iSchool doctoral students, having basic familiarity with the theories incorporated into the theoretical framework used here, were recruited to test intercoder reliability. Each student volunteer was provided with a "quick reference" version of the coding scheme in sections 3.7.2 and 3.7.3 below, with the final version used by the researcher as a guide for analysis included in Appendix D . Pilot test coders were given a summary of the coding rules and guidelines discussed herein. The second volunteer discussed the coding scheme, rules, and guidelines at some length with the researcher—including some brief practice coding—before coding began, and both volunteers took part in debriefing sessions with the researcher after coding had been completed. The researcher and the first volunteer coded the messages selected for the pilot test of the content analysis phase—120 messages, 60 each from one LibraryThing and Goodreads group. Changes were made after this coding cycle based on intercoder reliability statistics—using Cohen’s (1960) kappa as calculated by NVivo—and qualitative and holistic analysis of the results, and a second cycle proceeded. Further changes were made after this second cycle.

Changes were made to address weaknesses identified in the original procedures, coding scheme, and theoretical framework, to help ensure theoretical and operational clarity. Changes made after the first cycle were as follows:

Codes were only to be applied at the sentence level, with two exceptions as mentioned earlier.

Memos and annotations were stressed, especially to explain codes applied at levels higher than the sentence level and to explain coding in greater detail where deemed necessary.

Boundaries of worlds were to be considered emergent from the data, with memos and annotations recommended to explain the level of social and information worlds under consideration.

Definitions for all concepts were refined and tightened.

Cases where social norms or information value had broad application, across substantial parts of a thread or interview, were to be memoed or annotated instead of coded, since the latter was seen to be of less use for later analysis.

Information behavior was tightened, to consider only behavior that was normative at some level and to exclude general occurrences of information behavior, since under the latter interpretation whole threads and interviews could be coded.

If it was unclear whether a new world—of any size or scale—had truly emerged, memos and annotations were recommended to express the degree of confidence.

Three subcodes were added to account for different cases of LibraryThing or Goodreads acting as a standard boundary object: as an emergent site, an emergent technology / ICT, or another type of emergent boundary object.

Changes were made after the second cycle of coding and discussion among the researcher and multiple committee members, as follows:

The distinction between existing and emergent was stressed to be along a continuum, and to be a phenomenon that would emerge from the research data, similar to the size and shape of the worlds and their boundaries. Memos and annotations were further stressed to elaborate on where given cases fall on this continuum.

Codes and procedures were acknowledged to be complex, and to be using theories that had not been combined in previous research; the theoretical framework is emergent. As such, intercoder reliability statistics—as run using Cohen’s (1960) kappa after each coding cycle of the pilot test and initially planned for a portion of the interview data—were considered a less appropriate measure of the potential trustworthiness, credibility, transferability, dependability, and confirmability of the findings than originally thought. Both pilot tests showed that reaching high statistical levels of intercoder reliability would require extensive training of other coders—difficult if not impossible in dissertation research—and much fine-tuning of rules and procedures, fine-tuning that does not fit the interpretive and social constructionist paradigms in use for this research. Other techniques for ensuring qualitative trustworthiness (Gaskell & Bauer, 2000; Lincoln & Guba, 1985), already built into the study (see section 3.9.3 ), would now be emphasized alongside intracoder reliability checking at the conclusion of the study; results of the latter are included in Chapter 4 .

The following sections present the coding scheme used for each research question, as revised after the pilot testing. Section 3.7.2 includes the codes focusing on existing social and information worlds (RQ1), while section 3.7.3 includes the codes focusing on emergent social and information worlds (RQ2). The distinction between existing and emergent was treated as along a continuum, where the degree to which a world is existing or emergent was allowed to emerge from the research data. Frequent memos and annotations were made on this during analysis. An operational definition is given for the concept each code represents, as used in the coding and analysis of data from the content analysis and interviews phases. These definitions come from the literature review presented in Chapter 2 and the theories and theoretical framework described therein, with contributions from definitions in the Oxford English Dictionary’s online version (oed.com) where necessary and appropriate. A summarized version of the coding scheme, used as a quick reference during coding and analysis, is included as Appendix D.

3.7.2. Existing Worlds

3.7.2.1. translation.

Star and Griesemer (1989) defined translation as "the task of reconciling [the] meanings" of objects, methods, and concepts across social worlds (p. 388) so people can "work together" (p. 389). Multiple translations, gatekeepers, or "passage points" can exist between different social worlds (p. 390). This was operationalized as the process of reconciliation and translation of meanings—taken to include understandings—between different people, social worlds, or information worlds.

3.7.2.2. Coherence

While Star and Griesemer (1989) never gave coherence an explicit, glossary-style definition, it can be conceptualized as the degree of consistency between different translations and social or information worlds. Boundary objects play a critical role "in developing and maintaining coherence across intersecting social worlds" (p. 393). Coherence was operationalized using the common characteristics of social and information worlds, coded under the definitions given below. Coding took place at the level of these characteristics, not for coherence in general.

Social norms : Burnett, Besant, and Chatman (2001, p. 537) defined social norms as the "standards of ‘rightness’ and ‘wrongness’ in social appearances" that apply in an information world. Jaeger and Burnett (2010, p. 22) restated this as "a world’s shared sense of the appropriateness—the rightness or *wrongness—*of social appearances and observable behaviors." Drawing from these, social norms were operationally defined as the common standards and sense of appropriate (right or wrong) behaviors, activities, and social appearances in an information world. In some cases, a substantial part of or an entire thread or interview could be seen as socially normative, but it was decided that in those cases the social norms code would not be applied to every message or sentence, as doing so would not be of much use for later analysis. Instead, a memo or annotation was made to note and discuss the application of social norms to large parts of a thread or interview.

Social types : Burnett et al. (2001, p. 537) defined social types as "the [social] classification of a person." Jaeger and Burnett (2010, p. 22) elaborated on this, stating social types are "the ways in which individuals are perceived and defined within the context of their [information] world." This was operationalized following the latter definition and to include explicit and implicit roles, status, and hierarchy.

Information value : Jaeger and Burnett (2010, p. 35) defined information value as "a shared sense of a relative scale of the importance of information, of whether particular kinds of information are worth one’s attention or not." Such values may include, but are not limited to, "emotional, spiritual, cultural, political, or economic value—or some combination" (p. 35). Values may be explicit and acknowledged, or implicit within message content or interview responses. A succinct operational definition, used in this study for coding, is that information value is a shared sense, explicit or implicit, of the relative scale of the importance—emotionally, spiritually, culturally, politically, and/or economically—of information and whether it is worth attention. As with social norms, if a substantial part of or an entire thread or interview was seen as expressing the shared information values of a world, the code was not applied to every message or sentence; instead a memo or annotation was used.

Information behavior and activities : Burnett and Jaeger (2008, "Small worlds" section, para. 8) defined information behavior as "the full spectrum of normative [information] behavior … available to members of a … world"; this was restated in different words by Jaeger and Burnett (2010, p. 23). Information behavior can include seeking, searching, sharing, or use of data, information, or knowledge; communication and interaction; and avoidance of data, information, or knowledge. Strauss (1978) did not provide an explicit definition of activities, but his use of the word within the social worlds perspective corresponds with one of its senses in the Oxford English Dictionary: "something which a person, animal, or group chooses to do; an occupation, a pursuit" ("Activity," 2012). A slight restriction was placed on this operationally, that the "something" should have an informational component (with information construed to include data and knowledge). Operationally, this code was used to identify occurrences of normative, chosen information behavior and information-based occupations or pursuits—defined broadly—by members of a world. Such behavior had to be normative at some level to be coded, and general occurrence of information behavior were not coded, since under such an interpretation whole threads and interviews could be construed as such.

Organizations : Strauss (1978) stated social worlds may have "temporary divisions of labor" at first, but "organizations inevitably evolve to further one aspect or another of the world’s activities." This sense is similar to the definition of an organization as "an organized body of people with a particular purpose" found in the Oxford English Dictionary ("Organization," 2012). A combination of the two was used for operational coding: organizations are organized, but possibly temporary bodies with the particular purpose of furthering one aspect or another of the world’s activities.

3.7.2.3. Boundary object

Codes were applied for treatment of the digital library as a boundary object. This was operationalized by coding passages where the digital libraries cross the boundaries between multiple existing social or information worlds and are used within and adapted to many of them "simultaneously" (Star & Griesemer, 1989, p. 408) while "maintain[ing] a common identity across sites" (Star, 1989, p. 46). Instances of the boundary object’s use as a common site and information and communication technology (ICT) were coded using the definitions below. Coding took place at the level of these characteristics, not for boundary objects in general.

Common site : Strauss (1978) related sites to "space and shaped landscape"; the term’s use under the social worlds perspective corresponds to this sense given in the Oxford English Dictionary: "a position or location in or on something, esp. one where some activity happens or is done" ("Site," 2012). This location may be a physical, virtual, or metaphorical space, as seen in many of the concepts of community reviewed in Section 2.2. A succinct operational definition, used for coding, is that sites are spaces, positions, or locations—physical, virtual, or metaphorical—where information-related activities and behaviors take place.

Common information and communication technologies (ICTs) : Strauss (1978) defined technology as "inherited or innovative modes of carrying out the social world’s activities" (p. 122). ICTs are often referred to in the literature of LIS, knowledge management, education, and other fields without explicit definition, and there is no one historical source all uses stem from. Remaining compatible with most of this literature and adapting from the definitions of Strauss (1978) and the Oxford English Dictionary ("Technology," 2012), ICTs were operationalized for coding purposes as inherited or innovative processes, methods, techniques, equipment, or systems—developed from the practical application of knowledge—used for carrying out information or communication-related behaviors and activities.

3.7.3. Emergent Worlds

3.7.3.1. convergence.

Convergence is seen in similar light to coherence, defined above as the degree of consistency between different translations and social or information worlds. Convergence was operationalized through the emergence of common characteristics in new social and information worlds (or proto-worlds), to be coded under the definitions given in section 3.7.2.2 above for social norms , social types , information value , information behaviors / activities , and organizations . Coding took place at the level of these characteristics, not for convergence in general; coding was kept separate from that for these characteristics under coherence. If it was unclear whether a new world—of any size or scale—had truly emerged, memos and annotations were made to express the degree of emergence seen in the data.

3.7.3.2. Boundary object as standard

Treatment of LibraryThing and Goodreads as a new, local standard for a new, emergent social or information world was coded in this category, to distinguish it from treatment of the digital libraries as boundary objects within and across existing information worlds ( section 3.7.2.3 ). This will be operationalized under three subcodes, where all coding would take place:

Emergent site : Under the definition of sites given above, cases of LibraryThing or Goodreads serving as an emergent, standard, and influential space, position, or location for information-related activities and behaviors were coded here. Clear evidence of the digital library serving as a new standard site for an emergent world was necessary. This code could be applied alongside the "emergent technology" code below, and in many cases this happened.

Emergent technology / ICT : Under the definition of technologies given above, cases of LibraryThing or Goodreads providing emergent and standard processes, methods, techniques, equipment, or systems—developed from the practical application of knowledge—used for carrying out information or communication-related behaviors and activities in an emergent world were coded here. Clear evidence of the digital library providing or serving as a new standard technology within an emergent world was necessary. This code could be applied alongside the "emergent site" code above.

Emergent boundary object : Cases where LibraryThing or Goodreads served as an emergent, standard boundary object, but not as a site or technology, were coded here. Clear evidence of the digital library serving as such a role was necessary, and clear evidence that it was not serving as a site or technology was required. This code was expected to be rare and in reality was; it was applied only a few times in the content analysis and not at all in the analysis of the interviews. It was included to ensure all cases of LibraryThing or Goodreads serving as a new, standardized boundary object wer captured. This code was considered mutually exclusive with the "emergent site" and "emergent technology / ICT" codes above.

3.8. Data Management

I have kept all data from this study in digital format on my personal laptop computer. Survey data was kept in Microsoft Excel (.xls/.xlsx) format, interview audio in .mp3 format, and messages and interview transcripts in Microsoft Word (.doc/.docx) format. A password protected and encrypted disk image was created and used for all dissertation data, the password known to the researcher but no one else. Within this image, separate folders were created for each phase of the study. All data analyzed using the coding scheme discussed in section 3.7 above—including messages, interview transcripts, and notes—was also kept in an NVivo project (.nvp) file at the top level within the image. This disk image will be kept until the date arrives for destruction of records from this dissertation.

Filenames for data served and continue to serve as metadata, reflecting the source of the data (participant pseudonym or group name for individual data, phase name for collated results), the date it was collected, the digital library the data refers to (LibraryThing or Goodreads), and the type of data it represents (e.g. thread, survey response, interview transcript, interview notes, preliminary analysis). For example, bob_GR_transcript_022914 . doc could be the filename for the transcript—in Microsoft Word format—of an interview with "Bob," a Goodreads user, conducted on the fictional date February 29, 2014. Three additional spreadsheets (in Microsoft Excel format) were created to provide metadata. Two—one for LibraryThing and one for Goodreads—link participants’ names and e-mail addresses to their psuedonyms; the other has kept track of survey data for interviewees, and was used during interview recruitment to help determine who would be invited to participate.

Encrypted and password-protected backups of all research data have been made on a weekly basis (with rare exceptions due to travel) onto an external hard drive kept at the researcher’s home. Additional encrypted and password-protected backups have and will be made onto recordable CDs or DVDs, to be kept in a filing cabinet belonging to the researcher in the Shores Building on FSU’s main campus or, once the researcher leaves FSU, in a similar secure work location. All research data for this study, including backups, will be deleted and destroyed by April 30 th , 2019 (this date being fewer than five years from the completion of the study). Appropriate excerpts from the data (using pseudonyms) and synthesized data analysis, findings, and conclusions—including the completed dissertation, journal articles, and conference papers—may be shared with other researchers, scholars, and the general public up to and beyond the date given above. Future research data and findings building on the data collected and conclusions drawn during this study may be shared with other researchers, scholars, and the general public, subject to restrictions put in place by the researcher’s home institution and funding source(s) at the time of such research.

3.9. Validity, Reliability, and Trustworthiness

3.9.1. holistic: mixed methods, case studies.

The validity and reliability of mixed methods studies can be assessed in two ways (Creswell & Plano Clark, 2011). One can look at the research as a whole, considering the study’s design, interrelations, and how everything fits together to ensure high levels of validity and reliability. Towards this view, Creswell and Plano Clark provided a list of potential validity threats in mixed methods research and strategies for minimizing these threats (pp. 242–243), which have been followed throughout the design and execution of this research.

Yin (2003) provided similar guidance for case study designs, summarized in his Figure 2.3 (p. 34). Each of these has been implemented in this study as follows:

"Use multiple sources of evidence": Three different methods of data collection have been used, each sampling across different groups and users from LibraryThing and Goodreads.

"Establish chain of evidence": The methods were linked together and informed each other. Data from content analysis helped inform the survey instrument, while the content analysis and survey data helped inform the interview instrument, process, and analysis. Data from all three methods has been tied together in the overall findings and conclusions from the study (see Chapter 5 ).

"Have key informants review draft case study report": While this specific technique was not used, I confirmed with interviewees that my impression of the critical incident they shared was accurate prior to the conclusion of each interview. Participants who requested a report of the findings on completion will receive one within a few weeks after defense of this dissertation.

"Do pattern-matching": Here Yin refers to looking for "several pieces of information from the same case [that] may be related to some theoretical proposition" (p. 26). This study achieved this by maintaining a consistent focus on the same phenomena throughout all three phases and using the same themes—based on the theoretical framework developed in section 2.8 —for coding the messages (in the content analysis phase) and interview transcripts (in the interview phase).

"Do explanation-building": Here Yin refers to establishing a cause-and-effect relationship between patterns in data and theoretical propositions. The pattern-matching above, combined with the theoretical framework discussed in section 2.8 and the philosophical and epistemological viewpoint provided by social informatics and social constructionism, allowed such explanations to be developed through synthesis of data from all three phases (see Chapter 5 , sections 5.1 and 5.2 ).

"Address rival explanations": While I admit favoring the theories used in the theoretical framework developed in section 2.8 , other theories related to communities, collaboration, information behavior, and knowledge management—reviewed elsewhere in Chapter 2 —could have provided a better explanation. The existing literature in these areas and my knowledge of them is used in later sections of Chapter 5 to address possibilities beyond the theoretical framework that relate to the findings seen here.

"Use logic models": Due to limitations of this study (see Chapter 5 , section 5.7 ), a visual model may be premature at this point. I may develop figures, diagrams, and other visual aids to help present the findings as part of posters, conference papers, journal articles, and research presentations.

"Use theory in single-case studies; use replication logic in multiple-case studies": While this is a multiple-case design, only two cases are considered here. Theory—the theoretical framework in section 2.8 —and replication logic—multiple groups and two digital libraries—have played important roles in the design and execution of this dissertation study.

"Use case study protocol": Constraints placed on procedures by the two sites were unavoidable, but where possible the same procedures were used for LibraryThing and Goodreads. Messages were collected and analyzed the same way; surveys distributed, collected, and analyzed the same way; and interviews followed the same themes and procedures. The extra requirement to obtain the consent of group moderators put in place by Goodreads prior to collecting messages and survey responses from users of that digital library did not cause great differences in the data collected or its comparability with that from LibraryThing groups. The researcher took care to document the study as it proceeded, including deviations in procedures that became necessary; the most notable of these was the need to vary the intended statistics and accept greater limitations on the survey results than were at first intended, as discussed above and in Chapter 4 , section 4.2 .

"Develop case study database": Given few cases in this study, a formal database was not constructed. The data management procedures discussed in section 3.8 and NVivo qualitative analysis software—which runs on a Microsoft SQL Server database—provided similar benefits to Yin’s recommendation here.

While holistic consideration of validity and reliability is useful, a second approach is necessary: examining the validity and reliability of each phase of a mixed-methods study—quantitative and qualitative—as an individual method. Each type of research has "specific types of validity checks" to perform (Creswell & Plano Clark, 2011, p. 239), since—despite the continuum mentioned by Ridenour and Newman (2008)—different methods require different measures of their reliability and validity. The two sections below take this approach and apply it to the quantitative—survey—and qualitative—content analysis and interview—phases of the dissertation study conducted here.

3.9.2. Quantitative: Survey

Validity and reliability for quantitative research are given substantial treatment in research methods textbooks, such as Schutt (2009, pp. 130–141) and Babbie (2007, pp. 143–149). The validity of the survey data can be broken down by the different types of validity these and other authors identify as used for quantitative research:

Face validity (Babbie, 2007, p. 146; Schutt, 2009, p. 132): Given that the survey questions were developed from the theories discussed in Chapter 2 and the theoretical framework developed in section 2.8 , each of which have face validity, the questions are judged to have met face validity for measuring the phenomena in question.

Measurement validity (Schutt, 2009, pp. 130–132): The survey questions were looked over by the researcher and his supervisory committee to ensure they did not suffer from idiosyncratic errors due to lack of understanding or unique feelings; from generic errors caused by outside factors; and from method factors such as unbalanced response choices or unclear questions. Attention paid to other kinds of validity helps improve measurement validity.

Content validity (Babbie, 2007, p. 147; Schutt, 2009, p. 132): Using multiple scales and multiple questions per scale helped the questions cover "the full range of [each] concept’s meaning" (p. 132) and the full range of the roles of LibraryThing and Goodreads in the social and information worlds of their users. The content analysis and interviews provided data from fewer users, but much thicker description of the phenomena of interest, as one would expect from qualitative research methods.

Criterion validity (Babbie, 2007, pp. 146–147; Schutt, 2009, pp. 132–134): This is difficult to measure here because no survey-based measures are known to have been developed for the theory of information worlds or boundary object theory prior to this study, and the social worlds perspective makes rare use of surveys. Schutt stated that "for many concepts of interest to social scientists, no other variable can reasonably be considered a criterion" (p. 134); Babbie (2007, p. 147) advocated using construct validity in these cases instead. Fowler (2002, p. 89) made a similar argument for questions "about subjective states, feelings, attitudes, and opinions," believing "there is no objective way of validating the answers … [they] can be assessed only by their correlations with other answers," through construct validity.

Construct validity (Babbie, 2007, p. 147; Schutt, 2009, pp. 134–135): Most of the measures used in the survey significantly correlated with each other, as one would expect given their relations to each other in the social worlds perspective and the theory of information worlds.

Reliability (Babbie, 2007, pp. 143–146; Schutt, 2009, pp. 135–138): While the survey was not repeated by each participant, using multiple measures of each concept and triangulation of the findings via the content analysis and interview phases of the study served a similar role to measures of test-retest or pre- and post-test reliability in an experimental design. The reliability of the scales was analyzed, while the randomization of survey questions (except the demographic questions) helped improve reliability.

3.9.3. Qualitative: Content Analysis and Interviews

A few qualitative and mixed methods researchers hold to positivistic treatments of validity and reliability, requiring use of quantitative measures such as intercoder percentage agreement, Holsti’s (1969) coefficient of reliability, Cohen’s (1960) kappa, or Krippendorf’s (2004b) alpha. Most qualitative researchers, however, argue validity and reliability should not be ported over from quantitative to qualitative research with no changes, nor ignored; instead they must be adapted and changed to fit the naturalistic and ethnographic nature of most qualitative research (Gaskell & Bauer, 2000; Golafshani, 2003; Kvale & Brinkmann, 2009; Lincoln & Guba, 1985b; Ridenour & Newman, 2008). Which adaptations and changes should be put into place for qualitative research is the subject of debate (Golafshani, 2003). Golafshani found "credibility, … confirmability, … dependability … transferability," and "trustworthiness"—the last term preferred by Lincoln and Guba (1985b)—to be the most often terms used to describe the validity of qualitative research. No matter what term is chosen, validity is "inescapably grounded in the processes and intentions of particular [qualitative] research methodologies and projects" (Winter, 2000, p. 1, as cited in Golafshani, 2003, p. 602). Dependability and trustworthiness were the closest linked to reliability in qualitative research by Golafshani (p. 601) and Lincoln and Guba (1985b).

This dissertation research study, while drawing from all of the sources cited above, adapted the criteria and techniques cited by Gaskell and Bauer (2000) and Lincoln and Guba (1985b) for ensuring the validity and reliability of the qualitative phases of the study. These are discussed below, following four broader categories of trustworthiness outlined by Lincoln and Guba.

3.9.3.1. Credibility

The sequential, multiphase design allowed for prolonged engagement with the environment—19 months from prospectus defense to dissertation defense—and persistent, detailed observation of the phenomena under consideration. Using an approach for coding and analysis similar to the constant comparative method of grounded theory (Charmaz, 2006; Strauss & Corbin, 1994) helped ensure breadth and depth. Methods were triangulated via the sequential, multiphase design, where each method reflexively informed and was informed by the others and the theoretical framework developed in section 2.8 . The theoretical framework provides two perspectives—the lenses of the social worlds perspective and the theory of information worlds—that were triangulated in analysis, and the researcher was and is familiar with other social theories, models, and concepts of information and information behavior, some of which apply to the findings (see the later sections of Chapter 5 ). Triangulation of multiple investigators was difficult given the individual nature of a dissertation project, but the input of the dissertation committee and the researcher’s colleagues was considered and welcomed at appropriate stages. Using member checking in the interview process and later methods in the sequential design to check earlier ones led to greater credibility for the study and produced a high level of communicative validity.

Statistical intercoder reliability testing, while used during the pilot testing of the content analysis procedures, was later and is now considered less appropriate for this study; the combination of theories incorporated in the theoretical framework was being used for the first time, and as such the coding scheme and framework should be considered at least somewhat emergent. The coding scheme and procedures are acknowledged to have been quite complex. Statistics such as Cohen’s (1960) kappa or Krippendorff’s (2004) alpha are not very compatible with this exploratory study, using an emergent framework, and following an interpretive approach to analysis (Ahuvia, 2001). The pilot testing of the content analysis procedures, incorporating intercoder reliability testing with Cohen’s kappa, showed that reaching high statistical levels of intercoder reliability would require extensive training of other coders—difficult if not impossible in dissertation research—and much fine-tuning of rules and procedures, fine-tuning that might be appropriate for a non-dissertation, post-positivistic study, but does not mesh with the interpretive and social constructionist paradigms in use here nor fit with the nature and resources of dissertation research. Intracoder reliability testing was performed, using percent agreement and Cohen’s kappa, for the content analysis and interviews; this is reported in Chapter 4 at the beginning of each section of findings. Stressing of the other measures discussed here to address credibility and qualitative trustworthiness is believed to have been enough to overcome any limitations caused by not using intercoder reliability statistics.

3.9.3.2. Transferability

Every effort was made in the prospectus to be transparent in how the research would be conducted, and such transparency carried over to the research and to writing this dissertation. The data collection for the content analysis and interview phases was constructed to provide valid and complete results, from reaching saturation, leading to insightful analysis; this has occurred. As seen in Chapters 4 and 5, the data allow for thick description (Geertz, 1973) of the phenomena in context, taken from messages and interview transcripts, which can allow other researchers to assess the potential transferability of the research findings to other settings.

3.9.3.3. Dependability

As discussed above, every effort has been made to be transparent in the conduct of this research. The data collection for the content analysis and interview phases provides valid and complete results, having reached saturation, leading to insightful analysis. I remained transparent with users who were surveyed and interviewed, disclosing the full and true purpose of the study and not engaging in deception. Using participants whose survey or content analysis data indicated they would provide interest and insight in an interview helped satisfy Gaskell and Bauer’s call for revealing and relevant findings, and I feel what is found in Chapters 4 and 5 also fits. By ensuring saturation was reached in the interviews, the dependability of the study is increased further. While the inquiry audit suggested by Lincoln and Guba was not implemented for this study, the process of defending the prospectus and dissertation and the guidance of the dissertation committee throughout the process has served a similar purpose.

3.9.3.4. Confirmability

The data analysis process included memoing, annotating, and note taking at appropriate moments, including reflective comments on the data and the researcher’s experience. The researcher noted any and all reflective comments on the research study, theoretical framework, data collection process, and data analysis process during all phases of the project. Triangulation (as discussed above) helped ensure confirmability. While the formal confirmability audit suggested by Lincoln and Guba—examining if findings, interpretations, and recommendations are supported by the data—was not implemented for this study, the process of defending the dissertation serves a similar purpose.

3.10. Ethical Considerations

This study is not known to have violated any ethical principles or procedures. The content analysis phase used messages accessible to the public, posted in LibraryThing and Goodreads groups, as its source of data. The identities of the users who posted each message remains confidential. Usernames have been used to allow for identifying common message authors in a thread, for analysis of the flow of conversation, and for identifying potential participants for later phases of the study, but have not been and will not be part of further analysis, results, and publications. Identities have remained confidential throughout the survey and interview phases of the study, and will continue to do so after a defended dissertation. Psuedonyms have been and will continue to be used in any published or unpublished reports of the results and conclusions, and any other data or information with the potential to identify participants to people familiar with them has been altered for the purposes of this dissertation and future presentation and publication.

Informed consent was obtained from participants in the survey and interview phases, before they completed the survey instrument or participated in the main portion of the interview, and—as required by Goodreads for use of their digital library as a setting for this research (see Appendix A , section A.1 )—from the moderators of Goodreads groups. Their participation was voluntary; any participant who wished not to complete the survey or be interviewed, or wanted to request an interview be stopped or their survey data be deleted, would have been accommodated and allowed to not take part in or withdraw from the study. Moderators had the same right when it came to deciding if their group would take part in the study as a whole. No users or moderators who had previously consented expressed feeling uncomfortable and wishing to withdraw. Some moderators and potential interviewees did not respond to invitations, and one potential interviewee did not show up for her interview time and never responded to inquiries, but it is unclear why she chose to withdraw or why others were not interested in—in some cases further—participation. If any participants wish to withdraw their data from the study in the future, after already completing the survey or having been interviewed, their survey results, interview transcript, interview audio recording, and notes taken by the researcher after their interview will be removed from the data collected and analyzed as best as is possible, although their data will have already been analyzed and affected the conclusions drawn from data analysis (seen in Chapter 5 ). This is an unavoidable consequence and will be dealt with as best as possible by the researcher, should it occur.

On the opposite end of the research lifecycle, in two of the LibraryThing groups—which will not be named to maintain confidentiality and not "rock the boat" where it is unnecessary—a small number of users (five to ten) responded to the survey invitation post with comments disliking the survey instrument or facing confusion over the questions asked. I answered the questions and queries as best as possible without causing excessive bias in the survey results, but there was not much that could be done to please some users. They were, strictly speaking, not expressing any uncomfortable feelings—if anything they made me more uncomfortable than my survey had done to them—but this is worth noting as a negative reaction. It was not the norm; most participants were happy to complete the survey without incident, and no harm or risks occurred to any participants, greater than those experienced in everyday life, as a result of viewing or completing the survey or participating in the research in other ways.

The study was explained to participants in all letters they received, at the beginning of the survey in the informed consent statement, in the interview informed consent statement, and in verbal form at the beginning of the interview; see Appendix A for the letter and consent forms. As such, participants should have had complete awareness of the potential risks (or lack thereof) and benefits, that their participation was and is voluntary, and of the compensation provided, before giving their informed consent for each phase of the data collection. Participants were not deceived in any way at any point during this study. The potential benefits to the participants, as users of the LibraryThing or Goodreads digital libraries, were great enough to outweigh any small possibility of harm or any risks discussed above. The identity and affiliation of the researcher was known to all prospective participants via the invitation letters and informed consent statements, and the purpose of the interview and reasoning behind it was reiterated to each interview participant at the start of their interview. There were no issues seen with the researcher (as interviewer) maintaining appropriate boundaries with participants during the interview phase of the study.

The FSU Human Subjects Committee, an institutional review board (IRB), approved this study, including the pilot test of the content analysis phase. Documentation of this approval can be found in Appendix E , section E.3 .

3.11. Conclusion

This chapter has presented the details of the method and procedures for this dissertation research study. The use of content analysis, a survey questionnaire, and semi-structured interviews in sequence within a mixed methods research design addressed the purpose of the research: to improve understanding of the organizational, cultural, institutional, collaborative, and social contexts of digital libraries. As stated in Chapter 1 and shown in Chapter 2 , these contexts have important effects on users, communities, and information behavior. There is a clear need for theoretical and practical research into the roles digital libraries play within, between, and across communities, social worlds, and information worlds. This study helps satisfy that need.

The research design is well-grounded in epistemology and theory, previous research, and previous and existing practice; Chapter 2 provides this necessary context. The study operates under the tenets of the social paradigm, social informatics, and social constructionism, and incorporates boundary object theory, the social worlds perspective, and the theory of information worlds into its theoretical framework. This design has allowed for data to be collected and analyzed, at multiple levels and using multiple methods, on the roles that LibraryThing and Goodreads, two cases of social digital libraries, play as boundary objects in translation, coherence, and convergence between existing and of emergent social and information worlds. Chapter 4 turns to presenting the findings from this data and analysis of it, with Chapter 5 providing greater synthesis and discussion of the findings, implications, and conclusions of this research.

The FSU iSchool was known at the time as the School of Library and Information Studies; for simplicity the newer name (which took effect in early 2014) will be used to refer to this entity in this dissertation. The older name is still present on the invitation letters and consent forms as approved by FSU’s Human Subjects Committee in Appendix A . ↩︎

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HOW TO WRITE CHAPTER THREE OF YOUR RESEARCH PROJECT (RESEARCH METHODOLOGY) | ResearchWap Blog

• Posted: Friday, 17 April 2020
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How To Write Chapter Three Of Your Research Project (Research Methodology)

Methodology In Research Paper

Chapter three of the research project or the research methodology is another significant part of the research project writing. In developing the chapter three of the research project, you state the purpose of research, research method you wish to adopt, the instruments to be used, where you will collect your data, types of data collection, and how you collected it.

This chapter explains the different methods to be used in the research project. Here you mention the procedures and strategies you will employ in the study such as research design, study design in research, research area (area of the study), the population of the study, etc.

You also tell the reader your research design methods, why you chose a particular method, method of analysis, how you planned to analyze your data. Your methodology should be written in a simple language such that other researchers can follow the method and arrive at the same conclusion or findings.

You can choose a survey design when you want to survey a particular location or behavior by administering instruments such as structured questionnaires, interviews, or experimental; if you intend manipulating some variables.

The purpose of chapter three (research methodology) is to give an experienced investigator enough information to replicate the study. Some supervisors do not understand this and require students to write what is in effect, a textbook.

A research design is used to structure the research and to show how all of the major parts of the research project, including the sample, measures, and methods of assignment, work together to address the central research questions in the study. The chapter three should begin with a paragraph reiterating the purpose of research.

It is very important that before choosing design methods, try and ask yourself the following questions:

Will I generate enough information that will help me to solve the research problem by adopting this method?

Method vs Methodology

I think the most appropriate in methods versus methodology is to think in terms of their inter-connectedness and relationship between both. You should not beging thinking so much about research methods without thinking of developing a research methodology.

Metodologia or methodology is the consideration of your research objectives and the most effective method  and approach to meet those objectives. That is to say that methodology in research paper is the first step in planning a research project work. 

Design Methodology: Methodological Approach                

Example of methodology in research paper, you are attempting to identify the influence of personality on a road accident, you may wish to look at different personality types, you may also look at accident records from the FRSC, you may also wish to look at the personality of drivers that are accident victims, once you adopt this method, you are already doing a survey, and that becomes your  metodologia or methodology .

Your methodology should aim to provide you with the information to allow you to come to some conclusions about the personalities that are susceptible to a road accident or those personality types that are likely to have a road accident. The following subjects may or may not be in the order required by a particular institution of higher education, but all of the subjects constitute a defensible in metodologia or methodology chapter.

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Methodology

A  methodology  is the rationale for the research approach, and the lens through which the analysis occurs. Said another way, a methodology describes the “general research strategy that outlines the way in which research is to be undertaken” The methodology should impact which method(s) for a research endeavor are selected in order to generate the compelling data.

Example Of Methodology In Research Paper :

• Phenomenology: describes the “lived experience” of a particular phenomenon
• Ethnography: explores the social world or culture, shared beliefs and behaviors
• Participatory: views the participants as active researchers
• Ethno methodology: examines how people use dialogue and body language to construct a world view
• Grounding theory*: assumes a blank slate and uses an inductive approach to develop a new theory

A  method  is simply the tool used to answer your research questions — how, in short, you will go about collecting your data.

Methods Section Of Research Paper Example :

• Contextual inquiry
• Usability study
• Diary study

If you are choosing among these, you might say “what method should I use?” and settle on one or more methods to answer your research question.

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Research Design Definition: WRITING A RESEARCH DESIGN

A qualitative study does not have variables. A scientific study has variables, which are sometimes mentioned in Chapter 1 and defined in more depth in Chapter 3. Spell out the independent and dependent, variables. An unfortunate trend in some institutions is to repeat the research questions and/or hypotheses in both Chapter 1 and Chapter 3. Sometimes an operational statement of the research hypotheses in the null form is given to set the stage for later statistical inferences. In a quantitative study, state the level of significance that will be used to accept or reject the hypotheses.

Pilot Study

In a quantitative study, a survey instrument that the researcher designed needs a pilot study to validate the effectiveness of the instrument, and the value of the questions to elicit the right information to answer the primary research questions in. In a scientific study, a pilot study may precede the main observation to correct any problems with the instrumentation or other elements in the data collection technique. Describe the pilot study as it relates to the research design, development of the instrument, data collection procedures, or characteristics of the sample.

Instruments

In a research study, the instrument used to collect data may be created by the researcher or based on an existing instrument. If the instrument is the researcher created, the process used to select the questions should be described and justified. If an existing instrument is used, the background of the instrument is described including who originated it, and what measures were used to validate it.

If a Likert scale is used, the scale should be described. If the study involves interviews, an interview protocol should be developed that will result in a consistent process of data collection across all interviews. Two types of questions are found in an interview protocol: the primary research questions, which are not asked of the participants, and the interview questions that are based on the primary research questions and are asked of the participants.

In a qualitative study, this is the section where most of the appendices are itemized, starting with letters of permission to conduct the study and letters of invitation to participate with the attached consent forms. Sample: this has to do with the number of your participants or subjects as the case may be. Analysis (how are you planning to analyze the results?)

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EFFECTIVE GUIDE AND METHODOLOGY SAMPLES

This chapter deals effectively with the research methods to be adopted in conducting the research, and it is organized under the following sub-headings:

• Research Design
• Area of Study

The population of the Study

• Sample and Sampling Techniques
• Instruments for Data Collection

The validity of the Instrument

Reliability of the Instrument

• Administration of the instruments
• Scoring the instruments

Method of Data Collection

Method of Data Analysis

Research Design:

This has to do with the structure of the research instrument to be used in collecting data. It could be in sections depending on different variables that form the construct for the entire topic of the research problems. A reliable instrument with a wrong research design will adversely affect the reliability and generalization of the research. The choice of design suitable for each research is determined by many factors among which are: kind of research, research hypothesis, the scope of the research, and the sensitive nature of the research.

Area of Study:

Research Area; this has to do with the geographical environment of the study area where the places are located, the historical background when necessary and commercial activities of that geographical area. For example, the area of the study is Ebonyi State University. At the creation of Ebonyi State in 1996, the Abakaliki campus of the then ESUT was upgraded to Ebonyi State University College by Edict no. 5 of Ebonyi State, 1998 still affiliated to ESUT with Prof. Fidelis Ogah, former ESUT Deputy Vice-Chancellor as the first Rector. In 1997, the Faculty of Applied and Natural Sciences with 8 departments was added to the fledging University, and later in 1998 when the ESUT Pre-Science Programme was relocated to Nsukka, the EBSUC Pre-Degree School commenced lectures in both Science and Arts in replacement of the former. This study focused on the students of the Business Education department in Ebonyi state university.

The population is regarded in research work as the type of people and the group of people under investigation. It has to be specific or specified. For example educational study teachers in Lagos state. Once the population is chosen, the next thing is to choose the samples from the population.

According to Uma (2007), the population is referred to as the totality of items or object which the researcher is interested in. It can also be the total number of people in an area of study. Hence, the population of this study comprised of all the students in the department of Business Education, Ebonyi State University which is made up of year one to four totaling 482. The actual number for the study was ascertained using Yaro-Yamane's formula which stated thus:

n   =        N

N is the Population

1 is constant

e is the error margin

Then, n   =         482

1+482(0.05)2

= 214.35 approximately 214

Sample and sampling technique:

It may not be possible to reach out to the number of people that form the entire population for the study to either interview, observe, or serve them with copies of the questionnaire. To be realistic, the sample should be up to 20% of the total population. Two sampling techniques are popular among all the sampling techniques. These are random and stratified random sampling techniques. (A). in Random Sampling, the writers select any specific number from a place like a school, village, etc. (B). In Stratified Random Sampling, one has to indicate a specific number from a stratum which could be a group of people according to age, qualification, etc. or different groups from different locations and different considerations attached.

Instruments for Data Collection:

This is a device or different devices used in collecting data. Example: interview, questionnaire, checklist, etc. instrument is prepared in sets or subsections, each set should be an entity thus asking questions about a particular variable to be tested after collecting data. The type of instrument used will determine the responses expected. All questions should be well set so as to determine the reliability of the instrument.

This has to do with different measures in order to determine the validity and reliability of the research instrument. For example, presenting the drafted questionnaire to the supervisor for scrutiny. Giving the questionnaire to the supervisor for useful comments and corrections would help to validate the instrument.

The test-retest reliability method is one of the simplest ways of testing the stability and reliability of an instrument over time. The test-retest approach was adopted by the researcher in establishing the reliability of the instrument. In doing this 25 copies of the questionnaire were administered on twenty-five selected respondents. After two weeks another 25 copies of the same questionnaire were re-administered on the same group. Their responses on the two occasions were correlated using Parsons Product Moment Correlation. A co-efficient of 0.81 was gotten and this was high enough to consider the instrument reliable.

Administration of the instruments:

Here, the writer states whether he or she administers the test personally or through an assistant. He also indicates the rate of return of the copies of the questionnaire administered.

Scoring the instruments:

Here items on the questionnaire or any other device used must be assigned numerical values. For example, 4 points to strongly agree, 3 points to agree, 2 points to disagree, and 1 point to strongly disagree.

Table of Analysis

The researcher collected data using the questionnaire. Copies of the questionnaire were administered by the researcher on the respondents. All the respondents were expected to give maximum co-operation, as the information on the questionnaire is all on things that revolve around their study. Hence, enough time was taken to explain how to tick or indicate their opinion on the items stated in the research questionnaire.

In this study, the mean was used to analyze the data collected. A four (4) point Likert scale was used to analyze each of the questionnaire items.

The weighing was as follows:

VGE—————- Very Great Extent (4 points)

GE—————– Great Extent (3 points)

LE—————– Little Extent (2 points)

VLE—————- Very Little Extent (1 point)

SA—————– Strongly Agree (4 points)

A——————- Agree (3 points)

D—————— Disagree (2 points)

SD—————- Strongly Disagree (1 point)

The mean of the scale will then be determined by summing up the points and dividing their number as follows with the formula:

Where; x= mean

f= frequency

X= Nominal value of the option

∑= summation

N= Total Number

Therefore, the mean of the scale is 2.5.

This means that any item statement with a mean of 2.50 and above is considered agreed by the respondents and any item statement below 2.5 is considered disagreed.

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Home » Thesis – Structure, Example and Writing Guide

Thesis – Structure, Example and Writing Guide

Table of contents.

Definition:

Thesis is a scholarly document that presents a student’s original research and findings on a particular topic or question. It is usually written as a requirement for a graduate degree program and is intended to demonstrate the student’s mastery of the subject matter and their ability to conduct independent research.

History of Thesis

The concept of a thesis can be traced back to ancient Greece, where it was used as a way for students to demonstrate their knowledge of a particular subject. However, the modern form of the thesis as a scholarly document used to earn a degree is a relatively recent development.

The origin of the modern thesis can be traced back to medieval universities in Europe. During this time, students were required to present a “disputation” in which they would defend a particular thesis in front of their peers and faculty members. These disputations served as a way to demonstrate the student’s mastery of the subject matter and were often the final requirement for earning a degree.

In the 17th century, the concept of the thesis was formalized further with the creation of the modern research university. Students were now required to complete a research project and present their findings in a written document, which would serve as the basis for their degree.

The modern thesis as we know it today has evolved over time, with different disciplines and institutions adopting their own standards and formats. However, the basic elements of a thesis – original research, a clear research question, a thorough review of the literature, and a well-argued conclusion – remain the same.

Structure of Thesis

The structure of a thesis may vary slightly depending on the specific requirements of the institution, department, or field of study, but generally, it follows a specific format.

Here’s a breakdown of the structure of a thesis:

This is the first page of the thesis that includes the title of the thesis, the name of the author, the name of the institution, the department, the date, and any other relevant information required by the institution.

This is a brief summary of the thesis that provides an overview of the research question, methodology, findings, and conclusions.

This page provides a list of all the chapters and sections in the thesis and their page numbers.

Introduction

This chapter provides an overview of the research question, the context of the research, and the purpose of the study. The introduction should also outline the methodology and the scope of the research.

Literature Review

This chapter provides a critical analysis of the relevant literature on the research topic. It should demonstrate the gap in the existing knowledge and justify the need for the research.

Methodology

This chapter provides a detailed description of the research methods used to gather and analyze data. It should explain the research design, the sampling method, data collection techniques, and data analysis procedures.

This chapter presents the findings of the research. It should include tables, graphs, and charts to illustrate the results.

This chapter interprets the results and relates them to the research question. It should explain the significance of the findings and their implications for the research topic.

This chapter summarizes the key findings and the main conclusions of the research. It should also provide recommendations for future research.

This section provides a list of all the sources cited in the thesis. The citation style may vary depending on the requirements of the institution or the field of study.

This section includes any additional material that supports the research, such as raw data, survey questionnaires, or other relevant documents.

How to write Thesis

Here are some steps to help you write a thesis:

• Choose a Topic: The first step in writing a thesis is to choose a topic that interests you and is relevant to your field of study. You should also consider the scope of the topic and the availability of resources for research.
• Develop a Research Question: Once you have chosen a topic, you need to develop a research question that you will answer in your thesis. The research question should be specific, clear, and feasible.
• Conduct a Literature Review: Before you start your research, you need to conduct a literature review to identify the existing knowledge and gaps in the field. This will help you refine your research question and develop a research methodology.
• Develop a Research Methodology: Once you have refined your research question, you need to develop a research methodology that includes the research design, data collection methods, and data analysis procedures.
• Collect and Analyze Data: After developing your research methodology, you need to collect and analyze data. This may involve conducting surveys, interviews, experiments, or analyzing existing data.
• Write the Thesis: Once you have analyzed the data, you need to write the thesis. The thesis should follow a specific structure that includes an introduction, literature review, methodology, results, discussion, conclusion, and references.
• Edit and Proofread: After completing the thesis, you need to edit and proofread it carefully. You should also have someone else review it to ensure that it is clear, concise, and free of errors.
• Submit the Thesis: Finally, you need to submit the thesis to your academic advisor or committee for review and evaluation.

Example of Thesis

Example of Thesis template for Students:

Title of Thesis

Table of Contents:

Chapter 1: Introduction

Chapter 2: Literature Review

Chapter 3: Research Methodology

Chapter 4: Results

Chapter 5: Discussion

Chapter 6: Conclusion

References:

Appendices:

Note: That’s just a basic template, but it should give you an idea of the structure and content that a typical thesis might include. Be sure to consult with your department or supervisor for any specific formatting requirements they may have. Good luck with your thesis!

Application of Thesis

Thesis is an important academic document that serves several purposes. Here are some of the applications of thesis:

• Academic Requirement: A thesis is a requirement for many academic programs, especially at the graduate level. It is an essential component of the evaluation process and demonstrates the student’s ability to conduct original research and contribute to the knowledge in their field.
• Career Advancement: A thesis can also help in career advancement. Employers often value candidates who have completed a thesis as it demonstrates their research skills, critical thinking abilities, and their dedication to their field of study.
• Publication : A thesis can serve as a basis for future publications in academic journals, books, or conference proceedings. It provides the researcher with an opportunity to present their research to a wider audience and contribute to the body of knowledge in their field.
• Personal Development: Writing a thesis is a challenging task that requires time, dedication, and perseverance. It provides the student with an opportunity to develop critical thinking, research, and writing skills that are essential for their personal and professional development.
• Impact on Society: The findings of a thesis can have an impact on society by addressing important issues, providing insights into complex problems, and contributing to the development of policies and practices.

Purpose of Thesis

The purpose of a thesis is to present original research findings in a clear and organized manner. It is a formal document that demonstrates a student’s ability to conduct independent research and contribute to the knowledge in their field of study. The primary purposes of a thesis are:

• To Contribute to Knowledge: The main purpose of a thesis is to contribute to the knowledge in a particular field of study. By conducting original research and presenting their findings, the student adds new insights and perspectives to the existing body of knowledge.
• To Demonstrate Research Skills: A thesis is an opportunity for the student to demonstrate their research skills. This includes the ability to formulate a research question, design a research methodology, collect and analyze data, and draw conclusions based on their findings.
• To Develop Critical Thinking: Writing a thesis requires critical thinking and analysis. The student must evaluate existing literature and identify gaps in the field, as well as develop and defend their own ideas.
• To Provide Evidence of Competence : A thesis provides evidence of the student’s competence in their field of study. It demonstrates their ability to apply theoretical concepts to real-world problems, and their ability to communicate their ideas effectively.
• To Facilitate Career Advancement : Completing a thesis can help the student advance their career by demonstrating their research skills and dedication to their field of study. It can also provide a basis for future publications, presentations, or research projects.

When to Write Thesis

The timing for writing a thesis depends on the specific requirements of the academic program or institution. In most cases, the opportunity to write a thesis is typically offered at the graduate level, but there may be exceptions.

Generally, students should plan to write their thesis during the final year of their graduate program. This allows sufficient time for conducting research, analyzing data, and writing the thesis. It is important to start planning the thesis early and to identify a research topic and research advisor as soon as possible.

In some cases, students may be able to write a thesis as part of an undergraduate program or as an independent research project outside of an academic program. In such cases, it is important to consult with faculty advisors or mentors to ensure that the research is appropriately designed and executed.

It is important to note that the process of writing a thesis can be time-consuming and requires a significant amount of effort and dedication. It is important to plan accordingly and to allocate sufficient time for conducting research, analyzing data, and writing the thesis.

Characteristics of Thesis

The characteristics of a thesis vary depending on the specific academic program or institution. However, some general characteristics of a thesis include:

• Originality : A thesis should present original research findings or insights. It should demonstrate the student’s ability to conduct independent research and contribute to the knowledge in their field of study.
• Clarity : A thesis should be clear and concise. It should present the research question, methodology, findings, and conclusions in a logical and organized manner. It should also be well-written, with proper grammar, spelling, and punctuation.
• Research-Based: A thesis should be based on rigorous research, which involves collecting and analyzing data from various sources. The research should be well-designed, with appropriate research methods and techniques.
• Evidence-Based : A thesis should be based on evidence, which means that all claims made in the thesis should be supported by data or literature. The evidence should be properly cited using appropriate citation styles.
• Critical Thinking: A thesis should demonstrate the student’s ability to critically analyze and evaluate information. It should present the student’s own ideas and arguments, and engage with existing literature in the field.
• Academic Style : A thesis should adhere to the conventions of academic writing. It should be well-structured, with clear headings and subheadings, and should use appropriate academic language.

Advantages of Thesis

There are several advantages to writing a thesis, including:

• Development of Research Skills: Writing a thesis requires extensive research and analytical skills. It helps to develop the student’s research skills, including the ability to formulate research questions, design and execute research methodologies, collect and analyze data, and draw conclusions based on their findings.
• Contribution to Knowledge: Writing a thesis provides an opportunity for the student to contribute to the knowledge in their field of study. By conducting original research, they can add new insights and perspectives to the existing body of knowledge.
• Preparation for Future Research: Completing a thesis prepares the student for future research projects. It provides them with the necessary skills to design and execute research methodologies, analyze data, and draw conclusions based on their findings.
• Career Advancement: Writing a thesis can help to advance the student’s career. It demonstrates their research skills and dedication to their field of study, and provides a basis for future publications, presentations, or research projects.
• Personal Growth: Completing a thesis can be a challenging and rewarding experience. It requires dedication, hard work, and perseverance. It can help the student to develop self-confidence, independence, and a sense of accomplishment.

Limitations of Thesis

There are also some limitations to writing a thesis, including:

• Time and Resources: Writing a thesis requires a significant amount of time and resources. It can be a time-consuming and expensive process, as it may involve conducting original research, analyzing data, and producing a lengthy document.
• Narrow Focus: A thesis is typically focused on a specific research question or topic, which may limit the student’s exposure to other areas within their field of study.
• Limited Audience: A thesis is usually only read by a small number of people, such as the student’s thesis advisor and committee members. This limits the potential impact of the research findings.
• Lack of Real-World Application : Some thesis topics may be highly theoretical or academic in nature, which may limit their practical application in the real world.
• Pressure and Stress : Writing a thesis can be a stressful and pressure-filled experience, as it may involve meeting strict deadlines, conducting original research, and producing a high-quality document.
• Potential for Isolation: Writing a thesis can be a solitary experience, as the student may spend a significant amount of time working independently on their research and writing.

About the author

Muhammad Hassan

Researcher, Academic Writer, Web developer

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Methods Section: Chapter Three

The methods section , or chapter three, of the dissertation or thesis is often the most challenging for graduate students.  The methodology section, chapter three should reiterate the research questions and hypotheses, present the research design, discuss the participants, the instruments to be used, the procedure, the data analysis plan , and the sample size justification.

Research Questions and Null Hypotheses

Chapter three should begin with a portion that discusses the research questions and null hypotheses.  In the research questions and null hypotheses portion of the methodology chapter, the research questions should be restated in statistical language.  For example, “Is there a difference in GPA by gender?” is a t-test type of question, whereas “Is there a relationship between GPA and income level?” is a correlation type of question.  The important thing to remember is to use the language that foreshadows the data analysis plan .  The null hypotheses are just the research questions stated in the null; for example, “There is no difference in GPA by gender,” or “There is no relationship between GPA and income level.”

Research Design

The next portion of the methods section, chapter three is focused on developing the research design.  The research design has several possibilities. First, you must decide if you are doing quantitative, qualitative, or mixed methods research. In a quantitative study, you are assessing participants’ responses on a measure.  For example, participants can endorse their level of agreement on some scale.  A qualitative design is a typically a semi-structured interview which gets transcribed, and the themes among the participants are derived.  A mixed methods project is a mixture of both a quantitative and qualitative study.

Participants

In the research methodology, the participants are typically a sample of the population you want to study.  You are probably not going to study all school children, but you may sample from the population of school children.  You need to include information about the characteristics of the population in your study (Are you sampling all males? teachers with under five years of experience?).  This represents the participants portion of your methods section, chapter three.

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Instruments

The instruments section is a critical part of the methodology section, chapter three.  The instruments section should include the name of the instruments, the scales or subscales, how the scales are computed, and the reliability and validity of the scales.  The instruments portion should have references to the researchers who created the instruments.

The procedure section of the methods chapter is simply how you are going to administer the instruments that you just described to the participants you are going to select.  You should walk the reader through the procedure in detail so that they can replicate your steps and your study.

Data Analysis Plan

The data analysis plan is just that — how you are going to analyze the data when you get the data from your participants.   It includes the statistical tests you are going to use, the statistical assumptions of these tests, and the justification for the statistical tests.

Sample Size Justification

Another important portion of your methods chapter three, is the sample size justification.  Sample size justification (or power analysis) is selecting how many participants you need to have in your study.  The sample size is based on several criteria:  the power you select (which is typically .80), the alpha level selected (which is typically .05), and the effect size (typically, a large or medium effect size is selected).  Importantly, once these criteria are selected, the sample size is going to be based on the type of statistic: an ANOVA is going to have a different sample size calculation than a multiple regression.

Dissertation Structure & Layout 101: How to structure your dissertation, thesis or research project.

By: Derek Jansen (MBA) Reviewed By: David Phair (PhD) | July 2019

So, you’ve got a decent understanding of what a dissertation is , you’ve chosen your topic and hopefully you’ve received approval for your research proposal . Awesome! Now its time to start the actual dissertation or thesis writing journey.

To craft a high-quality document, the very first thing you need to understand is dissertation structure . In this post, we’ll walk you through the generic dissertation structure and layout, step by step. We’ll start with the big picture, and then zoom into each chapter to briefly discuss the core contents. If you’re just starting out on your research journey, you should start with this post, which covers the big-picture process of how to write a dissertation or thesis .

*The Caveat *

In this post, we’ll be discussing a traditional dissertation/thesis structure and layout, which is generally used for social science research across universities, whether in the US, UK, Europe or Australia. However, some universities may have small variations on this structure (extra chapters, merged chapters, slightly different ordering, etc).

So, always check with your university if they have a prescribed structure or layout that they expect you to work with. If not, it’s safe to assume the structure we’ll discuss here is suitable. And even if they do have a prescribed structure, you’ll still get value from this post as we’ll explain the core contents of each section.  

Overview: S tructuring a dissertation or thesis

• Acknowledgements page
• Abstract (or executive summary)
• Table of contents , list of figures and tables
• Chapter 1: Introduction
• Chapter 2: Literature review
• Chapter 3: Methodology
• Chapter 4: Results
• Chapter 5: Discussion
• Chapter 6: Conclusion
• Reference list

As I mentioned, some universities will have slight variations on this structure. For example, they want an additional “personal reflection chapter”, or they might prefer the results and discussion chapter to be merged into one. Regardless, the overarching flow will always be the same, as this flow reflects the research process , which we discussed here – i.e.:

• The introduction chapter presents the core research question and aims .
• The literature review chapter assesses what the current research says about this question.
• The methodology, results and discussion chapters go about undertaking new research about this question.
• The conclusion chapter (attempts to) answer the core research question .

In other words, the dissertation structure and layout reflect the research process of asking a well-defined question(s), investigating, and then answering the question – see below.

To restate that – the structure and layout of a dissertation reflect the flow of the overall research process . This is essential to understand, as each chapter will make a lot more sense if you “get” this concept. If you’re not familiar with the research process, read this post before going further.

Right. Now that we’ve covered the big picture, let’s dive a little deeper into the details of each section and chapter. Oh and by the way, you can also grab our free dissertation/thesis template here to help speed things up.

The title page of your dissertation is the very first impression the marker will get of your work, so it pays to invest some time thinking about your title. But what makes for a good title? A strong title needs to be 3 things:

• Succinct (not overly lengthy or verbose)
• Specific (not vague or ambiguous)
• Representative of the research you’re undertaking (clearly linked to your research questions)

Typically, a good title includes mention of the following:

• The broader area of the research (i.e. the overarching topic)
• The specific focus of your research (i.e. your specific context)
• Indication of research design (e.g. quantitative , qualitative , or  mixed methods ).

For example:

A quantitative investigation [research design] into the antecedents of organisational trust [broader area] in the UK retail forex trading market [specific context/area of focus].

Again, some universities may have specific requirements regarding the format and structure of the title, so it’s worth double-checking expectations with your institution (if there’s no mention in the brief or study material).

Acknowledgements

This page provides you with an opportunity to say thank you to those who helped you along your research journey. Generally, it’s optional (and won’t count towards your marks), but it is academic best practice to include this.

So, who do you say thanks to? Well, there’s no prescribed requirements, but it’s common to mention the following people:

• Your dissertation supervisor or committee.
• Any professors, lecturers or academics that helped you understand the topic or methodologies.
• Any tutors, mentors or advisors.
• Your family and friends, especially spouse (for adult learners studying part-time).

There’s no need for lengthy rambling. Just state who you’re thankful to and for what (e.g. thank you to my supervisor, John Doe, for his endless patience and attentiveness) – be sincere. In terms of length, you should keep this to a page or less.

Abstract or executive summary

The dissertation abstract (or executive summary for some degrees) serves to provide the first-time reader (and marker or moderator) with a big-picture view of your research project. It should give them an understanding of the key insights and findings from the research, without them needing to read the rest of the report – in other words, it should be able to stand alone .

For it to stand alone, your abstract should cover the following key points (at a minimum):

• Your research questions and aims – what key question(s) did your research aim to answer?
• Your methodology – how did you go about investigating the topic and finding answers to your research question(s)?
• Your findings – following your own research, what did do you discover?
• Your conclusions – based on your findings, what conclusions did you draw? What answers did you find to your research question(s)?

So, in much the same way the dissertation structure mimics the research process, your abstract or executive summary should reflect the research process, from the initial stage of asking the original question to the final stage of answering that question.

In practical terms, it’s a good idea to write this section up last , once all your core chapters are complete. Otherwise, you’ll end up writing and rewriting this section multiple times (just wasting time). For a step by step guide on how to write a strong executive summary, check out this post .

Need a helping hand?

Table of contents

This section is straightforward. You’ll typically present your table of contents (TOC) first, followed by the two lists – figures and tables. I recommend that you use Microsoft Word’s automatic table of contents generator to generate your TOC. If you’re not familiar with this functionality, the video below explains it simply:

If you find that your table of contents is overly lengthy, consider removing one level of depth. Oftentimes, this can be done without detracting from the usefulness of the TOC.

Right, now that the “admin” sections are out of the way, its time to move on to your core chapters. These chapters are the heart of your dissertation and are where you’ll earn the marks. The first chapter is the introduction chapter – as you would expect, this is the time to introduce your research…

It’s important to understand that even though you’ve provided an overview of your research in your abstract, your introduction needs to be written as if the reader has not read that (remember, the abstract is essentially a standalone document). So, your introduction chapter needs to start from the very beginning, and should address the following questions:

• What will you be investigating (in plain-language, big picture-level)?
• Why is that worth investigating? How is it important to academia or business? How is it sufficiently original?
• What are your research aims and research question(s)? Note that the research questions can sometimes be presented at the end of the literature review (next chapter).
• What is the scope of your study? In other words, what will and won’t you cover ?
• How will you approach your research? In other words, what methodology will you adopt?
• How will you structure your dissertation? What are the core chapters and what will you do in each of them?

These are just the bare basic requirements for your intro chapter. Some universities will want additional bells and whistles in the intro chapter, so be sure to carefully read your brief or consult your research supervisor.

If done right, your introduction chapter will set a clear direction for the rest of your dissertation. Specifically, it will make it clear to the reader (and marker) exactly what you’ll be investigating, why that’s important, and how you’ll be going about the investigation. Conversely, if your introduction chapter leaves a first-time reader wondering what exactly you’ll be researching, you’ve still got some work to do.

Now that you’ve set a clear direction with your introduction chapter, the next step is the literature review . In this section, you will analyse the existing research (typically academic journal articles and high-quality industry publications), with a view to understanding the following questions:

• What does the literature currently say about the topic you’re investigating?
• Is the literature lacking or well established? Is it divided or in disagreement?
• How does your research fit into the bigger picture?
• How does your research contribute something original?
• How does the methodology of previous studies help you develop your own?

Depending on the nature of your study, you may also present a conceptual framework towards the end of your literature review, which you will then test in your actual research.

Again, some universities will want you to focus on some of these areas more than others, some will have additional or fewer requirements, and so on. Therefore, as always, its important to review your brief and/or discuss with your supervisor, so that you know exactly what’s expected of your literature review chapter.

Now that you’ve investigated the current state of knowledge in your literature review chapter and are familiar with the existing key theories, models and frameworks, its time to design your own research. Enter the methodology chapter – the most “science-ey” of the chapters…

In this chapter, you need to address two critical questions:

• Exactly HOW will you carry out your research (i.e. what is your intended research design)?
• Exactly WHY have you chosen to do things this way (i.e. how do you justify your design)?

Remember, the dissertation part of your degree is first and foremost about developing and demonstrating research skills . Therefore, the markers want to see that you know which methods to use, can clearly articulate why you’ve chosen then, and know how to deploy them effectively.

Importantly, this chapter requires detail – don’t hold back on the specifics. State exactly what you’ll be doing, with who, when, for how long, etc. Moreover, for every design choice you make, make sure you justify it.

In practice, you will likely end up coming back to this chapter once you’ve undertaken all your data collection and analysis, and revise it based on changes you made during the analysis phase. This is perfectly fine. Its natural for you to add an additional analysis technique, scrap an old one, etc based on where your data lead you. Of course, I’m talking about small changes here – not a fundamental switch from qualitative to quantitative, which will likely send your supervisor in a spin!

You’ve now collected your data and undertaken your analysis, whether qualitative, quantitative or mixed methods. In this chapter, you’ll present the raw results of your analysis . For example, in the case of a quant study, you’ll present the demographic data, descriptive statistics, inferential statistics , etc.

Typically, Chapter 4 is simply a presentation and description of the data, not a discussion of the meaning of the data. In other words, it’s descriptive, rather than analytical – the meaning is discussed in Chapter 5. However, some universities will want you to combine chapters 4 and 5, so that you both present and interpret the meaning of the data at the same time. Check with your institution what their preference is.

Now that you’ve presented the data analysis results, its time to interpret and analyse them. In other words, its time to discuss what they mean, especially in relation to your research question(s).

What you discuss here will depend largely on your chosen methodology. For example, if you’ve gone the quantitative route, you might discuss the relationships between variables . If you’ve gone the qualitative route, you might discuss key themes and the meanings thereof. It all depends on what your research design choices were.

Most importantly, you need to discuss your results in relation to your research questions and aims, as well as the existing literature. What do the results tell you about your research questions? Are they aligned with the existing research or at odds? If so, why might this be? Dig deep into your findings and explain what the findings suggest, in plain English.

The final chapter – you’ve made it! Now that you’ve discussed your interpretation of the results, its time to bring it back to the beginning with the conclusion chapter . In other words, its time to (attempt to) answer your original research question s (from way back in chapter 1). Clearly state what your conclusions are in terms of your research questions. This might feel a bit repetitive, as you would have touched on this in the previous chapter, but its important to bring the discussion full circle and explicitly state your answer(s) to the research question(s).

Next, you’ll typically discuss the implications of your findings . In other words, you’ve answered your research questions – but what does this mean for the real world (or even for academia)? What should now be done differently, given the new insight you’ve generated?

Lastly, you should discuss the limitations of your research, as well as what this means for future research in the area. No study is perfect, especially not a Masters-level. Discuss the shortcomings of your research. Perhaps your methodology was limited, perhaps your sample size was small or not representative, etc, etc. Don’t be afraid to critique your work – the markers want to see that you can identify the limitations of your work. This is a strength, not a weakness. Be brutal!

This marks the end of your core chapters – woohoo! From here on out, it’s pretty smooth sailing.

The reference list is straightforward. It should contain a list of all resources cited in your dissertation, in the required format, e.g. APA , Harvard, etc.

It’s essential that you use reference management software for your dissertation. Do NOT try handle your referencing manually – its far too error prone. On a reference list of multiple pages, you’re going to make mistake. To this end, I suggest considering either Mendeley or Zotero. Both are free and provide a very straightforward interface to ensure that your referencing is 100% on point. I’ve included a simple how-to video for the Mendeley software (my personal favourite) below:

Some universities may ask you to include a bibliography, as opposed to a reference list. These two things are not the same . A bibliography is similar to a reference list, except that it also includes resources which informed your thinking but were not directly cited in your dissertation. So, double-check your brief and make sure you use the right one.

The very last piece of the puzzle is the appendix or set of appendices. This is where you’ll include any supporting data and evidence. Importantly, supporting is the keyword here.

Your appendices should provide additional “nice to know”, depth-adding information, which is not critical to the core analysis. Appendices should not be used as a way to cut down word count (see this post which covers how to reduce word count ). In other words, don’t place content that is critical to the core analysis here, just to save word count. You will not earn marks on any content in the appendices, so don’t try to play the system!

Time to recap…

And there you have it – the traditional dissertation structure and layout, from A-Z. To recap, the core structure for a dissertation or thesis is (typically) as follows:

• Acknowledgments page

Most importantly, the core chapters should reflect the research process (asking, investigating and answering your research question). Moreover, the research question(s) should form the golden thread throughout your dissertation structure. Everything should revolve around the research questions, and as you’ve seen, they should form both the start point (i.e. introduction chapter) and the endpoint (i.e. conclusion chapter).

I hope this post has provided you with clarity about the traditional dissertation/thesis structure and layout. If you have any questions or comments, please leave a comment below, or feel free to get in touch with us. Also, be sure to check out the rest of the  Grad Coach Blog .

Psst... there’s more!

This post was based on one of our popular Research Bootcamps . If you're working on a research project, you'll definitely want to check this out ...

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36 Comments

many thanks i found it very useful

Glad to hear that, Arun. Good luck writing your dissertation.

Such clear practical logical advice. I very much needed to read this to keep me focused in stead of fretting.. Perfect now ready to start my research!

what about scientific fields like computer or engineering thesis what is the difference in the structure? thank you very much

Thanks so much this helped me a lot!

Very helpful and accessible. What I like most is how practical the advice is along with helpful tools/ links.

Thanks Ade!

Thank you so much sir.. It was really helpful..

You’re welcome!

Hi! How many words maximum should contain the abstract?

Thank you so much 😊 Find this at the right moment

You’re most welcome. Good luck with your dissertation.

best ever benefit i got on right time thank you

Many times Clarity and vision of destination of dissertation is what makes the difference between good ,average and great researchers the same way a great automobile driver is fast with clarity of address and Clear weather conditions .

I guess Great researcher = great ideas + knowledge + great and fast data collection and modeling + great writing + high clarity on all these

You have given immense clarity from start to end.

Morning. Where will I write the definitions of what I’m referring to in my report?

Thank you so much Derek, I was almost lost! Thanks a tonnnn! Have a great day!

Thanks ! so concise and valuable

This was very helpful. Clear and concise. I know exactly what to do now.

Thank you for allowing me to go through briefly. I hope to find time to continue.

Really useful to me. Thanks a thousand times

Very interesting! It will definitely set me and many more for success. highly recommended.

Thank you soo much sir, for the opportunity to express my skills

Usefull, thanks a lot. Really clear

Very nice and easy to understand. Thank you .

That was incredibly useful. Thanks Grad Coach Crew!

My stress level just dropped at least 15 points after watching this. Just starting my thesis for my grad program and I feel a lot more capable now! Thanks for such a clear and helpful video, Emma and the GradCoach team!

Do we need to mention the number of words the dissertation contains in the main document?

It depends on your university’s requirements, so it would be best to check with them 🙂

Such a helpful post to help me get started with structuring my masters dissertation, thank you!

Great video; I appreciate that helpful information

It is so necessary or avital course

This blog is very informative for my research. Thank you

Doctoral students are required to fill out the National Research Council’s Survey of Earned Doctorates

wow this is an amazing gain in my life

This is so good

How can i arrange my specific objectives in my dissertation?

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How To Write Chapter 3 Of A PhD Thesis Proposal (A Detailed Guide)

The format of a PhD thesis proposal varies from one institution to another. In most cases, however, chapter 3 of the PhD thesis is the research methodology chapter.

This article discusses the main sections of the research methodology chapter and provides tips on how best to write it.

Introduction

Research design, population and sampling, random sampling, non-random sampling, data collection methods and tools, questionnaires, focus group discussions, observation, document review, ethical considerations, data analysis, limitations of the study, final thoughts on how to write chapter 3 of a phd thesis proposal.

The first section is a brief introduction to the chapter, which highlights what the chapter is about.

This section discusses the research design that the study will use. The research design should be guided by the research objectives and research questions the student wants to answer. The research design can be: quantitative, qualitative, or mixed-methods design.

In quantitative research, the study will collect, analyse and present numerical data in the form of statistics. The statistics can be descriptive, inferential, or a mix of both.

In qualitative research, the study collects, analyses and presents data that is in the form of words, opinions, or thoughts of the respondents. Its focus is on the lived-in experiences of the respondents with regard to the problem under investigation.

In mixed-methods research, the study uses a combination of quantitative and qualitative research methods. So some of the research questions render themselves to quantitative research, while others to qualitative research.

Each of these research designs has its pros and cons.

Population of study refers to the entire list of your subjects of interest. If the population is so small, the student can opt to include all the subjects in the study. However, if the population is large, it becomes difficult – both time-wise and resource-wise – to include all the subjects in the study.

A sample is a sub-set of the population of study from which data will be collected to enable the student understand the population.

An example of population vs. sample: Suppose a study aims at investigating the effects of COVID-19 pandemic on micro and small enterprises (MSEs) in Kenya. The population of the study will be all the MSEs in Kenya, which are thousands in number, distributed across the country. It will be impossible for the student to collect data from all those MSEs and therefore a sample will be necessary. The sample size the student decides to use will depend on whether the study is quantitative, qualitative or both. For quantitative studies, a large sample size is necessary, while for qualitative study, the sample size need not be large.

Sampling is the process by which a sample is drawn from a population. There are two categories of sampling techniques, namely: random and non-random sampling. The use of either depends on your research design.

In random sampling, the sample is selected randomly and each subject in the population has an equal chance of being selected for the sample.

The advantage of random sampling is that the results from the sample can be generalised to the population, especially if the sample size is sufficiently large.

Random sampling is used primarily for quantitative studies.

In non-random sampling, the sample is selected deliberately rather than randomly. As a result, the subjects do not have an equal chance of being selected for the sample.

It is also referred to as purposive sampling, meaning that the sample being selected have a specific purpose.

Non-random sampling is used primarily for qualitative sampling.

In this section, the student is expected to discuss in detail the type of data he will collect, that is, whether primary or secondary data (or both) and how he will go about collecting the data from the sample. The methods and tools used also depend on the research design. They include:

Questionnaires are mostly used to collect quantitative data.

Questionnaires are structured in nature and include closed-ended questions.

There are four main types of closed-ended questions used in questionnaires:

• for example: how many children do you have?
• for example: does your household have a radio? 1. Yes 2. No
• for example: what is your highest level of education? 1. No education 2. Primary education 3. Secondary education 4. Tertiary level
• for example: please rate your level of satisfaction with the water services board. 1. Very dissatisfied 2. Dissatisfied 3. Neutral 4. Satisfied 5. Very satisfied

There are two forms of questionnaaire delivery: facilitated questionnaires and self-administered questionnaires.

For facilitated questionnaires, the researcher administers the questionnaire while in self-administered questionnaires, the respondent fills in the questionnaire without the presence of the researcher.

Self-administered questionnaires can be delivered by hand, or mailed via the post office or through email. Facilitated questionnaires can be done either face-to-face or through telephone. Each of these options has its pros and cons.

Interviews are oral discussions between the researcher and the respondent.

Unlike questionnaires, interviews are semi-structured. The researcher uses an interview guide to guide the discussion. The interview guide has some questions that the researcher asks the respondent. However, subsequent questions and discussions are determined by the responses given by the respondent to previous questions.

The flow of interviews will therefore vary from one respondent to another depending on their personalities and openness to responding to the questions.

Whereas interviews are held with individuals, focus group discussions (FGDs) are held with a group of respondents who are key to the problem under investigation.

The participants for an FGD should be selected carefully to represent diverse subjects of the population under investigation.

In the example of the study on the effects of COVID-19 pandemic on micro and small enterprises in Kenya, the student can create a focus group that has the following members: a female-owned enterprise, a male-owned enterprise, a youth-owned enterprise, a family-run enterprise, a non-family-run enterprise, customers of the enterprises, and an employee of the Micro and Small Enterprises Authority (MSEA). Such a focus group would have rich discussions of the views of the different players in the industry.

Observation is also a method of data collection that is commonly used. There are two types of observation: participant observation and non-participant observation.

In participant observation, the researcher immerses himself into the environment of study. In the MSEs study, for example, the researcher would choose to work in one of the enterprises for a period of time where he would observe how the business performs on a day-to-day basis.

In non-participant observation, the researcher removes himself from the environment of study and instead observes from a distance. In the MSEs study, for example, the researcher would go somewhere close to an enterprise and observe how the business performs e.g. how many clients visit the business on a day-to-day basis.

Each observation type has its own pros and cons.

During observation, the researcher should use an observation checklist that guides him on what needs to be observed and the frequency of observation.

In this data collection methods, the student obtains relevant documents to his study and reviews them in-depth. For instance, in the MSEs, the student can review the MSEs Policy of Kenya, Strategic Plan of the Micro and Small Enterprises Authority etc. Such documents are useful in informing the researcher the current state of affairs of the problem under investigation.

This section highlights the ethical considerations that would be followed during the data collection process. The ethical considerations vary from study to study and include:

Consent: the researcher should seek informed consent from the respondent before the data collection begins. For instance, when administering the questionnaire or conducting interviews, the researcher should start by informing the respondent what the study is about, how the respondent was selected, and the benefits of the study and then seek permission to continue with the study. The consent can be in written or oral form.

Compensation for participation: while participating in the study should be voluntary, some research have allowance for monetary compensation. The respondents should be informed of any plans to compensate them but after they have participated in the study, not before.

Confidentiality: the researcher should assure the respondents that their responses will be kept confidential.

Dissemination of the study findings with the respondents: there should be a plan for the student to disseminate the results of the study with the participants, for instance, through validation workshops or written publications.

Additionally, most academic institutions require their students to obtain ethical clearance for their research from the relevant authorities. Students should check if this requirement applies to them and follow the necessary procedure.

In this section, the student should discuss how the data collected will be analysed. Data analysis methods and techniques vary depending on whether the data is quantitative or qualitative.

For quantitative research, the interest of data analysis is the numbers which can be obtained through descriptive statistics and inferential statistics.

Descriptive statistics is usually the first step in analysing quantitative data. There are three categories of descriptive statistics:

• Measures of frequency: frequency table or cross-tabulation table.
• Measures of central tendency: mean, median and mode.
• Measures of variability: range, standard deviation and variance.

Inferential analysis goes a step further and looks at whether the results from the sample can be generalised to the wider population. For studies that involve interventions, inferential analysis is used to check if the intervention has any impact on the population in which it was implemented.

Some inferential analysis techniques include:

• Checking for differences between groups: t-test, analysis of variance (ANOVA) and Chi-square test.
• Checking for correlation or causation between variables: linear regression, logistic regression (logit, probit, multinomial logit/probit models etc).

The choice of data analysis technique will depend on the type of data the student has. For instance, a dependent variable that is continuous will use a different analysis technique from a dependent variable that is categorical in nature. Additionally, the choice of the data analysis technique should be guided by the research questions. The results from the analysis should be able to provide answers to the research questions posed.

For qualitative research, data analysis involves analysing the content of the interviews and focus group discussions. The content can be in different forms such as interview recordings and hand-written notes.

The recordings should be transcribed first and the notes should be organised well before analysis can take place.

The analysis of qualitative data involves coding the data, indexing the data and framing the data to identify the themes that emerge from the data.

Besides discussing the data analysis techniques, the student should discuss the softwares that will be used for analysis. There are many softwares in the market that are used for quantitative (such as SPSS and STATA) and qualitative data (such as NVivo).

The last section in the research methodology chapter discusses the potential limitations of the study and how the limitations will be mitigated. An example of study limitation is low response rate of questionnaires, which can be mitigated through triangulation.

The limitations of the study will vary from one study to another and depend on the context within which the study is conducted.

This article provided a detailed guide on how to write the research methodology chapter of a PhD thesis proposal. The research methodology chapter is informed by the research problem and research questions specified in chapter 1 of the thesis proposal. Students should therefore think through carefully their research study from the beginning because what is in the introduction chapter informs the content in the remaining chapters of the proposal and final thesis.

Related posts

How To Write Chapter 1 Of A PhD Thesis Proposal (A Practical Guide)

How To Write Chapter 2 Of A PhD Thesis Proposal (A Beginner’s Guide)

Grace Njeri-Otieno

Grace Njeri-Otieno is a Kenyan, a wife, a mom, and currently a PhD student, among many other balls she juggles. She holds a Bachelors' and Masters' degrees in Economics and has more than 7 years' experience with an INGO. She was inspired to start this site so as to share the lessons learned throughout her PhD journey with other PhD students. Her vision for this site is "to become a go-to resource center for PhD students in all their spheres of learning."

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• Dissertation Table of Contents in Word | Instructions & Examples

Dissertation Table of Contents in Word | Instructions & Examples

Published on May 15, 2022 by Tegan George . Revised on July 18, 2023.

The table of contents is where you list the chapters and major sections of your thesis, dissertation , or research paper, alongside their page numbers. A clear and well-formatted table of contents is essential, as it demonstrates to your reader that a quality paper will follow.

The table of contents (TOC) should be placed between the abstract and the introduction . The maximum length should be two pages. Depending on the nature of your thesis , paper, or dissertation topic , there are a few formatting options you can choose from.

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Table of contents

What to include in your table of contents, what not to include in your table of contents, creating a table of contents in microsoft word, table of contents examples, updating a table of contents in microsoft word, other lists in your thesis, dissertation, or research paper, other interesting articles, frequently asked questions about the table of contents.

Depending on the length of your document, you can choose between a single-level, subdivided, or multi-level table of contents.

• A single-level table of contents only includes “level 1” headings , or chapters. This is the simplest option, but it may be too broad for a long document like a dissertation.
• A subdivided table of contents includes chapters as well as “level 2” headings, or sections. These show your reader what each chapter contains.
• A multi-level table of contents also further divides sections into “level 3” headings. This option can get messy quickly, so proceed with caution. Remember your table of contents should not be longer than 2 pages. A multi-level table is often a good choice for a shorter document like a research paper .

Examples of level 1 headings are Introduction, Literature Review , Methodology , and Bibliography. Subsections of each of these would be level 2 headings, further describing the contents of each chapter or large section. Any further subsections would be level 3.

In these introductory sections, less is often more. As you decide which sections to include, narrow it down to only the most essential.

Including appendices and tables

You should include all appendices in your table of contents. Whether or not you include tables and figures depends largely on how many there are in your document.

If there are more than three figures and tables, you might consider listing them on a separate page. Otherwise, you can include each one in the table of contents.

• Theses and dissertations often have a separate list of figures and tables.
• Research papers generally don’t have a separate list of figures and tables.

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All level 1 and level 2 headings should be included in your table of contents, with level 3 headings used very sparingly.

The following things should never be included in a table of contents:

• Your acknowledgements page
• Your abstract
• The table of contents itself

The acknowledgements and abstract always precede the table of contents, so there’s no need to include them. This goes for any sections that precede the table of contents.

To automatically insert a table of contents in Microsoft Word, be sure to first apply the correct heading styles throughout the document, as shown below.

• Choose which headings are heading 1 and which are heading 2 (or 3)!
• For example, if all level 1 headings should be Times New Roman, 12-point font, and bold, add this formatting to the first level 1 heading.
• Highlight the level 1 heading.
• Right-click the style that says “Heading 1.”
• Select “Update Heading 1 to Match Selection.”
• Allocate the formatting for each heading throughout your document by highlighting the heading in question and clicking the style you wish to apply.

Once that’s all set, follow these steps:

• Add a title to your table of contents. Be sure to check if your citation style or university has guidelines for this.
• Place your cursor where you would like your table of contents to go.
• In the “References” section at the top, locate the Table of Contents group.
• Here, you can select which levels of headings you would like to include. You can also make manual adjustments to each level by clicking the Modify button.
• When you are ready to insert the table of contents, click “OK” and it will be automatically generated, as shown below.

The key features of a table of contents are:

• Clear headings and subheadings
• Corresponding page numbers

Check with your educational institution to see if they have any specific formatting or design requirements.

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Write yourself a reminder to update your table of contents as one of your final tasks before submitting your dissertation or paper. It’s normal for your text to shift a bit as you input your final edits, and it’s crucial that your page numbers correspond correctly.

It’s easy to update your page numbers automatically in Microsoft Word. Simply right-click the table of contents and select “Update Field.” You can choose either to update page numbers only or to update all information in your table of contents.

In addition to a table of contents, you might also want to include a list of figures and tables, a list of abbreviations, and a glossary in your thesis or dissertation. You can use the following guides to do so:

• List of figures and tables
• List of abbreviations

It is less common to include these lists in a research paper.

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All level 1 and 2 headings should be included in your table of contents . That means the titles of your chapters and the main sections within them.

The contents should also include all appendices and the lists of tables and figures, if applicable, as well as your reference list .

Do not include the acknowledgements or abstract in the table of contents.

To automatically insert a table of contents in Microsoft Word, follow these steps:

• Apply heading styles throughout the document.
• In the references section in the ribbon, locate the Table of Contents group.
• Click the arrow next to the Table of Contents icon and select Custom Table of Contents.
• Select which levels of headings you would like to include in the table of contents.

Make sure to update your table of contents if you move text or change headings. To update, simply right click and select Update Field.

The table of contents in a thesis or dissertation always goes between your abstract and your introduction .

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How to structure a thesis

A typical thesis structure

1. abstract, 2. introduction, 3. literature review, 6. discussion, 7. conclusion, 8. reference list, frequently asked questions about structuring a thesis, related articles.

Starting a thesis can be daunting. There are so many questions in the beginning:

• How do you actually start your thesis?
• How do you structure it?
• What information should the individual chapters contain?

Each educational program has different demands on your thesis structure, which is why asking directly for the requirements of your program should be a first step. However, there is not much flexibility when it comes to structuring your thesis.

Abstract : a brief overview of your entire thesis.

Literature review : an evaluation of previous research on your topic that includes a discussion of gaps in the research and how your work may fill them.

Methods : outlines the methodology that you are using in your research.

Thesis : a large paper, or multi-chapter work, based on a topic relating to your field of study.

The abstract is the overview of your thesis and generally very short. This section should highlight the main contents of your thesis “at a glance” so that someone who is curious about your work can get the gist quickly. Take a look at our guide on how to write an abstract for more info.

Tip: Consider writing your abstract last, after you’ve written everything else.

The introduction to your thesis gives an overview of its basics or main points. It should answer the following questions:

• Why is the topic being studied?
• How is the topic being studied?
• What is being studied?

In answering the first question, you should know what your personal interest in this topic is and why it is relevant. Why does it matter?

To answer the "how", you should briefly explain how you are going to reach your research goal. Some prefer to answer that question in the methods chapter, but you can give a quick overview here.

And finally, you should explain "what" you are studying. You can also give background information here.

You should rewrite the introduction one last time when the writing is done to make sure it connects with your conclusion. Learn more about how to write a good thesis introduction in our thesis introduction guide .

A literature review is often part of the introduction, but it can be a separate section. It is an evaluation of previous research on the topic showing that there are gaps that your research will attempt to fill. A few tips for your literature review:

• Use a wide array of sources
• Show both sides of the coin
• Make sure to cover the classics in your field
• Present everything in a clear and structured manner

For more insights on lit reviews, take a look at our guide on how to write a literature review .

The methodology chapter outlines which methods you choose to gather data, how the data is analyzed and justifies why you chose that methodology . It shows how your choice of design and research methods is suited to answering your research question.

Make sure to also explain what the pitfalls of your approach are and how you have tried to mitigate them. Discussing where your study might come up short can give you more credibility, since it shows the reader that you are aware of its limitations.

Tip: Use graphs and tables, where appropriate, to visualize your results.

The results chapter outlines what you found out in relation to your research questions or hypotheses. It generally contains the facts of your research and does not include a lot of analysis, because that happens mostly in the discussion chapter.

Clearly visualize your results, using tables and graphs, especially when summarizing, and be consistent in your way of reporting. This means sticking to one format to help the reader evaluate and compare the data.

The discussion chapter includes your own analysis and interpretation of the data you gathered , comments on your results and explains what they mean. This is your opportunity to show that you have understood your findings and their significance.

Point out the limitations of your study, provide explanations for unexpected results, and note any questions that remain unanswered.

This is probably your most important chapter. This is where you highlight that your research objectives have been achieved. You can also reiterate any limitations to your study and make suggestions for future research.

Remember to check if you have really answered all your research questions and hypotheses in this chapter. Your thesis should be tied up nicely in the conclusion and show clearly what you did, what results you got, and what you learned. Discover how to write a good conclusion in our thesis conclusion guide .

At the end of your thesis, you’ll have to compile a list of references for everything you’ve cited above. Ideally, you should keep track of everything from the beginning. Otherwise, this could be a mammoth and pretty laborious task to do.

Consider using a reference manager like Paperpile to format and organize your citations. Paperpile allows you to organize and save your citations for later use and cite them in thousands of citation styles directly in Google Docs, Microsoft Word, or LaTeX:

🔲 Introduction

🔲 Literature review

🔲 Discussion

🔲 Conclusion

🔲 Reference list

The basic elements of a thesis are: Abstract, Introduction, Literature Review, Methods, Results, Discussion, Conclusion, and Reference List.

It's recommended to start a thesis by writing the literature review first. This way you learn more about the sources, before jumping to the discussion or any other element.

It's recommended to write the abstract of a thesis last, once everything else is done. This way you will be able to provide a complete overview of your work.

Usually, the discussion is the longest part of a thesis. In this part you are supposed to point out the limitations of your study, provide explanations for unexpected results, and note any questions that remain unanswered.

The order of the basic elements of a thesis are: 1. Abstract, 2. Introduction, 3. Literature Review, 4. Methods, 5. Results, 6. Discussion, 7. Conclusion, and 8. Reference List.