what recommendation do you have for future research

The Ultimate Guide to Crafting Impactful Recommendations in Research

Are you ready to take your research to the next level? Crafting impactful recommendations is the key to unlocking the full potential of your study. By providing clear, actionable suggestions based on your findings, you can bridge the gap between research and real-world application.

In this ultimate guide, we'll show you how to write recommendations that make a difference in your research report or paper.

You'll learn how to craft specific, actionable recommendations that connect seamlessly with your research findings. Whether you're a student, writer, teacher, or journalist, this guide will help you master the art of writing recommendations in research. Let's get started and make your research count!

Understanding the Purpose of Recommendations

Recommendations in research serve as a vital bridge between your findings and their real-world applications. They provide specific, action-oriented suggestions to guide future studies and decision-making processes. Let's dive into the key purposes of crafting effective recommendations:

Guiding Future Research

Research recommendations play a crucial role in steering scholars and researchers towards promising avenues of exploration. By highlighting gaps in current knowledge and proposing new research questions, recommendations help advance the field and drive innovation.

Influencing Decision-Making

Well-crafted recommendations have the power to shape policies, programs, and strategies across various domains, such as:

• Policy-making
• Product development
• Marketing strategies
• Medical practice

By providing clear, evidence-based suggestions, recommendations facilitate informed decision-making and improve outcomes.

Connecting Research to Practice

Recommendations act as a conduit for transferring knowledge from researchers to practitioners, policymakers, and stakeholders. They bridge the gap between academic findings and their practical applications, ensuring that research insights are effectively translated into real-world solutions.

Enhancing Research Impact

By crafting impactful recommendations, you can amplify the reach and influence of your research, attracting attention from peers, funding agencies, and decision-makers.

Addressing Limitations

Recommendations provide an opportunity to acknowledge and address the limitations of your study. By suggesting concrete and actionable possibilities for future research, you demonstrate a thorough understanding of your work's scope and potential areas for improvement.

Identifying Areas for Future Research

Discovering research gaps is a crucial step in crafting impactful recommendations. It involves reviewing existing studies and identifying unanswered questions or problems that warrant further investigation. Here are some strategies to help you identify areas for future research:

Explore Research Limitations

Take a close look at the limitations section of relevant studies. These limitations often provide valuable insights into potential areas for future research. Consider how addressing these limitations could enhance our understanding of the topic at hand.

Critically Analyze Discussion and Future Research Sections

When reading articles, pay special attention to the discussion and future research sections. These sections often highlight gaps in the current knowledge base and propose avenues for further exploration. Take note of any recurring themes or unanswered questions that emerge across multiple studies.

Utilize Targeted Search Terms

To streamline your search for research gaps, use targeted search terms such as "literature gap" or "future research" in combination with your subject keywords. This approach can help you quickly identify articles that explicitly discuss areas for future investigation.

Seek Guidance from Experts

Don't hesitate to reach out to your research advisor or other experts in your field. Their wealth of knowledge and experience can provide valuable insights into potential research gaps and emerging trends.

By employing these strategies, you'll be well-equipped to identify research gaps and craft recommendations that push the boundaries of current knowledge. Remember, the goal is to refine your research questions and focus your efforts on areas where more understanding is needed.

Structuring Your Recommendations

When it comes to structuring your recommendations, it's essential to keep them concise, organized, and tailored to your audience. Here are some key tips to help you craft impactful recommendations:

Prioritize and Organize

• Limit your recommendations to the most relevant and targeted suggestions for your peers or colleagues in the field.
• Place your recommendations at the end of the report, as they are often top of mind for readers.
• Write your recommendations in order of priority, with the most important ones for decision-makers coming first.

Use a Clear and Actionable Format

• Write recommendations in a clear, concise manner using actionable words derived from the data analyzed in your research.
• Use bullet points instead of long paragraphs for clarity and readability.
• Ensure that your recommendations are specific, measurable, attainable, relevant, and timely (SMART).

Connect Recommendations to Research

By following this simple formula, you can ensure that your recommendations are directly connected to your research and supported by a clear rationale.

Tailor to Your Audience

• Consider the needs and interests of your target audience when crafting your recommendations.
• Explain how your recommendations can solve the issues explored in your research.
• Acknowledge any limitations or constraints of your study that may impact the implementation of your recommendations.

Avoid Common Pitfalls

• Don't undermine your own work by suggesting incomplete or unnecessary recommendations.
• Avoid using recommendations as a place for self-criticism or introducing new information not covered in your research.
• Ensure that your recommendations are achievable and comprehensive, offering practical solutions for the issues considered in your paper.

By structuring your recommendations effectively, you can enhance the reliability and validity of your research findings, provide valuable strategies and suggestions for future research, and deliver impactful solutions to real-world problems.

Crafting Actionable and Specific Recommendations

Crafting actionable and specific recommendations is the key to ensuring your research findings have a real-world impact. Here are some essential tips to keep in mind:

Embrace Flexibility and Feasibility

Your recommendations should be open to discussion and new information, rather than being set in stone. Consider the following:

• Be realistic and considerate of your team's capabilities when making recommendations.
• Prioritize recommendations based on impact and reach, but be prepared to adjust based on team effort levels.
• Focus on solutions that require the fewest changes first, adopting an MVP (Minimum Viable Product) approach.

Provide Detailed and Justified Recommendations

To avoid vagueness and misinterpretation, ensure your recommendations are:

• Detailed, including photos, videos, or screenshots whenever possible.
• Justified based on research findings, providing alternatives when findings don't align with expectations or business goals.

Use this formula when writing recommendations:

Observed problem/pain point/unmet need + consequence + potential solution

Adopt a Solution-Oriented Approach

Foster Collaboration and Participation

• Promote staff education on current research and create strategies to encourage adoption of promising clinical protocols.
• Include representatives from the treatment community in the development of the research initiative and the review of proposals.
• Require active, early, and permanent participation of treatment staff in the development, implementation, and interpretation of the study.

Tailor Recommendations to the Opportunity

When writing recommendations for a specific opportunity or program:

• Highlight the strengths and qualifications of the researcher.
• Provide specific examples of their work and accomplishments.
• Explain how their research has contributed to the field.
• Emphasize the researcher's potential for future success and their unique contributions.

By following these guidelines, you'll craft actionable and specific recommendations that drive meaningful change and showcase the value of your research.

Connecting Recommendations with Research Findings

Connecting your recommendations with research findings is crucial for ensuring the credibility and impact of your suggestions. Here's how you can seamlessly link your recommendations to the evidence uncovered in your study:

Grounding Recommendations in Research

Your recommendations should be firmly rooted in the data and insights gathered during your research process. Avoid including measures or suggestions that were not discussed or supported by your study findings. This approach ensures that your recommendations are evidence-based and directly relevant to the research at hand.

Highlighting the Significance of Collaboration

Research collaborations offer a wealth of benefits that can enhance an agency's competitive position. Consider the following factors when discussing the importance of collaboration in your recommendations:

• Organizational Development: Participation in research collaborations depends on an agency's stage of development, compatibility with its mission and culture, and financial stability.
• Trust-Building: Long-term collaboration success often hinges on a history of increasing involvement and trust between partners.
• Infrastructure: A permanent infrastructure that facilitates long-term development is key to successful collaborative programs.

Emphasizing Commitment and Participation

Fostering Quality Improvement and Organizational Learning

In your recommendations, highlight the importance of enhancing quality improvement strategies and fostering organizational learning. Show sensitivity to the needs and constraints of community-based programs, as this understanding is crucial for effective collaboration and implementation.

Addressing Limitations and Implications

If not already addressed in the discussion section, your recommendations should mention the limitations of the study and their implications. Examples of limitations include:

• Sample size or composition
• Participant attrition
• Study duration

By acknowledging these limitations, you demonstrate a comprehensive understanding of your research and its potential impact.

By connecting your recommendations with research findings, you provide a solid foundation for your suggestions, emphasize the significance of collaboration, and showcase the potential for future research and practical applications.

Crafting impactful recommendations is a vital skill for any researcher looking to bridge the gap between their findings and real-world applications. By understanding the purpose of recommendations, identifying areas for future research, structuring your suggestions effectively, and connecting them to your research findings, you can unlock the full potential of your study. Remember to prioritize actionable, specific, and evidence-based recommendations that foster collaboration and drive meaningful change.

As you embark on your research journey, embrace the power of well-crafted recommendations to amplify the impact of your work. By following the guidelines outlined in this ultimate guide, you'll be well-equipped to write recommendations that resonate with your audience, inspire further investigation, and contribute to the advancement of your field. So go forth, make your research count, and let your recommendations be the catalyst for positive change.

Q: What are the steps to formulating recommendations in research? A: To formulate recommendations in research, you should first gain a thorough understanding of the research question. Review the existing literature to inform your recommendations and consider the research methods that were used. Identify which data collection techniques were employed and propose suitable data analysis methods. It's also essential to consider any limitations and ethical considerations of your research. Justify your recommendations clearly and finally, provide a summary of your recommendations.

Q: Why are recommendations significant in research studies? A: Recommendations play a crucial role in research as they form a key part of the analysis phase. They provide specific suggestions for interventions or strategies that address the problems and limitations discovered during the study. Recommendations are a direct response to the main findings derived from data collection and analysis, and they can guide future actions or research.

Q: Can you outline the seven steps involved in writing a research paper? A: Certainly. The seven steps to writing an excellent research paper include:

• Allowing yourself sufficient time to complete the paper.
• Defining the scope of your essay and crafting a clear thesis statement.
• Conducting a thorough yet focused search for relevant research materials.
• Reading the research materials carefully and taking detailed notes.
• Writing your paper based on the information you've gathered and analyzed.
• Editing your paper to ensure clarity, coherence, and correctness.
• Submitting your paper following the guidelines provided.

Q: What tips can help make a research paper more effective? A: To enhance the effectiveness of a research paper, plan for the extensive process ahead and understand your audience. Decide on the structure your research writing will take and describe your methodology clearly. Write in a straightforward and clear manner, avoiding the use of clichés or overly complex language.

Sign up for more like this.

• Cookies & Privacy
• GETTING STARTED
• Introduction
• FUNDAMENTALS
• Acknowledgements
• Research questions & hypotheses
• Concepts, constructs & variables
• Research limitations
• Getting started
• Sampling Strategy
• Research Quality
• Research Ethics
• Data Analysis

FUTURE RESEARCH

Types of future research suggestion.

The Future Research section of your dissertation is often combined with the Research Limitations section of your final, Conclusions chapter. This is because your future research suggestions generally arise out of the research limitations you have identified in your own dissertation. In this article, we discuss six types of future research suggestion. These include: (1) building on a particular finding in your research; (2) addressing a flaw in your research; examining (or testing) a theory (framework or model) either (3) for the first time or (4) in a new context, location and/or culture; (5) re-evaluating and (6) expanding a theory (framework or model). The goal of the article is to help you think about the potential types of future research suggestion that you may want to include in your dissertation.

Before we discuss each of these types of future research suggestion, we should explain why we use the word examining and then put or testing in brackets. This is simply because the word examining may be considered more appropriate when students use a qualitative research design; whereas the word testing fits better with dissertations drawing on a quantitative research design. We also put the words framework or model in brackets after the word theory . We do this because a theory , framework and model are not the same things. In the sections that follow, we discuss six types of future research suggestion.

Addressing research limitations in your dissertation

Building on a particular finding or aspect of your research, examining a conceptual framework (or testing a theoretical model) for the first time, examining a conceptual framework (or testing a theoretical model) in a new context, location and/or culture.

• Expanding a conceptual framework (or testing a theoretical model)

Re-evaluating a conceptual framework (or theoretical model)

In the Research Limitations section of your Conclusions chapter, you will have inevitably detailed the potential flaws (i.e., research limitations) of your dissertation. These may include:

An inability to answer your research questions

Theoretical and conceptual problems

Limitations of your research strategy

Problems of research quality

Identifying what these research limitations were and proposing future research suggestions that address them is arguably the easiest and quickest ways to complete the Future Research section of your Conclusions chapter.

Often, the findings from your dissertation research will highlight a number of new avenues that could be explored in future studies. These can be grouped into two categories:

Your dissertation will inevitably lead to findings that you did not anticipate from the start. These are useful when making future research suggestions because they can lead to entirely new avenues to explore in future studies. If this was the case, it is worth (a) briefly describing what these unanticipated findings were and (b) suggesting a research strategy that could be used to explore such findings in future.

Sometimes, dissertations manage to address all aspects of the research questions that were set. However, this is seldom the case. Typically, there will be aspects of your research questions that could not be answered. This is not necessarily a flaw in your research strategy, but may simply reflect that fact that the findings did not provide all the answers you hoped for. If this was the case, it is worth (a) briefly describing what aspects of your research questions were not answered and (b) suggesting a research strategy that could be used to explore such aspects in future.

You may want to recommend that future research examines the conceptual framework (or tests the theoretical model) that you developed. This is based on the assumption that the primary goal of your dissertation was to set out a conceptual framework (or build a theoretical model). It is also based on the assumption that whilst such a conceptual framework (or theoretical model) was presented, your dissertation did not attempt to examine (or test) it in the field . The focus of your dissertations was most likely a review of the literature rather than something that involved you conducting primary research.

Whilst it is quite rare for dissertations at the undergraduate and master's level to be primarily theoretical in nature like this, it is not unknown. If this was the case, you should think about how the conceptual framework (or theoretical model) that you have presented could be best examined (or tested) in the field . In understanding the how , you should think about two factors in particular:

What is the context, location and/or culture that would best lend itself to my conceptual framework (or theoretical model) if it were to be examined (or tested) in the field?

What research strategy is most appropriate to examine my conceptual framework (or test my theoretical model)?

If the future research suggestion that you want to make is based on examining your conceptual framework (or testing your theoretical model) in the field , you need to suggest the best scenario for doing so.

More often than not, you will not only have set out a conceptual framework (or theoretical model), as described in the previous section, but you will also have examined (or tested) it in the field . When you do this, focus is typically placed on a specific context, location and/or culture.

If this is the case, the obvious future research suggestion that you could propose would be to examine your conceptual framework (or test the theoretical model) in a new context, location and/or culture. For example, perhaps you focused on consumers (rather than businesses), or Canada (rather than the United Kingdom), or a more individualistic culture like the United States (rather than a more collectivist culture like China).

When you propose a new context, location and/or culture as your future research suggestion, make sure you justify the choice that you make. For example, there may be little value in future studies looking at different cultures if culture is not an important component underlying your conceptual framework (or theoretical model). If you are not sure whether a new context, location or culture is more appropriate, or what new context, location or culture you should select, a review the literature will often help clarify where you focus should be.

Expanding a conceptual framework (or theoretical model)

Assuming that you have set out a conceptual framework (or theoretical model) and examined (or tested) it in the field , another series of future research suggestions comes out of expanding that conceptual framework (or theoretical model).

We talk about a series of future research suggestions because there are so many ways that you can expand on your conceptual framework (or theoretical model). For example, you can do this by:

Examining constructs (or variables) that were included in your conceptual framework (or theoretical model) but were not focused.

Looking at a particular relationship aspect of your conceptual framework (or theoretical model) further.

Adding new constructs (or variables) to the conceptual framework (or theoretical model) you set out (if justified by the literature).

It would be possible to include one or a number of these as future research suggestions. Again, make sure that any suggestions you make have are justified , either by your findings or the literature.

With the dissertation process at the undergraduate and master's level lasting between 3 and 9 months, a lot a can happen in between. For example, a specific event (e.g., 9/11, the economic crisis) or some new theory or evidence that undermines (or questions) the literature (theory) and assumptions underpinning your conceptual framework (or theoretical model). Clearly, there is little you can do about this. However, if this happens, reflecting on it and re-evaluating your conceptual framework (or theoretical model), as well as your findings, is an obvious source of future research suggestions.

Research Recommendations – Guiding policy-makers for evidence-based decision making

Research recommendations play a crucial role in guiding scholars and researchers toward fruitful avenues of exploration. In an era marked by rapid technological advancements and an ever-expanding knowledge base, refining the process of generating research recommendations becomes imperative.

But, what is a research recommendation?

Research recommendations are suggestions or advice provided to researchers to guide their study on a specific topic . They are typically given by experts in the field. Research recommendations are more action-oriented and provide specific guidance for decision-makers, unlike implications that are broader and focus on the broader significance and consequences of the research findings. However, both are crucial components of a research study.

Difference Between Research Recommendations and Implication

Although research recommendations and implications are distinct components of a research study, they are closely related. The differences between them are as follows:

Types of Research Recommendations

Recommendations in research can take various forms, which are as follows:

These recommendations aim to assist researchers in navigating the vast landscape of academic knowledge.

Let us dive deeper to know about its key components and the steps to write an impactful research recommendation.

Key Components of Research Recommendations

The key components of research recommendations include defining the research question or objective, specifying research methods, outlining data collection and analysis processes, presenting results and conclusions, addressing limitations, and suggesting areas for future research. Here are some characteristics of research recommendations:

Research recommendations offer various advantages and play a crucial role in ensuring that research findings contribute to positive outcomes in various fields. However, they also have few limitations which highlights the significance of a well-crafted research recommendation in offering the promised advantages.

The importance of research recommendations ranges in various fields, influencing policy-making, program development, product development, marketing strategies, medical practice, and scientific research. Their purpose is to transfer knowledge from researchers to practitioners, policymakers, or stakeholders, facilitating informed decision-making and improving outcomes in different domains.

How to Write Research Recommendations?

Research recommendations can be generated through various means, including algorithmic approaches, expert opinions, or collaborative filtering techniques. Here is a step-wise guide to build your understanding on the development of research recommendations.

1. Understand the Research Question:

Understand the research question and objectives before writing recommendations. Also, ensure that your recommendations are relevant and directly address the goals of the study.

2. Review Existing Literature:

Familiarize yourself with relevant existing literature to help you identify gaps , and offer informed recommendations that contribute to the existing body of research.

3. Consider Research Methods:

Evaluate the appropriateness of different research methods in addressing the research question. Also, consider the nature of the data, the study design, and the specific objectives.

4. Identify Data Collection Techniques:

Gather dataset from diverse authentic sources. Include information such as keywords, abstracts, authors, publication dates, and citation metrics to provide a rich foundation for analysis.

5. Propose Data Analysis Methods:

Suggest appropriate data analysis methods based on the type of data collected. Consider whether statistical analysis, qualitative analysis, or a mixed-methods approach is most suitable.

6. Consider Limitations and Ethical Considerations:

Acknowledge any limitations and potential ethical considerations of the study. Furthermore, address these limitations or mitigate ethical concerns to ensure responsible research.

7. Justify Recommendations:

Explain how your recommendation contributes to addressing the research question or objective. Provide a strong rationale to help researchers understand the importance of following your suggestions.

8. Summarize Recommendations:

Provide a concise summary at the end of the report to emphasize how following these recommendations will contribute to the overall success of the research project.

By following these steps, you can create research recommendations that are actionable and contribute meaningfully to the success of the research project.

Download now to unlock some tips to improve your journey of writing research recommendations.

Example of a Research Recommendation

Here is an example of a research recommendation based on a hypothetical research to improve your understanding.

Research Recommendation: Enhancing Student Learning through Integrated Learning Platforms

Background:

The research study investigated the impact of an integrated learning platform on student learning outcomes in high school mathematics classes. The findings revealed a statistically significant improvement in student performance and engagement when compared to traditional teaching methods.

Recommendation:

In light of the research findings, it is recommended that educational institutions consider adopting and integrating the identified learning platform into their mathematics curriculum. The following specific recommendations are provided:

• Implementation of the Integrated Learning Platform:

Schools are encouraged to adopt the integrated learning platform in mathematics classrooms, ensuring proper training for teachers on its effective utilization.

• Professional Development for Educators:

Develop and implement professional programs to train educators in the effective use of the integrated learning platform to address any challenges teachers may face during the transition.

• Monitoring and Evaluation:

Establish a monitoring and evaluation system to track the impact of the integrated learning platform on student performance over time.

• Resource Allocation:

Allocate sufficient resources, both financial and technical, to support the widespread implementation of the integrated learning platform.

By implementing these recommendations, educational institutions can harness the potential of the integrated learning platform and enhance student learning experiences and academic achievements in mathematics.

This example covers the components of a research recommendation, providing specific actions based on the research findings, identifying the target audience, and outlining practical steps for implementation.

Using AI in Research Recommendation Writing

Enhancing research recommendations is an ongoing endeavor that requires the integration of cutting-edge technologies, collaborative efforts, and ethical considerations. By embracing data-driven approaches and leveraging advanced technologies, the research community can create more effective and personalized recommendation systems. However, it is accompanied by several limitations. Therefore, it is essential to approach the use of AI in research with a critical mindset, and complement its capabilities with human expertise and judgment.

Here are some limitations of integrating AI in writing research recommendation and some ways on how to counter them.

1. Data Bias

AI systems rely heavily on data for training. If the training data is biased or incomplete, the AI model may produce biased results or recommendations.

How to tackle: Audit regularly the model’s performance to identify any discrepancies and adjust the training data and algorithms accordingly.

2. Lack of Understanding of Context:

AI models may struggle to understand the nuanced context of a particular research problem. They may misinterpret information, leading to inaccurate recommendations.

How to tackle: Use AI to characterize research articles and topics. Employ them to extract features like keywords, authorship patterns and content-based details.

3. Ethical Considerations:

AI models might stereotype certain concepts or generate recommendations that could have negative consequences for certain individuals or groups.

How to tackle: Incorporate user feedback mechanisms to reduce redundancies. Establish an ethics review process for AI models in research recommendation writing.

4. Lack of Creativity and Intuition:

AI may struggle with tasks that require a deep understanding of the underlying principles or the ability to think outside the box.

How to tackle: Hybrid approaches can be employed by integrating AI in data analysis and identifying patterns for accelerating the data interpretation process.

5. Interpretability:

Many AI models, especially complex deep learning models, lack transparency on how the model arrived at a particular recommendation.

How to tackle: Implement models like decision trees or linear models. Provide clear explanation of the model architecture, training process, and decision-making criteria.

6. Dynamic Nature of Research:

Research fields are dynamic, and new information is constantly emerging. AI models may struggle to keep up with the rapidly changing landscape and may not be able to adapt to new developments.

How to tackle: Establish a feedback loop for continuous improvement. Regularly update the recommendation system based on user feedback and emerging research trends.

The integration of AI in research recommendation writing holds great promise for advancing knowledge and streamlining the research process. However, navigating these concerns is pivotal in ensuring the responsible deployment of these technologies. Researchers need to understand the use of responsible use of AI in research and must be aware of the ethical considerations.

Exploring research recommendations plays a critical role in shaping the trajectory of scientific inquiry. It serves as a compass, guiding researchers toward more robust methodologies, collaborative endeavors, and innovative approaches. Embracing these suggestions not only enhances the quality of individual studies but also contributes to the collective advancement of human understanding.

Frequently Asked Questions

The purpose of recommendations in research is to provide practical and actionable suggestions based on the study's findings, guiding future actions, policies, or interventions in a specific field or context. Recommendations bridges the gap between research outcomes and their real-world application.

To make a research recommendation, analyze your findings, identify key insights, and propose specific, evidence-based actions. Include the relevance of the recommendations to the study's objectives and provide practical steps for implementation.

Begin a recommendation by succinctly summarizing the key findings of the research. Clearly state the purpose of the recommendation and its intended impact. Use a direct and actionable language to convey the suggested course of action.

Rate this article Cancel Reply

Your email address will not be published.

Enago Academy's Most Popular Articles

• Career Corner
• Reporting Research

How to Create a Poster That Stands Out: Challenges and Tips for a smooth poster presentation

It was the conference season. Judy was excited to present her first poster! She had…

• Diversity and Inclusion
• Industry News

6 Reasons Why There is a Decline in Higher Education Enrollment: Action plan to overcome this crisis

Over the past decade, colleges and universities across the globe have witnessed a concerning trend…

Academic Essay Writing Made Simple: 4 types and tips

The pen is mightier than the sword, they say, and nowhere is this more evident…

Ensuring Academic Integrity and Transparency in Academic Research: A comprehensive checklist for researchers

Academic integrity is the foundation upon which the credibility and value of scientific findings are…

• Publishing News

Unified AI Guidelines Crucial as Academic Writing Embraces Generative Tools

As generative artificial intelligence (AI) tools like ChatGPT are advancing at an accelerating pace, their…

How to Create a Poster That Stands Out: Challenges and Tips for a smooth poster…

How to Effectively Cite a PDF (APA, MLA, AMA, and Chicago Style)

How to Optimize Your Research Process: A step-by-step guide

Sign-up to read more

Subscribe for free to get unrestricted access to all our resources on research writing and academic publishing including:

• 2000+ blog articles
• 50+ Webinars
• 10+ Expert podcasts
• 50+ Infographics
• 10+ Checklists
• Research Guides

We hate spam too. We promise to protect your privacy and never spam you.

I am looking for Editing/ Proofreading services for my manuscript Tentative date of next journal submission:

What would be most effective in reducing research misconduct?

Last updated 27/06/24: Online ordering is currently unavailable due to technical issues. We apologise for any delays responding to customers while we resolve this. For further updates please visit our website: https://www.cambridge.org/news-and-insights/technical-incident

We use cookies to distinguish you from other users and to provide you with a better experience on our websites. Close this message to accept cookies or find out how to manage your cookie settings .

Login Alert

• > How to Do Research
• > Draw conclusions and make recommendations

Book contents

• Frontmatter
• Acknowledgements
• Introduction: Types of research
• Part 1 The research process
• 1 Develop the research objectives
• 2 Design and plan the study
• 3 Write the proposal
• 4 Obtain financial support for the research
• 5 Manage the research
• 6 Draw conclusions and make recommendations
• 7 Write the report
• 8 Disseminate the results
• Part 2 Methods
• Appendix The market for information professionals: A proposal from the Policy Studies Institute

6 - Draw conclusions and make recommendations

from Part 1 - The research process

Published online by Cambridge University Press:  09 June 2018

This is the point everything has been leading up to. Having carried out the research and marshalled all the evidence, you are now faced with the problem of making sense of it all. Here you need to distinguish clearly between three different things: results, conclusions and recommendations.

Results are what you have found through the research. They are more than just the raw data that you have collected. They are the processed findings of the work – what you have been analysing and striving to understand. In total, the results form the picture that you have uncovered through your research. Results are neutral. They clearly depend on the nature of the questions asked but, given a particular set of questions, the results should not be contentious – there should be no debate about whether or not 63 per cent of respondents said ‘yes’ to question 16.

When you consider the results you can draw conclusions based on them. These are less neutral as you are putting your interpretation on the results and thus introducing a degree of subjectivity. Some research is simply descriptive – the final report merely presents the results. In most cases, though, you will want to interpret them, saying what they mean for you – drawing conclusions.

These conclusions might arise from a comparison between your results and the findings of other studies. They will, almost certainly, be developed with reference to the aim and objectives of the research. While there will be no debate over the results, the conclusions could well be contentious. Someone else might interpret the results differently, arriving at different conclusions. For this reason you need to support your conclusions with structured, logical reasoning.

Having drawn your conclusions you can then make recommendations. These should flow from your conclusions. They are suggestions about action that might be taken by people or organizations in the light of the conclusions that you have drawn from the results of the research. Like the conclusions, the recommendations may be open to debate. You may feel that, on the basis of your conclusions, the organization you have been studying should do this, that or the other.

Access options

Save book to kindle.

To save this book to your Kindle, first ensure [email protected] is added to your Approved Personal Document E-mail List under your Personal Document Settings on the Manage Your Content and Devices page of your Amazon account. Then enter the ‘name’ part of your Kindle email address below. Find out more about saving to your Kindle .

Note you can select to save to either the @free.kindle.com or @kindle.com variations. ‘@free.kindle.com’ emails are free but can only be saved to your device when it is connected to wi-fi. ‘@kindle.com’ emails can be delivered even when you are not connected to wi-fi, but note that service fees apply.

Find out more about the Kindle Personal Document Service .

• Draw conclusions and make recommendations
• Book: How to Do Research
• Online publication: 09 June 2018
• Chapter DOI: https://doi.org/10.29085/9781856049825.007

Save book to Dropbox

To save content items to your account, please confirm that you agree to abide by our usage policies. If this is the first time you use this feature, you will be asked to authorise Cambridge Core to connect with your account. Find out more about saving content to Dropbox .

Save book to Google Drive

To save content items to your account, please confirm that you agree to abide by our usage policies. If this is the first time you use this feature, you will be asked to authorise Cambridge Core to connect with your account. Find out more about saving content to Google Drive .

Suggestions for Future Research

Your dissertation needs to include suggestions for future research. Depending on requirements of your university, suggestions for future research can be either integrated into Research Limitations section or it can be a separate section.

You will need to propose 4-5 suggestions for future studies and these can include the following:

1. Building upon findings of your research . These may relate to findings of your study that you did not anticipate. Moreover, you may suggest future research to address unanswered aspects of your research problem.

2. Addressing limitations of your research . Your research will not be free from limitations and these may relate to formulation of research aim and objectives, application of data collection method, sample size, scope of discussions and analysis etc. You can propose future research suggestions that address the limitations of your study.

3. Constructing the same research in a new context, location and/or culture . It is most likely that you have addressed your research problem within the settings of specific context, location and/or culture. Accordingly, you can propose future studies that can address the same research problem in a different settings, context, location and/or culture.

4. Re-assessing and expanding theory, framework or model you have addressed in your research . Future studies can address the effects of specific event, emergence of a new theory or evidence and/or other recent phenomenon on your research problem.

My e-book,  The Ultimate Guide to Writing a Dissertation in Business Studies: a step by step assistance  offers practical assistance to complete a dissertation with minimum or no stress. The e-book covers all stages of writing a dissertation starting from the selection to the research area to submitting the completed version of the work within the deadline. John Dudovskiy

• - Google Chrome

Intended for healthcare professionals

• My email alerts
• BMA member login
• Username * Password * Forgot your log in details? Need to activate BMA Member Log In Log in via OpenAthens Log in via your institution

Search form

• Advanced search
• Search responses
• Search blogs
• How to formulate...

How to formulate research recommendations

• Related content
• Peer review
• Polly Brown ([email protected]) , publishing manager 1 ,
• Klara Brunnhuber , clinical editor 1 ,
• Kalipso Chalkidou , associate director, research and development 2 ,
• Iain Chalmers , director 3 ,
• Mike Clarke , director 4 ,
• Mark Fenton , editor 3 ,
• Carol Forbes , reviews manager 5 ,
• Julie Glanville , associate director/information service manager 5 ,
• Nicholas J Hicks , consultant in public health medicine 6 ,
• Janet Moody , identification and prioritisation manager 6 ,
• Sara Twaddle , director 7 ,
• Hazim Timimi , systems developer 8 ,
• Pamela Young , senior programme manager 6
• 1 BMJ Publishing Group, London WC1H 9JR,
• 2 National Institute for Health and Clinical Excellence, London WC1V 6NA,
• 3 Database of Uncertainties about the Effects of Treatments, James Lind Alliance Secretariat, James Lind Initiative, Oxford OX2 7LG,
• 4 UK Cochrane Centre, Oxford OX2 7LG,
• 5 Centre for Reviews and Dissemination, University of York, York YO10 5DD,
• 6 National Coordinating Centre for Health Technology Assessment, University of Southampton, Southampton SO16 7PX,
• 7 Scottish Intercollegiate Guidelines Network, Edinburgh EH2 1EN,
• 8 Update Software, Oxford OX2 7LG
• Correspondence to: PBrown
• Accepted 22 September 2006

“More research is needed” is a conclusion that fits most systematic reviews. But authors need to be more specific about what exactly is required

Long awaited reports of new research, systematic reviews, and clinical guidelines are too often a disappointing anticlimax for those wishing to use them to direct future research. After many months or years of effort and intellectual energy put into these projects, authors miss the opportunity to identify unanswered questions and outstanding gaps in the evidence. Most reports contain only a less than helpful, general research recommendation. This means that the potential value of these recommendations is lost.

Current recommendations

In 2005, representatives of organisations commissioning and summarising research, including the BMJ Publishing Group, the Centre for Reviews and Dissemination, the National Coordinating Centre for Health Technology Assessment, the National Institute for Health and Clinical Excellence, the Scottish Intercollegiate Guidelines Network, and the UK Cochrane Centre, met as members of the development group for the Database of Uncertainties about the Effects of Treatments (see bmj.com for details on all participating organisations). Our aim was to discuss the state of research recommendations within our organisations and to develop guidelines for improving the presentation of proposals for further research. All organisations had found weaknesses in the way researchers and authors of systematic reviews and clinical guidelines stated the need for further research. As part of the project, a member of the Centre for Reviews and Dissemination under-took a rapid literature search to identify information on research recommendation models, which found some individual methods but no group initiatives to attempt to standardise recommendations.

Suggested format for research recommendations on the effects of treatments

Core elements.

E Evidence (What is the current state of the evidence?)

P Population (What is …

Log in using your username and password

BMA Member Log In

If you have a subscription to The BMJ, log in:

• Need to activate
• Log in via institution
• Log in via OpenAthens

Log in through your institution

Subscribe from £184 *.

Subscribe and get access to all BMJ articles, and much more.

* For online subscription

Access this article for 1 day for: £33 / $40 / €36 ( excludes VAT )

You can download a PDF version for your personal record.

Buy this article

Have a language expert improve your writing

Run a free plagiarism check in 10 minutes, generate accurate citations for free.

• Knowledge Base
• Dissertation

How to Write a Thesis or Dissertation Conclusion

Published on September 6, 2022 by Tegan George and Shona McCombes. Revised on November 20, 2023.

The conclusion is the very last part of your thesis or dissertation . It should be concise and engaging, leaving your reader with a clear understanding of your main findings, as well as the answer to your research question .

In it, you should:

• Clearly state the answer to your main research question
• Summarize and reflect on your research process
• Make recommendations for future work on your thesis or dissertation topic
• Show what new knowledge you have contributed to your field
• Wrap up your thesis or dissertation

Instantly correct all language mistakes in your text

Upload your document to correct all your mistakes in minutes

Table of contents

Discussion vs. conclusion, how long should your conclusion be, step 1: answer your research question, step 2: summarize and reflect on your research, step 3: make future recommendations, step 4: emphasize your contributions to your field, step 5: wrap up your thesis or dissertation, full conclusion example, conclusion checklist, other interesting articles, frequently asked questions about conclusion sections.

While your conclusion contains similar elements to your discussion section , they are not the same thing.

Your conclusion should be shorter and more general than your discussion. Instead of repeating literature from your literature review , discussing specific research results , or interpreting your data in detail, concentrate on making broad statements that sum up the most important insights of your research.

As a rule of thumb, your conclusion should not introduce new data, interpretations, or arguments.

Don't submit your assignments before you do this

The academic proofreading tool has been trained on 1000s of academic texts. Making it the most accurate and reliable proofreading tool for students. Free citation check included.

Try for free

Depending on whether you are writing a thesis or dissertation, your length will vary. Generally, a conclusion should make up around 5–7% of your overall word count.

An empirical scientific study will often have a short conclusion, concisely stating the main findings and recommendations for future research. A humanities dissertation topic or systematic review , on the other hand, might require more space to conclude its analysis, tying all the previous sections together in an overall argument.

Your conclusion should begin with the main question that your thesis or dissertation aimed to address. This is your final chance to show that you’ve done what you set out to do, so make sure to formulate a clear, concise answer.

• Don’t repeat a list of all the results that you already discussed
• Do synthesize them into a final takeaway that the reader will remember.

An empirical thesis or dissertation conclusion may begin like this:

A case study –based thesis or dissertation conclusion may begin like this:

In the second example, the research aim is not directly restated, but rather added implicitly to the statement. To avoid repeating yourself, it is helpful to reformulate your aims and questions into an overall statement of what you did and how you did it.

Your conclusion is an opportunity to remind your reader why you took the approach you did, what you expected to find, and how well the results matched your expectations.

To avoid repetition , consider writing more reflectively here, rather than just writing a summary of each preceding section. Consider mentioning the effectiveness of your methodology , or perhaps any new questions or unexpected insights that arose in the process.

You can also mention any limitations of your research, but only if you haven’t already included these in the discussion. Don’t dwell on them at length, though—focus on the positives of your work.

• While x limits the generalizability of the results, this approach provides new insight into y .
• This research clearly illustrates x , but it also raises the question of y .

Here's why students love Scribbr's proofreading services

Discover proofreading & editing

You may already have made a few recommendations for future research in your discussion section, but the conclusion is a good place to elaborate and look ahead, considering the implications of your findings in both theoretical and practical terms.

• Based on these conclusions, practitioners should consider …
• To better understand the implications of these results, future studies could address …
• Further research is needed to determine the causes of/effects of/relationship between …

When making recommendations for further research, be sure not to undermine your own work. Relatedly, while future studies might confirm, build on, or enrich your conclusions, they shouldn’t be required for your argument to feel complete. Your work should stand alone on its own merits.

Just as you should avoid too much self-criticism, you should also avoid exaggerating the applicability of your research. If you’re making recommendations for policy, business, or other practical implementations, it’s generally best to frame them as “shoulds” rather than “musts.” All in all, the purpose of academic research is to inform, explain, and explore—not to demand.

Make sure your reader is left with a strong impression of what your research has contributed to the state of your field.

Some strategies to achieve this include:

• Returning to your problem statement to explain how your research helps solve the problem
• Referring back to the literature review and showing how you have addressed a gap in knowledge
• Discussing how your findings confirm or challenge an existing theory or assumption

Again, avoid simply repeating what you’ve already covered in the discussion in your conclusion. Instead, pick out the most important points and sum them up succinctly, situating your project in a broader context.

The end is near! Once you’ve finished writing your conclusion, it’s time to wrap up your thesis or dissertation with a few final steps:

• It’s a good idea to write your abstract next, while the research is still fresh in your mind.
• Next, make sure your reference list is complete and correctly formatted. To speed up the process, you can use our free APA citation generator .
• Once you’ve added any appendices , you can create a table of contents and title page .
• Finally, read through the whole document again to make sure your thesis is clearly written and free from language errors. You can proofread it yourself , ask a friend, or consider Scribbr’s proofreading and editing service .

Here is an example of how you can write your conclusion section. Notice how it includes everything mentioned above:

V. Conclusion

The current research aimed to identify acoustic speech characteristics which mark the beginning of an exacerbation in COPD patients.

The central questions for this research were as follows: 1. Which acoustic measures extracted from read speech differ between COPD speakers in stable condition and healthy speakers? 2. In what ways does the speech of COPD patients during an exacerbation differ from speech of COPD patients during stable periods?

All recordings were aligned using a script. Subsequently, they were manually annotated to indicate respiratory actions such as inhaling and exhaling. The recordings of 9 stable COPD patients reading aloud were then compared with the recordings of 5 healthy control subjects reading aloud. The results showed a significant effect of condition on the number of in- and exhalations per syllable, the number of non-linguistic in- and exhalations per syllable, and the ratio of voiced and silence intervals. The number of in- and exhalations per syllable and the number of non-linguistic in- and exhalations per syllable were higher for COPD patients than for healthy controls, which confirmed both hypotheses.

However, the higher ratio of voiced and silence intervals for COPD patients compared to healthy controls was not in line with the hypotheses. This unpredicted result might have been caused by the different reading materials or recording procedures for both groups, or by a difference in reading skills. Moreover, there was a trend regarding the effect of condition on the number of syllables per breath group. The number of syllables per breath group was higher for healthy controls than for COPD patients, which was in line with the hypothesis. There was no effect of condition on pitch, intensity, center of gravity, pitch variability, speaking rate, or articulation rate.

This research has shown that the speech of COPD patients in exacerbation differs from the speech of COPD patients in stable condition. This might have potential for the detection of exacerbations. However, sustained vowels rarely occur in spontaneous speech. Therefore, the last two outcome measures might have greater potential for the detection of beginning exacerbations, but further research on the different outcome measures and their potential for the detection of exacerbations is needed due to the limitations of the current study.

Checklist: Conclusion

I have clearly and concisely answered the main research question .

I have summarized my overall argument or key takeaways.

I have mentioned any important limitations of the research.

I have given relevant recommendations .

I have clearly explained what my research has contributed to my field.

I have  not introduced any new data or arguments.

You've written a great conclusion! Use the other checklists to further improve your dissertation.

If you want to know more about AI for academic writing, AI tools, or research bias, make sure to check out some of our other articles with explanations and examples or go directly to our tools!

Research bias

• Survivorship bias
• Self-serving bias
• Availability heuristic
• Halo effect
• Hindsight bias
• Deep learning
• Generative AI
• Machine learning
• Reinforcement learning
• Supervised vs. unsupervised learning

 (AI) Tools

• Grammar Checker
• Paraphrasing Tool
• Text Summarizer
• AI Detector
• Plagiarism Checker
• Citation Generator

In a thesis or dissertation, the discussion is an in-depth exploration of the results, going into detail about the meaning of your findings and citing relevant sources to put them in context.

The conclusion is more shorter and more general: it concisely answers your main research question and makes recommendations based on your overall findings.

While it may be tempting to present new arguments or evidence in your thesis or disseration conclusion , especially if you have a particularly striking argument you’d like to finish your analysis with, you shouldn’t. Theses and dissertations follow a more formal structure than this.

All your findings and arguments should be presented in the body of the text (more specifically in the discussion section and results section .) The conclusion is meant to summarize and reflect on the evidence and arguments you have already presented, not introduce new ones.

For a stronger dissertation conclusion , avoid including:

• Important evidence or analysis that wasn’t mentioned in the discussion section and results section
• Generic concluding phrases (e.g. “In conclusion …”)
• Weak statements that undermine your argument (e.g., “There are good points on both sides of this issue.”)

Your conclusion should leave the reader with a strong, decisive impression of your work.

The conclusion of your thesis or dissertation shouldn’t take up more than 5–7% of your overall word count.

The conclusion of your thesis or dissertation should include the following:

• A restatement of your research question
• A summary of your key arguments and/or results
• A short discussion of the implications of your research

Cite this Scribbr article

If you want to cite this source, you can copy and paste the citation or click the “Cite this Scribbr article” button to automatically add the citation to our free Citation Generator.

George, T. & McCombes, S. (2023, November 20). How to Write a Thesis or Dissertation Conclusion. Scribbr. Retrieved July 1, 2024, from https://www.scribbr.com/dissertation/write-conclusion/

Is this article helpful?

Tegan George

Other students also liked, how to write a discussion section | tips & examples, how to write an abstract | steps & examples, how to write a thesis or dissertation introduction, "i thought ai proofreading was useless but..".

I've been using Scribbr for years now and I know it's a service that won't disappoint. It does a good job spotting mistakes”

Educational resources and simple solutions for your research journey

What are Implications and Recommendations in Research? How to Write It, with Examples

Highly cited research articles often contain both implications and recommendations , but there is often some confusion around the difference between implications and recommendations in research. Implications of a study are the impact your research makes in your chosen area; they discuss how the findings of the study may be important to justify further exploration of your research topic. Research recommendations suggest future actions or subsequent steps supported by your research findings. It helps to improve your field of research or cross-disciplinary fields through future research or provides frameworks for decision-makers or policymakers. Recommendations are the action plan you propose based on the outcome.

In this article, we aim to simplify these concepts for researchers by providing key insights on the following:  

• what are implications in research 
• what is recommendation in research 
• differences between implications and recommendations 
• how to write implications in research 
• how to write recommendation in research 
• sample recommendation in research 

Table of Contents

What are implications in research

The implications in research explain what the findings of the study mean to researchers or to certain subgroups or populations beyond the basic interpretation of results. Even if your findings fail to bring radical or disruptive changes to existing ways of doing things, they might have important implications for future research studies. For example, your proposed method for operating remote-controlled robots could be more precise, efficient, or cheaper than existing methods, or the remote-controlled robot could be used in other application areas. This could enable more researchers to study a specific problem or open up new research opportunities.   

Implications in research inform how the findings, drawn from your results, may be important for and impact policy, practice, theory, and subsequent research. Implications may be theoretical or practical. 1  

• Practical implications are potential values of the study with practical or real outcomes . Determining the practical implications of several solutions can aid in identifying optimal solution results. For example, clinical research or research on classroom learning mostly has practical implications in research . If you developed a new teaching method, the implication would be how teachers can use that method based on your findings.  
• Theoretical implications in research constitute additions to existing theories or establish new theories. These types of implications in research characterize the ability of research to influence society in apparent ways. It is, at most, an educated guess (theoretical) about the possible implication of action and need not be as absolute as practical implications in research . If your study supported the tested theory, the theoretical implication would be that the theory can explain the investigated phenomenon. Else, your study may serve as a basis for modifying the theory. Theories may be partially supported as well, implying further study of the theory or necessary modifications are required.  

What are recommendations in research?

Recommendations in research can be considered an important segment of the analysis phase. Recommendations allow you to suggest specific interventions or strategies to address the issues and constraints identified through your study. It responds to key findings arrived at through data collection and analysis. A process of prioritization can help you narrow down important findings for which recommendations are developed.  

Recommendations in research examples

Recommendations in research may vary depending on the purpose or beneficiary as seen in the table below.  

Table: Recommendations in research examples based on purpose and beneficiary  

If you’re wondering how to make recommendations in research . You can use the simple  recommendation in research example below as a handy template.  

Table: Sample recommendation in research template  

Basic differences between implications and recommendations in research

Implications and recommendations in research are two important aspects of a research paper or your thesis or dissertation. Implications discuss the importance of the research findings, while recommendations offer specific actions to solve a problem. So, the basic difference between the two is in their function and the questions asked to achieve it. The following table highlights the main differences between implications and recommendations in research .  

Table: Differences between implications and recommendations in research  

Where do implications go in your research paper

Because the implications and recommendations of the research are based on study findings, both are usually written after the completion of a study. There is no specific section dedicated to implications in research ; they are usually integrated into the discussion section adding evidence as to why the results are meaningful and what they add to the field. Implications can be written after summarizing your main findings and before the recommendations and conclusion.   

Implications can also be presented in the conclusion section after a short summary of the study results.   

How to write implications in research

Implication means something that is inferred. The implications of your research are derived from the importance of your work and how it will impact future research. It is based on how previous studies have advanced your field and how your study can add to that.   

When figuring out how to write implications in research , a good strategy is to separate it into the different types of implications in research , such as social, political, technological, policy-related, or others. As mentioned earlier, the most frequently used are the theoretical and practical implications.   

Next, you need to ask, “Who will benefit the most from reading my paper?” Is it policymakers, physicians, the public, or other researchers? Once you know your target population, explain how your findings can help them.  

The implication section can include a paragraph or two that asserts the practical or managerial implications and links it to the study findings. A discussion can then follow, demonstrating that the findings can be practically implemented or how they will benefit a specific audience. The writer is given a specific degree of freedom when writing research implications , depending on the type of implication in research you want to discuss: practical or theoretical. Each is discussed differently, using different words or in separate sections. The implications can be based on how the findings in your study are similar or dissimilar to that in previous studies. Your study may reaffirm or disprove the results of other studies, which has important implications in research . You can also suggest future research directions in the light of your findings or require further research to confirm your findings, which are all crucial implications. Most importantly, ensure the implications in research are specific and that your tone reflects the strength of your findings without exaggerating your results.   

Implications in research can begin with the following specific sentence structures:  

• These findings suggest that…
• These results build on existing body of evidence of…
• These results should be considered when…
• While previous research focused on x, our results show that y…

What should recommendations in research look like?

Recommendations for future research should be:  

• Directly related to your research question or findings  
• Concrete and specific  
• Supported by a clear reasoning  

The recommendations in research can be based on the following factors:  

1. Beneficiary: A paper’s research contribution may be aimed at single or multiple beneficiaries, based on which recommendations can vary. For instance, if your research is about the quality of care in hospitals, the research recommendation to different beneficiaries might be as follows:  

• Nursing staff: Staff should undergo training to enhance their understanding of what quality of care entails.  
• Health science educators: Educators must design training modules that address quality-related issues in the hospital.  
• Hospital management: Develop policies that will increase staff participation in training related to health science.  

2. Limitations: The best way to figure out what to include in your research recommendations is to understand the limitations of your study. It could be based on factors that you have overlooked or could not consider in your present study. Accordingly, the researcher can recommend that other researchers approach the problem from a different perspective, dimension, or methodology. For example, research into the quality of care in hospitals can be based on quantitative data. The researcher can then recommend a qualitative study of factors influencing the quality of care, or they can suggest investigating the problem from the perspective of patients rather than the healthcare providers.   

3. Theory or Practice: Your recommendations in research could be implementation-oriented or further research-oriented.   

4. Your research: Research recommendations can be based on your topic, research objectives, literature review, and analysis, or evidence collected. For example, if your data points to the role of faculty involvement in developing effective programs, recommendations in research can include developing policies to increase faculty participation. Take a look at the evidence-based recommendation in research example s provided below.   

Table: Example of evidence-based research recommendation  

Avoid making the following mistakes when writing research recommendations :  

• Don’t undermine your own work: Recommendations in research should offer suggestions on how future studies can be built upon the current study as a natural extension of your work and not as an entirely new field of research.  
• Support your study arguments: Ensure that your research findings stand alone on their own merits to showcase the strength of your research paper.   

How to write recommendations in research

When writing research recommendations , your focus should be on highlighting what additional work can be done in that field. It gives direction to researchers, industries, or governments about changes or developments possible in this field. For example, recommendations in research can include practical and obtainable strategies offering suggestions to academia to address problems. It can also be a framework that helps government agencies in developing strategic or long-term plans for timely actions against disasters or aid nation-building.  

There are a few SMART 2 things to remember when writing recommendations in research. Your recommendations must be: 

• S pecific: Clearly state how challenges can be addressed for better outcomes and include an action plan that shows what can be achieved. 
• M easurable: Use verbs denoting measurable outcomes, such as identify, analyze, design, compute, assess, evaluate, revise, plan, etc., to strengthen recommendations in research .   
• A ttainable: Recommendations should offer a solution-oriented approach to problem-solving and must be written in a way that is easy to follow.  
• R elevant: Research recommendations should be reasonable, realistic, and result-based. Make sure to suggest future possibilities for your research field.  
• T imely: Time-based or time-sensitive recommendations in research help divide the action plan into long-term or short-term (immediate) goals. A timeline can also inform potential readers of what developments should occur over time.  

If you are wondering how many words to include in your research recommendation , a general rule of thumb would be to set aside 5% of the total word count for writing research recommendations . Finally, when writing the research implications and recommendations , stick to the facts and avoid overstating or over-generalizing the study findings. Both should be supported by evidence gathered through your data analysis.  

References:  

• Schmidt, F. L., & Hunter, J. E. (1998). The validity and utility of selection methods in personnel psychology: Practical and theoretical implications of 85 years of research findings.  Psychological bulletin ,  124 (2), 262.
• Doran, G. T. (1981). There’s a S.M.A.R.T. way to write management’s goals and objectives.  Manag Rev ,  70 (11), 35-36.

Researcher.Life is a subscription-based platform that unifies the best AI tools and services designed to speed up, simplify, and streamline every step of a researcher’s journey. The Researcher.Life All Access Pack is a one-of-a-kind subscription that unlocks full access to an AI writing assistant, literature recommender, journal finder, scientific illustration tool, and exclusive discounts on professional publication services from Editage.  

Based on 21+ years of experience in academia, Researcher.Life All Access empowers researchers to put their best research forward and move closer to success. Explore our top AI Tools pack, AI Tools + Publication Services pack, or Build Your Own Plan. Find everything a researcher needs to succeed, all in one place –  Get All Access now starting at just $17 a month !    

Related Posts

What is a Case Study in Research? Definition, Methods, and Examples

Take Top AI Tools for Researchers for a Spin with the Editage All Access 7-Day Pass!

Have a language expert improve your writing

Run a free plagiarism check in 10 minutes, automatically generate references for free.

• Knowledge Base
• Dissertation
• How to Write Recommendations in Research | Examples & Tips

How to Write Recommendations in Research | Examples & Tips

Published on 15 September 2022 by Tegan George .

Recommendations in research are a crucial component of your discussion section and the conclusion of your thesis , dissertation , or research paper .

As you conduct your research and analyse the data you collected , perhaps there are ideas or results that don’t quite fit the scope of your research topic . Or, maybe your results suggest that there are further implications of your results or the causal relationships between previously-studied variables than covered in extant research.

Instantly correct all language mistakes in your text

Be assured that you'll submit flawless writing. Upload your document to correct all your mistakes.

Table of contents

What should recommendations look like, building your research recommendation, how should your recommendations be written, recommendation in research example, frequently asked questions about recommendations.

Recommendations for future research should be:

• Concrete and specific
• Supported with a clear rationale
• Directly connected to your research

Overall, strive to highlight ways other researchers can reproduce or replicate your results to draw further conclusions, and suggest different directions that future research can take, if applicable.

Relatedly, when making these recommendations, avoid:

• Undermining your own work, but rather offer suggestions on how future studies can build upon it
• Suggesting recommendations actually needed to complete your argument, but rather ensure that your research stands alone on its own merits
• Using recommendations as a place for self-criticism, but rather as a natural extension point for your work

The only proofreading tool specialized in correcting academic writing

The academic proofreading tool has been trained on 1000s of academic texts and by native English editors. Making it the most accurate and reliable proofreading tool for students.

Correct my document today

There are many different ways to frame recommendations, but the easiest is perhaps to follow the formula of research question   conclusion  recommendation. Here’s an example.

Conclusion An important condition for controlling many social skills is mastering language. If children have a better command of language, they can express themselves better and are better able to understand their peers. Opportunities to practice social skills are thus dependent on the development of language skills.

As a rule of thumb, try to limit yourself to only the most relevant future recommendations: ones that stem directly from your work. While you can have multiple recommendations for each research conclusion, it is also acceptable to have one recommendation that is connected to more than one conclusion.

These recommendations should be targeted at your audience, specifically toward peers or colleagues in your field that work on similar topics to yours. They can flow directly from any limitations you found while conducting your work, offering concrete and actionable possibilities for how future research can build on anything that your own work was unable to address at the time of your writing.

See below for a full research recommendation example that you can use as a template to write your own.

The current study can be interpreted as a first step in the research on COPD speech characteristics. However, the results of this study should be treated with caution due to the small sample size and the lack of details regarding the participants’ characteristics.

Future research could further examine the differences in speech characteristics between exacerbated COPD patients, stable COPD patients, and healthy controls. It could also contribute to a deeper understanding of the acoustic measurements suitable for e-health measurements.

Prevent plagiarism, run a free check.

While it may be tempting to present new arguments or evidence in your thesis or disseration conclusion , especially if you have a particularly striking argument you’d like to finish your analysis with, you shouldn’t. Theses and dissertations follow a more formal structure than this.

All your findings and arguments should be presented in the body of the text (more specifically in the discussion section and results section .) The conclusion is meant to summarize and reflect on the evidence and arguments you have already presented, not introduce new ones.

The conclusion of your thesis or dissertation should include the following:

• A restatement of your research question
• A summary of your key arguments and/or results
• A short discussion of the implications of your research

For a stronger dissertation conclusion , avoid including:

• Generic concluding phrases (e.g. “In conclusion…”)
• Weak statements that undermine your argument (e.g. “There are good points on both sides of this issue.”)

Your conclusion should leave the reader with a strong, decisive impression of your work.

In a thesis or dissertation, the discussion is an in-depth exploration of the results, going into detail about the meaning of your findings and citing relevant sources to put them in context.

The conclusion is more shorter and more general: it concisely answers your main research question and makes recommendations based on your overall findings.

Cite this Scribbr article

If you want to cite this source, you can copy and paste the citation or click the ‘Cite this Scribbr article’ button to automatically add the citation to our free Reference Generator.

George, T. (2022, September 15). How to Write Recommendations in Research | Examples & Tips. Scribbr. Retrieved 1 July 2024, from https://www.scribbr.co.uk/thesis-dissertation/research-recommendations/

Is this article helpful?

Tegan George

Other students also liked, how to write a discussion section | tips & examples, how to write a thesis or dissertation conclusion, how to write a results section | tips & examples.

Science Teachers' Learning: Enhancing Opportunities, Creating Supportive Contexts (2015)

Chapter: 9 conclusions, recommendations, and directions for research.

Conclusions, Recommendations, and Directions for Research

In many ways, the message of this report is a simple one: all students deserve to understand and enjoy science, and helping teachers offer rich instruction will require building similarly rich learning environments for all science teachers. Creating such environments entails creating meaningful formal professional development programs and other opportunities for teachers to learn, as well as implementing policies and practices in schools that nurture cultures of learning for teachers and students alike.

As simple as this message may seem, the proverbial devil is in the details. As the new vision for the science education of K-12 students set forth in the Next Generation Science Standards (hereafter referred to as NGSS) and A Framework for K-12 Science Education (hereafter referred to as the Framework) has evolved, it is one that engages students in learning scientific and engineering practices, disciplinary core ideas, and crosscutting concepts. To achieve this new vision, teaching and learning in science classrooms will need to change, and so, too, will professional learning opportunities for teachers. This chapter summarizes the committee’s major conclusions and recommendations for effecting the needed changes, which are based on the evidence reviewed in this report and on the committee members’ collective expertise. We begin with the conclusions that flow directly from the analyses of existing literature in each chapter. We then lay out a set of conclusions the committee drew after looking across these analyses.

CONCLUSIONS

In reviewing the available research related to issues of contemporary science teacher learning, the committee drew a series of interrelated conclusions:

Conclusion 1: An evolving understanding of how best to teach science, including the NGSS, represents a significant transition in the way science is currently taught in most classrooms and will require most science teachers to alter the way they teach.

This vision of science learning and teaching draws on a long tradition of reform in science education that has emphasized the need for all students to learn significant disciplinary core ideas, coupled with scientific and engineering practices that are part of inquiry. In addition, the vision emphasizes the need to integrate knowledge through crosscutting concepts. To teach science in these ways, teachers will need to move away from traditional models of instruction that emphasize memorizing facts and covering a large number of discrete topics, focusing instead on core ideas, studied in depth, through active student engagement in investigations and opportunities to reflect on and build scientific explanations for phenomena.

Conclusion 2: The available evidence suggests that many science teachers have not had sufficiently rich experiences with the content relevant to the science courses they currently teach, let alone a substantially redesigned science curriculum. Very few teachers have experience with the science and engineering practices described in the NGSS. These trends are especially pronounced both for elementary school teachers and in schools that serve high percentages of low-income students, where teachers are often newer and less qualified.

Although professional development is available to all teachers, the committee found no evidence that elementary, middle, and high school science teachers have adequately rigorous opportunities to learn content related to the courses they teach, the new vision of science education, or how to teach to that new vision in challenging and effective ways. Instead, professional development appears to be more piecemeal, with few—if any—opportunities for the majority of teachers to engage in sustained study of science, scientific practices, and effective science instruction. High school teachers have some of these opportunities, while middle and elementary school teachers, who themselves may not have had much preparation in science and science teaching in their initial teacher prepa-

ration experiences, have fewer. Again, this situation is most pronounced in schools that serve high percentages of low-income students, and in which teacher turnover is especially high, leading to a less experienced and qualified workforce.

Conclusion 3: Typically, the selection of and participation in professional learning opportunities is up to individual teachers. There is often little attention to developing collective capacity for science teaching at the building and district levels or to offering teachers learning opportunities tailored to their specific needs and offered in ways that support cumulative learning over time.

While teachers in U.S. schools are required to participate regularly in professional development, mandated professional development tends to be generic, with little attention to systematically meeting the needs of science teachers. Many teachers pursue their own learning, taking summer professional development courses, volunteering to participate in curriculum development and/or review, working with preservice teachers, or taking on the role of professional developer or instructional coach. However, these individual pursuits are seldom linked to a well-articulated theory of teacher learning over time or a systemic vision of how to develop individual and collective teacher capacity.

Conclusion 4: Science teachers’ learning needs are shaped by their preparation, the grades and content areas they teach, and the contexts in which they work. Three important areas in which science teachers need to develop expertise are

• the knowledge, capacity, and skill required to support a diverse range of students;
• content knowledge, including understanding of disciplinary core ideas, crosscutting concepts, and scientific and engineering practices; and
• pedagogical content knowledge for teaching science, including a repertoire of teaching practices that support students in rigorous and consequential science learning.

The set of professional knowledge and skills that informs good teaching is vast. Central to this knowledge base are the knowledge and skill needed to teach all students, mastery of science and science practices, and understanding and skill in teaching science. The committee acknowledges that there are other domains of knowledge equally essential to effective science teaching, and chose to focus on these three as there is considerable science-specific research on how these domains enable high-quality

teaching. The capacity to teach all students science depends on teachers’ respect for and understanding of the range of experiences and knowledge that students from diverse backgrounds bring to school, and how to capitalize on those experiences in crafting rigorous instruction. Knowledge of the sciences one is assigned to teach, of how those sciences are related to one another and to other fields like engineering, and knowledge and skill in how best to teach students science also are essential to high-quality instruction as envisioned in the NGSS and Framework.

This new vision of science teaching and learning will require new learning on the part of all teachers in all of these domains. The knowledge that students bring with them from their families and communities that is relevant to disciplinary core ideas, scientific and engineering practices, and crosscutting concepts is an area yet to be fully explored. In general, many teachers have had limited opportunities to engage in scientific and engineering practices themselves, much less to explore them in connection with the disciplinary core ideas and crosscutting concepts that animate the new vision. New curricula and instructional experiences will need to be crafted—with input from and the active engagement of teachers themselves—to bring that vision to life in U.S. classrooms. The knowledge demands of this new vision will require that the entire community—science teachers, teacher educators, professional developers, and science education researchers, as well as institutions of higher education, cultural institutions, and industry all of which invest in professional development—to create new, ongoing opportunities for teachers to rise to these new standards and to document what they learn from their efforts along the way.

Conclusion 5: The best available evidence based on science professional development programs suggests that the following features of such programs are most effective:

• active participation of teachers who engage in the analysis of examples of effective instruction and the analysis of student work,
• a content focus,
• alignment with district policies and practices, and
• sufficient duration to allow repeated practice and/or reflection on classroom experiences.

The national interest in the power of professional development to enhance teacher quality has led to considerable investments in such programs and in research on what makes them effective. While the goal of linking professional development to student learning outcomes through

research remains somewhat elusive, a great deal has been learned from the careful work of researchers and professional development leaders who have iteratively built professional learning programs for teachers. More research remains to be conducted in this area, but the research in science education, as well as mathematics, suggests that professional development of sufficient duration to allow teachers to deepen their pedagogical content knowledge and practice new instructional methods in their classrooms can lead to improved instruction and student achievement. Hallmarks of high-quality professional learning opportunities include focus on specific content that is aligned with district or school curriculum and assessment policies, as well as the proactive and professional engagement of teachers are hallmarks of high-quality professional learning opportunities.

Conclusion 6: Professional learning in online environments and through social networking holds promise, although evidence on these modes from both research and practice is limited.

The potential to use new media to enhance teacher learning is undeniable. Social networking and online environments hold promise for meeting the “just-in-time” learning needs of teachers, and for providing access to science expertise and science education expertise for teachers in schools and communities that lack rich resources in these domains. While these areas have yet to be fully explored by teacher developers and science education researchers, the committee sees considerable potential for these resources as research accumulates concerning their effective use.

Conclusion 7: Science teachers’ professional learning occurs in a range of settings both within and outside of schools through a variety of structures (professional development programs, professional learning communities, coaching, and the like). There is limited evidence about the relative effectiveness of this broad array of learning opportunities and how they are best designed to support teacher learning.

Recently, there has been increasing commitment to creating schools where both students and teachers can learn. This heightened interest in “embedded professional learning” can take many forms, including professional learning communities; professional networks that reach across districts, the state, or the country; induction programs for early-career teachers; and coaching and mentoring for teachers wishing to improve their practice. Since teachers spend the majority of their professional time in classrooms and schools, it seems wise to capitalize on efforts to design

settings that support their professional learning, both individually and collectively and to expand research in those settings.

Conclusion 8: Schools need to be structured to encourage and support ongoing learning for science teachers especially given the number of new teachers entering the profession.

A growing body of research documents the generative conditions established for teacher learning when schools foster collective responsibility for student learning and well-being. However, the evidence base related to learning opportunities for teachers in schools and classrooms is weak, especially with regard to science. This, too, appears to be an area with too much potential to ignore. In particular, building school infrastructure that systematically develops the science and science teaching expertise necessary to engage all students meaningfully in the new vision embodied the Framework and NGSS can work proactively to ameliorate differences between schools that have ready access to such expertise and those that struggle to connect with it.

Conclusion 9: Science teachers’ development is best understood as long term and contextualized. The schools and classrooms in which teachers work shape what and how they learn. These contexts include, but are not limited to school, district, and state policies and practices concerning professional capacity (e.g., professional networks, coaching, partnerships), coherent instructional guidance (e.g., state and district curriculum and assessment/accountability policies), and leadership (e.g., principals and teacher leaders).

Teachers’ capacity to teach science well over time is intimately related to the environments in which they teach. The policies and practices that shape instruction vary from teacher evaluation to curriculum and accountability to teacher assignment. For example, teachers cannot teach science courses that do not align with their preparation. Nor is it productive for the feedback teachers receive concerning their annual evaluations to run counter to messages about effective science instruction embodied in curriculum policies.

Conclusion 10 : School and district administrators are central to building the capacity of the science teacher workforce.

Conditions in schools and districts can create contexts that allow teachers to take better advantage of professional learning opportunities both within the workday and outside of school. These conditions might

include, for example, required professional development time and other learning opportunities designed to foster better understanding of how to teach the redesigned science curriculum. Administrators can direct resources (e.g., location of teachers, scheduling of classes, materials budget) toward science and teachers’ learning in science. They also can send messages about the importance of science in schools. As instructional leaders, they need to understand the vision for science education in the Framework and NGSS and align policies and practices in the school to support this vision.

Conclusion 11: Teacher leaders may be an important resource for building a system that can support ambitious science instruction. There is increasing attention to creating opportunities for teachers to take on leadership roles to both improve science instruction and strengthen the science teacher workforce. These include roles as instructional coaches, mentors, and teacher leaders.

Expertise in both science and pedagogy in science is an important component of building capacity in schools and districts. The development of science teacher leaders can be an important mechanism for supporting science learning for all teachers. The range of new roles for teacher leaders—lead teacher, curriculum specialist, mentor, collaborating teacher, instructional coach, professional development leader—holds considerable potential for enhancing the science teacher workforce. Not only do these teacher leaders engage in advanced study of science and science teaching themselves, but they also take on roles that involve helping fellow teachers learn. Such leaders can guide school- or district-based professional learning communities, identify useful resources, and provide feedback to teachers as they modify their instructional practices. While little research exists on the effects of these leaders on teacher learning more generally, the committee sees these new roles as a potentially powerful mechanism for improving science teacher quality collectively.

In addition to the above conclusions, all of which are drawn from chapter-specific analyses, the committee drew two additional conclusions based on the big picture emerging from these related, but separate analyses.

Conclusion 12: Closing the gap between the new way of teaching science and current instruction in many schools will require attending to individual teachers’ learning needs, as well as to the larger system of practices and policies (such as allocation of resources, use of time, and provision of opportunities for collaboration) that shape how science is taught.

The committee’s view of science teacher learning is both individual and collective. That is, we see science teacher learning as an issue of building the capacity not only of individual teachers, but also of the science educator workforce more generally, particularly the capacity of science teachers in a school or district. The demands of schooling are such that distributed expertise is essential and building capacity across a group of teachers needs to be the goal. In addition, enhancing the collective teacher workforce is not simply a matter of ensuring that teachers, individually and collectively, have the necessary knowledge and skill. It is also necessary for schools, districts, school networks, and states to develop practices and policies including teacher hiring and retention, teacher evaluation, curriculum and accountability guidance, and school staffing and school/district leadership that enable good science teaching. Contexts shape the work of teaching, and enhancing science instruction in the United States will require new policies as well as well-prepared teachers.

Conclusion 13: The U.S. educational system lacks a coherent and well-articulated system of learning opportunities for teachers to continue developing expertise while in the classroom. Opportunities are unevenly distributed across schools, districts, and regions, with little attention to sequencing or how to support science teachers’ learning systematically. Moreover, schools and districts often lack systems that can provide a comprehensive view of teacher learning; identify specific teacher needs; or track investments—in time, money and resources—in science teachers’ professional learning

This is not a new observation, but it is a continuing problem. Despite a wealth of opportunities for science teacher learning offered in schools and districts and through cultural institutions and industry—ranging from summer institutes to research apprenticeships to curriculum development to Lesson Study—the majority of the nation’s science are impoverished in terms of targeted, coherent, aligned, and cumulative opportunities to enrich their understanding and practices in teaching all students challenging science. Piecemeal approaches have not redressed this well-established problem.

New incentives and investments to redesign/restructure science teachers’ learning opportunities in schools, districts, school networks, and partnerships are needed. In particular, leadership by administrators at the school and district levels is critical to promoting and supporting the enabling conditions for science teachers to learn. Teacher leaders also play a critical role in these efforts. Approaches for elementary, middle, and high schools may need to vary, but in every case, school systems need ways to identify the myriad opportunities that exist for teacher learning, when and under what conditions these opportunities are aligned with one

another, and how scarce resources can best be used to maximize opportunities for teacher learning and growth.

RECOMMENDATIONS FOR PRACTICE AND POLICY

Teachers matter, but they do not work in a vacuum. Their ability to elevate students’ scientific understanding depends on the schools, districts, and communities in which they work and the professional communities to which they belong. The recommendations below are intended to address the issues identified in the conclusions with particular attention to the ways that the current education system needs to be changed in order to support teachers’ ongoing learning as they respond to the demands placed by current reforms in science education.

Here, we focus on how schools and school systems (such as districts or charter networks) can improve the learning opportunities for science teachers. Focusing on this level of the system is essential, given the important roles played by principals and teacher leaders in connecting the rhetoric of visions such as that embodied in the Framework and NGSS to the realities of how teachers and students spend their time. Below we offer some specific recommendations for practices and policies we view as necessary to enhance ongoing teacher learning. Because the research base in this area is so uneven, often lacking science-specific studies related to the issues raised in this report, we think that these recommendations go hand-in-hand with research needs, and we offer recommendations for meeting these needs later in this chapter.

The following recommendations are not intended to be in chronological order—Recommendation 1, for example, does not have to be carried out first. Indeed, a plan for acting on recommendations toward the goal of enhancing science teacher learning to meet student learning goals is needed, and that plan might entail acting on a small number of recommendations, ordered in a way that capitalizes on current practice and policy and accelerates change.

In an ideal world, all these recommendations would be implemented. But in the real and complex world of schooling, it is important to start with one recommendation, building momentum, and with a long term goal of acting on the full set. Equally important is that acting on these recommendations will require additional resources (money, material, time, and personnel) or significant shifts in priorities. Such tradeoffs are inevitable, but investing in the individual and collective capacity of the workforce is essential to the improvement of science teaching in the United States. Finally, the committee presumes that acting on these recommendations

will require the engagement of teachers, teacher leaders, and administrators as partners in creating strong systems of science teacher learning.

Recommendation 1:

Take stock of the current status of learning opportunities for science teachers: School and district administrators should identify current offerings and opportunities for teacher learning in science—using a broad conceptualization of teacher learning opportunities, and including how much money and time are spent (as well as other associated costs). Throughout this process, attention should be paid to the opportunities available for teachers to learn about

• approaches for teaching all students,
• science content and scientific practices, and
• science pedagogical knowledge and science teaching practices.

When identifying costs, administrators should consider both traditional professional development time and other supports for learning, such as curriculum, teacher evaluation, and student assessment/accountability. Given differences in the learning needs of elementary, middle, and high school teachers, expenditures and time allocations should be broken down by grade level and by school and district level. Plans to address any inequities across classrooms or schools should be developed with an eye toward policies and practices that will equitably distribute teacher expertise and teacher learning opportunities across the system.

Recommendation 2:

Design a portfolio of coherent learning experiences for science teachers that attend to teachers’ individual and context-specific needs in partnership with professional networks, institutions of higher education, cultural institutions, and the broader scientific community as appropriate: Teachers and school and district administrators should articulate, implement, and support teacher learning opportunities in science as coherent, graduated sequences of experiences toward larger goals for improving science teaching and learning. Here, too, attention should be paid to building teachers’ knowledge and skill in the sciences and scientific practices, in science pedagogical content knowledge, and in science teaching practices. It is critical to support teachers’ opportunities to learn how to connect with students of diverse backgrounds and experiences and how to tap into relevant funds of knowledge of students and communities.

District personnel and school principals, in collaboration with teachers and parents, should identify the specific learning needs of science teachers in their schools and develop a multiyear growth plan for their

science teachers’ learning that is linked to their growth plan for students’ science learning. Central to this work are four questions:

• In light of our school’s/district’s science goals for our students, what learning opportunities will teachers need?
• What kinds of expertise are needed to support these learning opportunities?
• Where is that expertise located (inside and outside of schools)?
• What social arrangements and resources will enable this work?

Using a variety of assessments/measures designed to provide the kind of concrete feedback necessary to support (teacher and program) improvement, school principals, in collaboration with teachers and school partners, should regularly consult data form such sources as (teacher observations, student work, and student surveys or interviews) to assess progress on the growth plan. It will also be important to consider the larger contexts in which the plan will unfold and how existing policies and practices regarding personnel (hiring, retention, placement) and instructional guidance (curriculum and assessment) can enable or limit the plan.

Recommendation 3:

Consider both specialized professional learning programs outside of school and opportunities for science teachers’ learning embedded in the workday: A coherent, standards and evidence-based portfolio of professional learning opportunities for science teachers should include both specialized programs that occur outside of the school day and ongoing learning opportunities that are built into the workday and enhance capacity in schools and districts. Development of this portfolio will require some restructuring of teachers’ work in schools to support new learning opportunities. School and district leaders will need to develop policies and practices that provide the necessary resources (fiscal, time, facilities, tools, incentives).

As school and district leaders identify professional learning opportunities for science teachers, they should work to develop a portfolio of opportunities that address teachers’ varied needs, in ways that are sensitive to the school or district context. School and district leaders should not only make this portfolio of opportunities available to teachers; but also actively encourage, through their leadership and provision of resources, teachers’ engagement in these opportunities, and provide time during the school day for teachers to engage meaningfully in them. Furthermore, school and district leaders should work with teams of teachers to build coherent programs of science teaching learning opportunities, tailored to individual teachers and the school as a whole. The portfolio of teacher

learning opportunities should include structured, traditional professional development; cross-school teacher professional communities, and collaborations with local partners.

Recommendation 4:

Design and select learning opportunities for science teachers that are informed by the best available research: Teachers’ learning opportunities should be aligned with a system’s science standards, and should be grounded in an underlying theory of teacher learning and in research on the improvement of professional practice, and on how to meet the needs of the range of adult and student learners in a school or district. Learning opportunities for science teachers should have the following characteristics:

• Designed to achieve specific learning goals for teachers.
• Be content specific, that is, focused on particular scientific concepts and practices.
• Be student specific, that is, focused on the specific students served by the school district.
• Linked to teachers’ classroom instruction and include analysis of instruction.
• Include opportunities for teachers to practice teaching science in new ways and to interact with peers in improving the implementation of new teaching strategies.
• Include opportunities for teachers to collect and analyze data on their students’ learning.
• Offer opportunities for collaboration.

Designers of learning opportunities for teachers including commercial providers, community organizations, institutions of higher education and districts and states, should develop learning opportunities for teachers that reflect the above criteria.

When selecting learning opportunities for teachers, district and school leaders and teachers themselves should use the above criteria as a guide for identifying the most promising programs and learning experiences. District and state administrators should use these criteria to provide guidance for teachers on how to identify high-quality learning experiences.

District and state administrators should use (and make public) quality indicators to identify, endorse, and fund a portfolio of teacher learning opportunities, and should provide guidance for school leaders and teachers on how to select high-quality learning experiences in science appropriate to specific contexts.

Recommendation 5:

Develop internal capacity in science while seeking external partners with science expertise: School and district leaders should work to build school- and district-level capacity around science teaching. These efforts should include creating learning opportunities for teachers but might also include exploring different models for incorporating science expertise, such as employing science specialists at the elementary level or providing high school science department heads with time to observe and collaborate with their colleagues. When developing a strategy for building capacity, school and district leaders should consider the tradeoffs inherent in such choices.

School and district leaders should also explore developing partnerships with individuals and organizations—such as local businesses, institutions of higher education or science rich institutions—that can bring science expertise.

Crucial to developing relevant expertise is developing the capacity of professional development leaders. Investing in the development of professional developers who are knowledgeable about teaching all students the vision of science education represented in the NGSS (Next Generation Science Standards Lead States, 2013) and the Framework (National Research Council, 2012) is critical. It is not sufficient for these leaders to be good teachers themselves; they must also be prepared and supported to work with adult learners and to coordinate professional development with other policies and programs (including staffing, teacher evaluation, curriculum development, and student assessment).

Recommendation 6:

Create, evaluate, and revise policies and practices that encourage teachers to engage in professional learning related to science: District and school administrators and relevant leaders should work to establish dedicated professional development time during the salaried work week and work year for science teachers. They should encourage teachers to participate in science learning opportunities and structure time to allow for collaboration around science. Resources for professional learning should include time to meet with other teachers, to observe other classrooms, and to attend discrete events; space to meet with other teachers; requested materials; and incentives to participate. These policies and practices should take advantage of linkages with other policies For example, natural connections can be made between policies concerning professional development and teacher evaluation. Similarly, administrators could develop policies that more equitably distribute qualified and experienced science teachers across all students in school, districts, and school networks.

At the elementary level, district and school leaders should work to

establish parity for science professional development in relationship to other subjects, especially mathematics and English language arts.

Recommendation 7:

The potential of new formats and media should be explored to support science teachers’ learning when appropriate: Districts should consider the use of technology and online spaces/resources to support teacher learning in science. These tools may be particularly useful for supporting cross-school collaboration, providing teachers with flexible schedules for accessing resources, or enabling access to professional learning opportunities in rural areas where teachers may be isolated and it is difficult to convene in a central location.

As noted, the above recommendations focus on schools and districts/school networks, as the committee sees work at that level as a necessary condition for realizing the vision of the Framework and NGSS. Without the work of teachers, professional development leaders, and school leaders at the local level, the promise of these visionary documents cannot be realized.

Of course, working at that local level—while necessary—is not sufficient to change how science is taught across the United States and determining whether all children have access to high-quality science learning experiences. Within and across states, as well as nationally, science education needs to be elevated through policies, practices, and funding mechanisms. Without that kind of support, the local and essential work described in these recommendations will fall short. Other reports of the National Research Council (2014, 2015) include recommendations targeted to the state level that identify policies such as those related to assessment (National Research Council, 2014), high school graduation requirements (National Research Council, 2015), and teacher certification (National Research Council, 2015) that can help create supportive contexts for improving science education. The National Research Council (2013) also has issued recommendations for a national indicator system that would make it possible to track improvement in STEM education reforms, covering domains of state policy, curriculum, accountability, and teacher quality, and the National Science Teachers Association has issued a number of relevant position statements on accountability, teacher preparation and induction, leadership, and professional development. 1

As states, districts, and schools move forward with initiatives aimed at improving supports for science teachers’ learning, they should leverage these and other relevant resources that have been developed by such national organizations as the National Science Teachers Association, the

______________

1 See http://www.nsta.org/about/positions/#list [November 2015].

Council of State Science Supervisors, and Achieve, Inc. and are available online. These organizations also are creating networks of science educators who are exploring the Framework and NGSS and sharing ideas about implementation of the vision set forth in those documents. It is a massive undertaking to support all students, teachers, and schools in rising to the challenges of the new vision of science teaching and learning. And while the committee’s recommendations focus on a set of strategic activities that schools and districts might undertake to make progress, the science teachers, scientists, science teacher educators, and professional development leaders who constitute the membership of these organizations can contribute much to an enriched understanding of how to support ongoing teacher learning.

RECOMMENDATIONS FOR RESEARCH

Considerable research exists, both in science education and in education more generally on which to draw, for insights into the wise development of policies, programs, and practices that will enhance teacher learning. At the same time, much remains to be learned. The committee identified several areas of research that would inform the work of school leaders interested in supporting ongoing teacher learning. Before offering our recommendations for future research, we reiterate the major gaps in the research literature.

• No system is in place to collect data on the science teacher workforce, their qualifications, experience, and preparation. This is due in part to differences across states in both teacher certification and data collection; the problem is exacerbated by a lack of measures that could be used to do comparative work. The authors of the National Research Council (2010) study of teacher preparation make a similar observation.
• No system is in place to collect data on general trends in science teaching and learning. This gap will challenge the collective capacity to assess any progress that may be made on meeting the challenges of the vision in the Framework and the NGSS. The observations in the National Research Council report Monitoring Progress Toward Successful K-21 STEM Education (2013) are similar. Studies vary in both their conceptions of good science teaching and how teaching is measured, compromising the capacity to ascertain general trends.
• No system in place to collect data about the myriad professional learning opportunities that teachers encounter in and out of

school. The committee found enormous variation in teacher learning opportunities, with no centralized way to determine general trends or the effectiveness of various programs or combinations of experiences. This observation is similar to a conclusion drawn by the authors of the National Research Council (2010) report on teacher preparation.

• While there is a body of research on formal science professional development, that research tends to focus on individual programs and to rely heavily on teacher self report. Few studies used research designs involving control or comparison groups and incorporating pre/post measures of teachers’ knowledge and beliefs, instruction, and students’ outcomes. Without such studies, it is difficult to draw strong conclusions about effectiveness. The field lacks consistently used, technically powerful measures of science teachers’ knowledge and practice, as well as measures that capture the full range of student outcomes. There are a handful of noteworthy exceptions to this pattern (e.g., Heller et al., 2012; Roth et al., 2011).
• Substantially less research exists on other, potentially equally important opportunities for science teacher learning, including professional learning communities, mentoring and coaching, online learning, teacher networks, and teacher evaluation. In general, the evidence base related to learning opportunities for teachers that are embedded in schools and classrooms is weak, especially with regard to science.
• Almost no studies address school organization and context and how they might affect the impact of professional development programs. Little to no published research exists on the effects of recruitment, retention, and staffing policies on the quality of the science teaching workforce and of science instruction in schools and districts.
• Research on how and under what conditions principals and leaders affect the quality of science learning in their schools has yet to be conducted. Also lacking in the research literature are studies of how teachers learn to become leaders, as well as research that examines the role, expertise, or preparation of science professional development providers and facilitators.

Research Recommendation 1: Focus Research on Linking Professional Learning to Changes in Instructional Practice and Student Learning

In general, more research is needed to understand the path from professional learning opportunities to changes in teacher knowledge and

practice to student learning and engagement in terms of both individual teachers and the teacher workforce more generally. To be maximally helpful, that research should attend to the contexts in which teachers learn and teach (see Figure 8-2). The contextual factors that shape and are shaped by teachers’ learning opportunities, include teacher hiring, staffing, and assignment policies and practices; student and school demographics; resource distribution and use; instructional guidance; teacher evaluation; and school organization.

Research Recommendation 2: Invest in Improving Measures of Science Instruction and Science Learning

Fundamental to most research aimed at linking science teacher learning to student science learning and engagement is the development of publicly credible, technically sound, and professionally responsible measures of relevant teacher and student outcomes. Because teaching and learning also have subject-specific aspects, these outcome measures need to sample broadly from the practices, disciplinary core ideas, and crosscutting concepts outlined in the new vision of science teaching and learning. The committee cannot emphasize enough the centrality of good measures of teacher and student learning, particularly for addressing gaps in all of the domains cited above. This issue is noted in the National Research Council report Monitoring Progress Toward Successful K-12 STEM Education (National Research Council, 2013) as well. Lacking good outcome measures, considerable resources will continue to be devoted to professional learning opportunities with a limited ability to gauge their effects. Such measures would enable a great deal of needed research.

Research Recommendation 3: Design and Implement Research That Examines a Variety of Approaches to Supporting Science Teachers’ Learning

The committee urges a broad conceptualization of professional learning and thus research that examines how teachers learn from portfolios of learning opportunities, including both off-site and embedded professional development (e.g., study groups, professional learning communities, lesson study). Of particular benefit would be research assessing the effects of the interactions among various learning opportunities, as well as the particular contributions of different kinds of learning experiences to teacher knowledge and practice. The conduct of such research would require having much better documentation of the range of learning opportunities in which teachers participate and that were designed intentionally to build upon, extend, and enhance one another. Moreover, any investment in

teacher learning ought to be designed to document its effects; this would mean designing strong research in tandem with professional learning experiences, whether those experiences are based in cultural institutions, industry, universities, or schools. As is the case with all of the research recommended here, attention should be paid to contextual variation and how aspects of state, district, and school context mediate and/or moderate the effects of professional learning opportunities on teacher practice and student learning.

Typical research on professional learning is small scale, conducted by the program designers or providers, and uses locally developed measures. Although a growing number of studies entail carrying out large-scale, rigorous examinations of professional development interventions that link teachers’ learning to student outcomes, the results of those studies are mixed. The collective body of small-scale research has produced some insights, but understanding of the nature and effects of the range of professional learning opportunities will remain limited without large-scale studies that include multiple programs and are not as dependent on teacher self-report. A wide range of research methodologies have important roles in shedding light on science teacher learning, as does the use of multiple measures of teacher knowledge and practice and student engagement and learning.

Research Recommendation 4: Commit to Focusing on Meeting the Needs of Diverse Science Learners Across All Research on Professional Development

The committee urges that research on science teacher learning focus on opportunities that help teachers meet the needs of diverse students while teaching to the standards. Accomplishing this goal will require developing and studying professional learning programs—in and outside of schools—that interweave attention to science content with attention to the needs and experiences of all students, including English language learners, special education students, gifted and talented students, and diverse learners. Compelling research exists in many of these areas. But teachers do not teach diverse learners on Tuesdays and science on Wednesdays; they teach the two together, and supportive professional learning experiences for teachers will integrate knowledge across a range of domains. For example, teachers would be aided in achieving the new vision by research documenting how they can tap into students’ funds of knowledge when teaching a specific scientific practice or disciplinary idea. In other words, research that attends to the development of all three dimensions of teacher knowledge and skill discussed in this report—the

capacity to respond to all learners, disciplinary scientific knowledge, and pedagogical content knowledge—is essential.

Research Recommendation 5: Focus Research on Exploring the Potential Role of Technology

When relevant, attending to the potential role of technology in enabling teacher learning would help schools and school districts take advantage of the capabilities of new technologies in enabling teacher learning. Such research could focus on online or hybrid professional development programs, face-to-face learning opportunities that take advantage of the use of technology in pursuit of ambitious instruction, the use of technology to teach to the new vision of science learning, or the support of online professional networks of teachers.

Research Recommendation 6: Design and Implement Research Focused on the Learning Needs of Teacher Leaders and Professional Development Providers

The field also needs research on the development of teacher educators, professional development leaders, and teacher leaders more generally. Learning to teach teachers is related to but distinct from learning to teach. Research documenting and explaining how skilled teacher developers acquire relevant knowledge and practice would help improve the quality of professional learning across the myriad settings in which it takes place.

FINAL REFLECTIONS

First, given current efforts toward developing new curriculum and assessment materials aligned with the Framework and NGSS, it would be strategic to design research that documents what teachers learn in developing and implementing those materials, especially in their classrooms and with the range of supports provided to help them. As teachers and schools embrace the new vision for science teaching and learning, teachers, teacher leaders, principals, and professional development staff will be learning a great deal. Research should document that learning so that efforts to reform science instruction can learn productively from that experimentation.

Second, many fields of research relevant to science teaching and learning currently do not address what science teachers and their students learn. Science education would benefit greatly from being integrated into programs of research concerning instructional reform, English language

learners, how to reach and teach diverse student populations, teacher preparation, and teacher evaluation.

Finally, given that many schools and school networks are currently engaged in efforts to improve teacher learning opportunities, some of the research envisioned here might draw on design-based implementation research, networked improvement communities, strategic education partnerships, or other research designs. These research traditions—which are designed as collaborations among various stakeholders (schools, teachers, policy makers, and researchers) and committed to responding quickly to data and shifting course when necessary—holds great promise for helping teachers and schools respond in a timely fashion to the mandate to raise standards and teach all children scientifically rich curricula.

Heller, J.I., Daehler, K.R., Wong, N., Shinohara, M., and Miratrix, L.W. (2012). Differential effects of three professional development models on teacher knowledge and student achievement in elementary science. Journal of Research in Science Teaching , 49 (3), 333-362.

National Research Council. (2010). Preparing Teachers: Building Evidence for Sound Policy. Committee on the Study of Teacher Preparation Programs in the United States, Center for Education, Division of Behavioral and Social Sciences and Education. Washington, DC: The National Academies Press.

National Research Council. (2012). A Framework for K-12 Science Education: Practices, Crosscutting Concepts, and Core ideas. Committee on a Conceptual Framework for New K-12 Science Education Standards, Board on Science Education. Division of Behavioral and Social Sciences and Education. Washington, DC: The National Academies Press.

National Research Council. (2013). Monitoring Progress Toward Successful K-12 STEM Education: A Nation Advancing? Committee on the Evaluation Framework for Successful K-12 STEM Education. Board on Science Education and Board on Testing and Assessment, Division of Behavioral and Social Sciences and Education. Washington, DC: The National Academies Press.

National Research Council. (2014). Developing Assessments for the Next Generation Science Standards. Committee on Developing Assessments of Science Proficiency in K-12. Board on Testing and Assessment, Board on Science Education, Division of Behavioral and Social Sciences and Education. Washington, DC: The National Academies Press.

National Research Council. (2015). Guide to Implementing the Next Generation Science Standards . Committee on Guidance on Implementing the Next Generation Science Standards. Board on Science Education, Division of Behavioral and Social Sciences and Education. Washington, DC: The National Academies Press.

Next Generation Science Standards Lead States. (2013). Next Generation Science Standards: For States, By States . Washington, DC: The National Academies Press.

Roth, K., Garnier, H., Chen, C., Lemmens, M., Schwille, K., and Wickler, N.I.Z. (2011). Videobased lesson analysis: Effective science PD for teacher and student learning. Journal of Research in Science Teaching, 48 (2), 117-148.

Currently, many states are adopting the Next Generation Science Standards (NGSS) or are revising their own state standards in ways that reflect the NGSS. For students and schools, the implementation of any science standards rests with teachers. For those teachers, an evolving understanding about how best to teach science represents a significant transition in the way science is currently taught in most classrooms and it will require most science teachers to change how they teach.

That change will require learning opportunities for teachers that reinforce and expand their knowledge of the major ideas and concepts in science, their familiarity with a range of instructional strategies, and the skills to implement those strategies in the classroom. Providing these kinds of learning opportunities in turn will require profound changes to current approaches to supporting teachers' learning across their careers, from their initial training to continuing professional development.

A teacher's capability to improve students' scientific understanding is heavily influenced by the school and district in which they work, the community in which the school is located, and the larger professional communities to which they belong. Science Teachers' Learning provides guidance for schools and districts on how best to support teachers' learning and how to implement successful programs for professional development. This report makes actionable recommendations for science teachers' learning that take a broad view of what is known about science education, how and when teachers learn, and education policies that directly and indirectly shape what teachers are able to learn and teach.

The challenge of developing the expertise teachers need to implement the NGSS presents an opportunity to rethink professional learning for science teachers. Science Teachers' Learning will be a valuable resource for classrooms, departments, schools, districts, and professional organizations as they move to new ways to teach science.

READ FREE ONLINE

Welcome to OpenBook!

You're looking at OpenBook, NAP.edu's online reading room since 1999. Based on feedback from you, our users, we've made some improvements that make it easier than ever to read thousands of publications on our website.

Do you want to take a quick tour of the OpenBook's features?

Show this book's table of contents , where you can jump to any chapter by name.

...or use these buttons to go back to the previous chapter or skip to the next one.

Jump up to the previous page or down to the next one. Also, you can type in a page number and press Enter to go directly to that page in the book.

Switch between the Original Pages , where you can read the report as it appeared in print, and Text Pages for the web version, where you can highlight and search the text.

To search the entire text of this book, type in your search term here and press Enter .

Share a link to this book page on your preferred social network or via email.

View our suggested citation for this chapter.

Ready to take your reading offline? Click here to buy this book in print or download it as a free PDF, if available.

Get Email Updates

Do you enjoy reading reports from the Academies online for free ? Sign up for email notifications and we'll let you know about new publications in your areas of interest when they're released.

• Privacy Policy

Home » Future Research – Thesis Guide

Future Research – Thesis Guide

Table of Contents

Future Research

Definition:

Future research refers to investigations and studies that are yet to be conducted, and are aimed at expanding our understanding of a particular subject or area of interest. Future research is typically based on the current state of knowledge and seeks to address unanswered questions, gaps in knowledge, and new areas of inquiry.

How to Write Future Research in Thesis

Here are some steps to help you write effectively about future research in your thesis :

• Identify a research gap: Before you start writing about future research, identify the areas that need further investigation. Look for research gaps and inconsistencies in the literature , and note them down.
• Specify research questions : Once you have identified a research gap, create a list of research questions that you would like to explore in future research. These research questions should be specific, measurable, and relevant to your thesis.
• Discuss limitations: Be sure to discuss any limitations of your research that may require further exploration. This will help to highlight the need for future research and provide a basis for further investigation.
• Suggest methodologies: Provide suggestions for methodologies that could be used to explore the research questions you have identified. Discuss the pros and cons of each methodology and how they would be suitable for your research.
• Explain significance: Explain the significance of the research you have proposed, and how it will contribute to the field. This will help to justify the need for future research and provide a basis for further investigation.
• Provide a timeline : Provide a timeline for the proposed research , indicating when each stage of the research would be conducted. This will help to give a sense of the practicalities involved in conducting the research.
• Conclusion : Summarize the key points you have made about future research and emphasize the importance of exploring the research questions you have identified.

Examples of Future Research in Thesis

SomeExamples of Future Research in Thesis are as follows:

Future Research:

Although this study provides valuable insights into the effects of social media on self-esteem, there are several avenues for future research that could build upon our findings. Firstly, our sample consisted solely of college students, so it would be beneficial to extend this research to other age groups and demographics. Additionally, our study focused only on the impact of social media use on self-esteem, but there are likely other factors that influence how social media affects individuals, such as personality traits and social support. Future research could examine these factors in greater depth. Lastly, while our study looked at the short-term effects of social media use on self-esteem, it would be interesting to explore the long-term effects over time. This could involve conducting longitudinal studies that follow individuals over a period of several years to assess changes in self-esteem and social media use.

While this study provides important insights into the relationship between sleep patterns and academic performance among college students, there are several avenues for future research that could further advance our understanding of this topic.

• This study relied on self-reported sleep patterns, which may be subject to reporting biases. Future research could benefit from using objective measures of sleep, such as actigraphy or polysomnography, to more accurately assess sleep duration and quality.
• This study focused on academic performance as the outcome variable, but there may be other important outcomes to consider, such as mental health or well-being. Future research could explore the relationship between sleep patterns and these other outcomes.
• This study only included college students, and it is unclear if these findings generalize to other populations, such as high school students or working adults. Future research could investigate whether the relationship between sleep patterns and academic performance varies across different populations.
• Fourth, this study did not explore the potential mechanisms underlying the relationship between sleep patterns and academic performance. Future research could investigate the role of factors such as cognitive functioning, motivation, and stress in this relationship.

Overall, there is a need for continued research on the relationship between sleep patterns and academic performance, as this has important implications for the health and well-being of students.

Further research could investigate the long-term effects of mindfulness-based interventions on mental health outcomes among individuals with chronic pain. A longitudinal study could be conducted to examine the sustainability of mindfulness practices in reducing pain-related distress and improving psychological well-being over time. The study could also explore the potential mediating and moderating factors that influence the relationship between mindfulness and mental health outcomes, such as emotional regulation, pain catastrophizing, and social support.

Purpose of Future Research in Thesis

Here are some general purposes of future research that you might consider including in your thesis:

• To address limitations: Your research may have limitations or unanswered questions that could be addressed by future studies. Identify these limitations and suggest potential areas for further research.
• To extend the research : You may have found interesting results in your research, but future studies could help to extend or replicate your findings. Identify these areas where future research could help to build on your work.
• To explore related topics : Your research may have uncovered related topics that were outside the scope of your study. Suggest areas where future research could explore these related topics in more depth.
• To compare different approaches : Your research may have used a particular methodology or approach, but there may be other approaches that could be compared to your approach. Identify these other approaches and suggest areas where future research could compare and contrast them.
• To test hypotheses : Your research may have generated hypotheses that could be tested in future studies. Identify these hypotheses and suggest areas where future research could test them.
• To address practical implications : Your research may have practical implications that could be explored in future studies. Identify these practical implications and suggest areas where future research could investigate how to apply them in practice.

Applications of Future Research

Some examples of applications of future research that you could include in your thesis are:

• Development of new technologies or methods: If your research involves the development of new technologies or methods, you could discuss potential applications of these innovations in future research or practical settings. For example, if you have developed a new drug delivery system, you could speculate about how it might be used in the treatment of other diseases or conditions.
• Extension of your research: If your research only scratches the surface of a particular topic, you could suggest potential avenues for future research that could build upon your findings. For example, if you have studied the effects of a particular drug on a specific population, you could suggest future research that explores the drug’s effects on different populations or in combination with other treatments.
• Investigation of related topics: If your research is part of a larger field or area of inquiry, you could suggest potential research topics that are related to your work. For example, if you have studied the effects of climate change on a particular species, you could suggest future research that explores the impacts of climate change on other species or ecosystems.
• Testing of hypotheses: If your research has generated hypotheses or theories, you could suggest potential experiments or studies that could test these hypotheses in future research. For example, if you have proposed a new theory about the mechanisms of a particular disease, you could suggest experiments that could test this theory in other populations or in different disease contexts.

Advantage of Future Research

Including future research in a thesis has several advantages:

• Demonstrates critical thinking: Including future research shows that the author has thought deeply about the topic and recognizes its limitations. It also demonstrates that the author is interested in advancing the field and is not satisfied with only providing a narrow analysis of the issue at hand.
• Provides a roadmap for future research : Including future research can help guide researchers in the field by suggesting areas that require further investigation. This can help to prevent researchers from repeating the same work and can lead to more efficient use of resources.
• Shows engagement with the field : By including future research, the author demonstrates their engagement with the field and their understanding of ongoing debates and discussions. This can be especially important for students who are just entering the field and want to show their commitment to ongoing research.
• I ncreases the impact of the thesis : Including future research can help to increase the impact of the thesis by highlighting its potential implications for future research and practical applications. This can help to generate interest in the work and attract attention from researchers and practitioners in the field.

About the author

Muhammad Hassan

Researcher, Academic Writer, Web developer

You may also like

Research Recommendations – Examples and Writing...

Research Paper – Structure, Examples and Writing...

Thesis Outline – Example, Template and Writing...

Research Topics – Ideas and Examples

Research Approach – Types Methods and Examples

Dissertation Methodology – Structure, Example...

Conclusions and Recommendations for Future Research

• First Online: 08 April 2021

Cite this chapter

• Gert Janssenswillen   ORCID: orcid.org/0000-0002-7474-2088 7  

Part of the book series: Lecture Notes in Business Information Processing ((LNBIP,volume 412))

224 Accesses

At the start of this thesis, we set out on a quest for process realism: viewing and representing processes as they really are, as distinguished from the speculative.

Puzzles are sort of like life because you can mess up and rebuild later, and you’re likely smarter the next time around. Adam Silvera

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Subscribe and save.

• Get 10 units per month
• Download Article/Chapter or Ebook
• 1 Unit = 1 Article or 1 Chapter
• Cancel anytime
• Available as PDF
• Read on any device
• Instant download
• Own it forever
• Available as EPUB and PDF
• Compact, lightweight edition
• Dispatched in 3 to 5 business days
• Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

Author information

Authors and affiliations.

Research Group Business Informatics, Hasselt University, Diepenbeek, Belgium

Gert Janssenswillen

You can also search for this author in PubMed   Google Scholar

Corresponding author

Correspondence to Gert Janssenswillen .

Rights and permissions

Reprints and permissions

Copyright information

© 2021 Springer Nature Switzerland AG

About this chapter

Janssenswillen, G. (2021). Conclusions and Recommendations for Future Research. In: Unearthing the Real Process Behind the Event Data. Lecture Notes in Business Information Processing, vol 412. Springer, Cham. https://doi.org/10.1007/978-3-030-70733-0_10

Download citation

DOI : https://doi.org/10.1007/978-3-030-70733-0_10

Published : 08 April 2021

Publisher Name : Springer, Cham

Print ISBN : 978-3-030-70732-3

Online ISBN : 978-3-030-70733-0

eBook Packages : Computer Science Computer Science (R0)

Share this chapter

Anyone you share the following link with will be able to read this content:

Sorry, a shareable link is not currently available for this article.

Provided by the Springer Nature SharedIt content-sharing initiative

• Publish with us

Policies and ethics

• Find a journal
• Track your research

Unfortunately we don't fully support your browser. If you have the option to, please upgrade to a newer version or use Mozilla Firefox , Microsoft Edge , Google Chrome , or Safari 14 or newer. If you are unable to, and need support, please send us your feedback .

We'd appreciate your feedback. Tell us what you think! opens in new tab/window

3 scenarios for the future of research – which is most likely?

March 20, 2019 | 11 min read

By Alison Bert, DMA

Experts at AAAS weigh in on the new Research Futures study by Elsevier and Ipsos MORI

Caption: Experts debate the future of research at an interactive panel at the AAAS Annual Meeting in Washington, DC (from left): Dr. Peter Tindemans, Secretary General of EuroScience; Mary Woolley, President and CEO of Research!America; Prof. Sir Peter Gluckman, President Elect of the International Science Council; Dr. Joanne Tornow, Assistant Director for Biological Sciences at the National Science Foundation and, at the podium, Adrian Mulligan, Research Director for Customer Insights at Elsevier. (Photos by Alison Bert)

Imagine yourself 10 years from now. It’s 2029, and the world of research has changed – dramatically for some of you. But how?

Where will your research funding come from? Will your collaborators be academics or colleagues at a tech company?

Will you use artificial intelligence to determine your research hypothesis – and will journals use AI to decide whether to accept your paper? Will that “paper” even look like the manuscript you’re used to submitting?

If you’re a professor, will your students come to the university or study from afar?

These are just a few of the questions the new  Research Futures  scenario-planning study delves into. To forecast how research might be created and exchanged 10 years from now, investigators from Elsevier and Isos MORI examined the literature and market drivers, interviewed over 50 funders, futurists, publishers and technology experts and surveyed more than 2,000 researchers.

From the analysis, key themes emerged. The investigators then held creative workshops, and participants used this knowledge to develop three plausible scenarios    of the future:

Brave open world considers the rise of open science.

Tech titans looks at the growing influence of technology.

Eastern ascendance considers the role the East – and China in particular – might play.

Elsevier colleagues initially conceived this project to gain insights into how they could collaborate with the research community to build a better information system supporting research.

“We needed some information to inform our own decisions as an information analytics provider,” said Hannfried von Hindenburg, SVP of Global Communications, in introducing the panel. “But we felt we should make it public so that all of you could make your decisions based on this research.

“It’s meant to stimulate a discussion, and it’s meant to stimulate decision-making.”

That conversation continued when the report was released at the  Annual Meeting of the American Association for the Advancement of Science (AAAS) opens in new tab/window  in Washington, DC. A panel of research leaders – along with researchers in the audience – weighed in on which scenarios seemed most likely.

“Since we’re envisioning the future, there are no wrong answers,” said moderator Dr. Brad Fenwick, SVP of Global Strategic Alliances at Elsevier.

Hannfried von Hindenburg, SVP of Global Communications at Elsevier, introduces the report and panel at AAAS.

Exploring the future through a 3D lens

Adrian Mulligan summarizes key themes and scenarios in the report before seeking input from the panel and audience.

In his introduction to the report, lead investigator  Adrian Mulligan opens in new tab/window , Director of Research for Customer Insights at Elsevier, summarized the key points – starting with the “three dimensions” the experts  used to contemplate the future.

Three dimensions were used to contemplate the future: the progress of technology (blue); the degree of openness and sharing of research (orange); and those who support research and whether they would be aligned or fragmented (grey).

Blue represents the world of technology. “On one extreme, technology is revolutionary and drastically alters the way science is done,” Mulligan explained. “On the other, evolutionary tech is just like it is now, steadily progressing.”

Orange, meanwhile, represents the exchange of research and data and the degree to which it will be open or controlled, and gray represents whether organizations or nation states are aligned or fragmented.

Each of these elements combines with the others in a distinct way in the three future scenarios.

Scenario 1: Brave open world

In the Brave open world scenario, various factors converge for open collaboration.

“Brave open world” is characterized by open sharing of research, revolutionary technology and more convergence among stakeholders, Mulligan explained. For example, big tech partners with funders and research institutes to develop interoperable machine learning tools and platforms.

“In this scenario, all the actors and funders … come together to create an open platform in which science is shared,” he said. “Research articles are all open access, and the research article moves on from the current format to a more dynamic ‘notebook’ style that is more atomized and broken up.”

In addition, AI accelerates the speed and volume of research, and researchers are rewarded by a range of measures, including interdisciplinary collaboration, data dissemination and social impact.

Trust in science has increased because the public has greater access to published science, and researchers are expected present their work in a way that’s understandable to the lay person.

Scenario 2: Tech titans

In the Tech titans scenario, big tech companies take charge of the research landscape.

The “Tech titans” scenario is characterized by revolutionary technology, with the large tech companies becoming the main supporters, curators and distributors of knowledge. “The big technology companies step in and play a key role in the communication of science and the funding of research,” Mulligan said. “There are massive advances in AI in this world. Here, we see AI play such an important role that it changes society in essential ways. There are lots of job losses … in research as well.”

Much of research has become automated, driven by AI and data mining, and AI enables data-driven hypothesis generation – a practice we’re already experimenting with. Researchers often work closely with industry as independent consultants for large corporations.

Data sharing and machine learning have supported successful commercial breakthroughs, and the platforms the tech companies create have lowered the cost of doing research. However, there are concerns about data being held by private companies and not being made public – or medical advances not being evenly distributed. That competitive drive would likely spill onto the global stage.

“A number of countries are competing to deploy artificial intelligence, keeping it close to their chests in terms of the knowledge they have acquired in developing of new products,” Mulligan said. “And we find some countries struggling to adapt to making use of these new technologies.”

Meanwhile, it’s a politically fragmented world; state funding for research has been reduced, and industry and philanthropic organizations have stepped in to fill the gap, investing in challenge-led science.

Scenario 3: Eastern ascendance

In the Eastern ascendance scenario, China’s desire to transform into a knowledge-based economy has led to heavy public investment in R&D.

The third scenario – Eastern ascendance – is also a fragmented world, with a sharp division between the United States and China. “China has invested massively into research and development, and it’s really paying dividends for them,” Mulligan said. “In the West, we’re unable to keep up with what China is doing, and as a consequence, the sheer volume of that investment is really shaping the way research is being communicated and the advances that are being made.

“Actually, the world changes so much that China becomes a magnet for western researchers. So rather than Western researchers going to Oxford or MIT or the top universities in Europe, they’re heading towards China.

“Open science is embraced in this world,” he continued, “but only partly embraced because it’s quite a fragmented world. People are trying to take commercial advantage of the data and science that’s been communicated, so there’s a lack of global alignment on research projects. Everyone’s trying to do things in their own way.”

As a result, products like self-driving cars, or developments in personalized medicine, are not universally available.

In publishing, the Impact Factor continues to prevail and the subscription model plays a role. Meanwhile, big tech companies form  partnerships with publishers  to provide AI-enabled workflow and publishing tools.

Researchers or technology: which will drive new knowledge?

For the rest of the workshop, Dr. Fenwick posted questions from the survey, and audience members used their smart phones to register their answers in  Menti opens in new tab/window . For example:

Question:  “In 10 years, the creative force   driving forward new knowledge will be …”

Answer:  Researchers – Technology – Either equally likely

Mulligan started by alluding to the “robust intelligence of the ‘tech titan’ world” and the expanding role of AI in driving research: Could AI become so advanced that it could create new science? “We had a number of experts say that much of the hypotheses being generated will be coming from machines rather than humans,” he said. “The role of technology has the the potential to transform research.”

Two panelists challenged the question itself.

"The real idea underlying this statement is that AI will replace researchers completely, and this will not be the case," said Dr. Peter Tindemans, founding member and Secretary General of  EuroScience opens in new tab/window .

“I think it depends how you look at this,” said  Prof. Sir Peter Gluckman opens in new tab/window , President Elect of the  International Science Council opens in new tab/window  and former Chief Science Advisor for the Prime Minister of New Zealand. He referred to Prof.  Dan Sarewitz’s 2016 essay “Saving Science” in  The New Atlantis opens in new tab/window :

As Dan Sarewitz suggests … science is driven by technological development. Until the microscope was invented, you couldn’t look at the cell – etcetera, etcetera, etcetera. … Always new technologies allow new questions to be answered. So by definition, much science is driven ultimately by technological possibilities.

Dr.  Joanne Tornow opens in new tab/window , Assistant Director for Biological Sciences at the  National Science Foundation opens in new tab/window , countered with a vote for the researcher:

Technology by itself doesn’t answer the questions. It’s the researcher. … You have to have the technology – I agree. And technology is as disruptive and as transformational as an aha moment in understanding. But it doesn’t in and of itself solve a problem.

Dr. Fenwick then asked: “Where will the new idea to do the research come from? Where will the idea for the hypothesis come from? (How will it be decided whether) it’s worth researching? Will this be  in silico opens in new tab/window  or will it still be the PI that comes up with the idea?”

Dr. Tornow responded with still another question: “Where does new technology come from? New technology comes from ideas that researchers have. It’s kind of a virtuous cycle.”

Dr. Fenwick agreed that technology is often developed to meet the needs of science: “You wouldn’t build a collider if you didn’t have the scientific community saying I need this tool to answer this question.”

Then he played devil’s advocate: “On the other hand, I could make an argument that if we can’t digest all the science, but a machine can through machine learning, what if a machine came up with a question or hypothesis or a question worth asking and answering? Would we accept it?”

Not only would we accept it; researchers who enable their questions to be generated by AI would have a competitive advantage, Prof. Gluckman said. “Those researchers who do big data and use big-data tools tend to write papers that get into high impact journals,” he said. “And funders love big-data-based, meta-analysis type research.”

As the “chicken-and-egg” aspect of this conundrum became increasingly apparent, a woman in the audience aptly pointed out, “Someone had to write the algorithm.”

Ultimately, the panelists as well as the audience voted more in favor of researchers.

In the  Research Futures  survey of researchers, the most popular response was ‘researchers.’

Will students actually  go  to universities?

The next question dealt with the rising trend of distance learning in higher education:

Question:  “In 10 years, university student will be educated …

Answer:  Mostly on campus – Mostly remotely – Either equally likely.

Dr. Tindemans said there are pressing reasons for students to be on campus:

Students go to a university not just to learn something. Secondly, in many areas of study, you need to work together with your professors by doing experiments (and) other things together, and that is very difficult to organize another way. And the third thing is simply the status: a diploma is a link to what university and not just to a collection of exams you have passed online.

Mary Woolley opens in new tab/window , President and CEO of  Research!America opens in new tab/window , said the answer depends on the university and subjects being studied:

I would say there’s a context … of elite vs non-elite university and college institutions and education. For the elite, students would be more likely on campus. But for all the rest, which is a much higher percentage, I would think it would be increasingly remotely.

Dr. Fenwick pointed out that more elite universities in the US are “making a bet that they can do more distance learning.” As an example, he mentioned a university that bought a large education company, using Elsevier to create their learning platform.

Prof. Gluckman agreed that university education is likely to change, with a rise in interdisciplinary and team-based research, but added that other as yet uncertain factors would also impact these future scenarios. Prof. Gluckman foresees the probability of a more focused investment of government funding in a smaller proportion of research-intensive universities, with the other universities becoming more education-focused and offering more distance-learning options for current and continuing education. However, it’s not clear what form “lifelong re-learning and retraining” will take for many people, he said, “and I think we’re still a decade away from understanding how that’s going to evolve.”

Woolley mentioned “competing pressures” that could turn the tide either way: “the move toward interdisciplinary work and team science that really does require (in-person) interaction” versus the fact that “we’re getting much, much better at connecting remotely.” Ultimately, she said, it would depend on what fields people are studying, some of which will still require a presence on campus.

Similar to the panel’s responses, the audience’s were equally divided, as were those of the researchers who took the survey:

In the  Research Futures  survey of researchers, responses were divided almost equally.

“The best way to influence the future …”

In reflecting on the topic and what was learned from the study, Mulligan said: “You can think about the future, but the best way to influence the future is to create the future.”

Download the report and supporting material

The report  Research Futures: drivers and scenarios for the next decade  is freely available.

Download the summary report (including scenarios) opens in new tab/window

Download the full report (including the scenarios and essays) opens in new tab/window

Download the monitoring framework opens in new tab/window

Elements of the underlying study data are also freely available:

Visit Mendeley to view the list of references used for the literature review opens in new tab/window

View the full results and charts for the researcher survey opens in new tab/window

Find the results of the researcher survey on Mendeley Data opens in new tab/window

Contributor

Alison Bert, DMA

Executive Editor, Global Communications

Warning: The NCBI web site requires JavaScript to function. more...

An official website of the United States government

The .gov means it's official. Federal government websites often end in .gov or .mil. Before sharing sensitive information, make sure you're on a federal government site.

The site is secure. The https:// ensures that you are connecting to the official website and that any information you provide is encrypted and transmitted securely.

• Publications
• Account settings
• Browse Titles

NCBI Bookshelf. A service of the National Library of Medicine, National Institutes of Health.

Adams J, Bateman B, Becker F, et al. Effectiveness and acceptability of parental financial incentives and quasi-mandatory schemes for increasing uptake of vaccinations in preschool children: systematic review, qualitative study and discrete choice experiment. Southampton (UK): NIHR Journals Library; 2015 Nov. (Health Technology Assessment, No. 19.94.)

Effectiveness and acceptability of parental financial incentives and quasi-mandatory schemes for increasing uptake of vaccinations in preschool children: systematic review, qualitative study and discrete choice experiment.

Chapter 7 recommendations for future research.

Recommendations for future research have been considered in the discussion sections of Chapters 3 – 5 and are summarised here for ease of reference. We have attempted to place these in priority order.

• Further evidence is required on the effectiveness and cost-effectiveness of parental financial incentive and quasi-mandatory interventions for encouraging the uptake of preschool vaccinations. As such, interventions are likely to be implemented on a large scale; evaluation strategies such as natural experiments and step-wedge designs may be most useful in generating such evidence. 82
• Further evidence is required on the most effective and cost-effective configuration of any parental financial incentive and quasi-mandatory interventions for encouraging the uptake of preschool vaccinations. Intervention development work, taking account of existing behaviour-change theory, may be useful to maximise the potential effectiveness of incentive interventions. This should involve further consideration of the effective component, or components, of financial incentive interventions.
• Further consideration of reasons for non-vaccination should be incorporated into new interventions for promoting the uptake of preschool vaccinations. Parental financial incentive and quasi-mandatory interventions for encouraging uptake of preschool vaccinations may not adequately address the reasons for non-vaccination in high-income countries that tend to achieve overall high coverage of preschool vaccinations.
• Further consideration of how a quasi-mandatory intervention for encouraging the uptake of preschool vaccinations could be designed and implemented is required. Particular issues requiring further consideration include data sharing of vaccination status between health-care providers and schools, responsibilities of different sectors and staff, and how provision would be made for legitimate opt-out.
• If high-quality evidence of effectiveness of parental financial incentive and quasi-mandatory interventions for encouraging uptake of preschool vaccinations is generated, further evidence is required on how to effectively communicate this information to all stakeholders. As acceptability is linked to perceived effectiveness, further evidence on the impact of well-communicated effectiveness evidence on perceived acceptability is also required.
• The factors that may increase acceptance of mandatory schemes warrant further research, and additional DCEs could be conducted to explore parental preferences on how a mandate for vaccination might be imposed.
• Further consideration may be required of how existing systems and resources for encouraging the uptake of preschool vaccinations can be optimised. In particular, further evidence may be required on how to provide accessible information and education, and how to deliver accessible vaccination services. However, although these issues were raised in the present work, we did not conduct a systematic review on these topics and, as such, cannot make definitive recommendations for future research.
• Research engaging parents in an iterative codesign process to design optimally acceptable and usable information that conveys robust and balanced data on the consequences of disease and the benefits and risks of vaccinations is required.

Included under terms of UK Non-commercial Government License .

• Cite this Page Adams J, Bateman B, Becker F, et al. Effectiveness and acceptability of parental financial incentives and quasi-mandatory schemes for increasing uptake of vaccinations in preschool children: systematic review, qualitative study and discrete choice experiment. Southampton (UK): NIHR Journals Library; 2015 Nov. (Health Technology Assessment, No. 19.94.) Chapter 7, Recommendations for future research.
• PDF version of this title (21M)

Other titles in this collection

• Health Technology Assessment

Recent Activity

• Recommendations for future research - Effectiveness and acceptability of parenta... Recommendations for future research - Effectiveness and acceptability of parental financial incentives and quasi-mandatory schemes for increasing uptake of vaccinations in preschool children: systematic review, qualitative study and discrete choice experiment

Your browsing activity is empty.

Activity recording is turned off.

Turn recording back on

Connect with NLM

National Library of Medicine 8600 Rockville Pike Bethesda, MD 20894

Web Policies FOIA HHS Vulnerability Disclosure

Help Accessibility Careers