How To Make Recommendation in Case Study (With Examples)

How To Make Recommendation in Case Study (With Examples)

After analyzing your case study’s problem and suggesting possible courses of action , you’re now ready to conclude it on a high note. 

But first, you need to write your recommendation to address the problem. In this article, we will guide you on how to make a recommendation in a case study. 

Table of Contents

What is recommendation in case study, what is the purpose of recommendation in the case study, 1. review your case study’s problem, 2. assess your case study’s alternative courses of action, 3. pick your case study’s best alternative course of action, 4. explain in detail why you recommend your preferred course of action, examples of recommendations in case study, tips and warnings.

example of recommendation in case study 1

The Recommendation details your most preferred solution for your case study’s problem.

After identifying and analyzing the problem, your next step is to suggest potential solutions. You did this in the Alternative Courses of Action (ACA) section. Once you’re done writing your ACAs, you need to pick which among these ACAs is the best. The chosen course of action will be the one you’re writing in the recommendation section. 

The Recommendation portion also provides a thorough justification for selecting your most preferred solution. 

Notice how a recommendation in a case study differs from a recommendation in a research paper . In the latter, the recommendation tells your reader some potential studies that can be performed in the future to support your findings or to explore factors that you’re unable to cover. 

example of recommendation in case study 2

Your main goal in writing a case study is not only to understand the case at hand but also to think of a feasible solution. However, there are multiple ways to approach an issue. Since it’s impossible to implement all these solutions at once, you only need to pick the best one. 

The Recommendation portion tells the readers which among the potential solutions is best to implement given the constraints of an organization or business. This section allows you to introduce, defend, and explain this optimal solution. 

How To Write Recommendation in Case Study

example of recommendation in case study 3

You cannot recommend a solution if you are unable to grasp your case study’s issue. Make sure that you’re aware of the problem as well as the viewpoint from which you want to analyze it . 

example of recommendation in case study 4

Once you’ve fully grasped your case study’s problem, it’s time to suggest some feasible solutions to address it. A separate section of your manuscript called the Alternative Courses of Action (ACA) is dedicated to discussing these potential solutions. 

Afterward, you need to evaluate each ACA by identifying its respective advantages and disadvantages. 

example of recommendation in case study 5

After evaluating each proposed ACA, pick the one you’ll recommend to address the problem. All alternatives have their pros and cons so you must use your discretion in picking the best among these ACAs.

To help you decide which ACA to pick, here are some factors to consider:

  • Realistic : The organization must have sufficient knowledge, expertise, resources, and manpower to execute the recommended solution. 
  • Economical: The recommended solution must be cost-effective.
  • Legal: The recommended solution must adhere to applicable laws.
  • Ethical: The recommended solution must not have moral repercussions. 
  • Timely: The recommended solution can be executed within the expected timeframe. 

You may also use a decision matrix to assist you in picking the best ACA 1 .  This matrix allows you to rank the ACAs based on your criteria. Please refer to our examples in the next section for an example of a Recommendation formed using a decision matrix. 

example of recommendation in case study 6

Provide your justifications for why you recommend your preferred solution. You can also explain why other alternatives are not chosen 2 .  

example of recommendation in case study 7

To help you understand how to make recommendations in a case study, let’s take a look at some examples below.

Case Study Problem : Lemongate Hotel is facing an overwhelming increase in the number of reservations due to a sudden implementation of a Local Government policy that boosts the city’s tourism. Although Lemongate Hotel has a sufficient area to accommodate the influx of tourists, the management is wary of the potential decline in the hotel’s quality of service while striving to meet the sudden increase in reservations. 

Alternative Courses of Action:

  • ACA 1: Relax hiring qualifications to employ more hotel employees to ensure that sufficient human resources can provide quality hotel service
  • ACA 2: Increase hotel reservation fees and other costs as a response to the influx of tourists demanding hotel accommodation
  • ACA 3: Reduce privileges and hotel services enjoyed by each customer so that hotel employees will not be overwhelmed by the increase in accommodations.

Recommendation: 

Upon analysis of the problem, it is recommended to implement ACA 1. Among all suggested ACAs, this option is the easiest to execute with the minimal cost required. It will not also impact potential profits and customers’ satisfaction with hotel service.

Meanwhile, implementing ACA 2 might discourage customers from making reservations due to higher fees and look for other hotels as substitutes. It is also not recommended to do ACA 3 because reducing hotel services and privileges offered to customers might harm the hotel’s public reputation in the long run. 

The first paragraph of our sample recommendation specifies what ACA is best to implement and why.

Meanwhile, the succeeding paragraphs explain that ACA 2 and ACA 3 are not optimal solutions due to some of their limitations and potential negative impacts on the organization. 

Example 2 (with Decision Matrix)

Case Study: Last week, Pristine Footwear released its newest sneakers model for women – “Flightless.” However, the management noticed that “Flightless” had a mediocre sales performance in the previous week. For this reason, “Flightless” might be pulled out in the next few months.  The management must decide on the fate of “Flightless” with Pristine Footwear’s financial performance in mind. 

  • ACA 1: Revamp “Flightless” marketing by hiring celebrities/social media influencers to promote the product
  • ACA 2: Improve the “Flightless” current model by tweaking some features to fit current style trends
  • ACA 3: Sell “Flightless” at a lower price to encourage more customers
  • ACA 4: Stop production of “Flightless” after a couple of weeks to cut losses

Decision Matrix

Recommendation

Based on the decision matrix above 3 , the best course of action that Pristine Wear, Inc. must employ is ACA 3 or selling “Flightless” shoes at lower prices to encourage more customers. This solution can be implemented immediately without the need for an excessive amount of financial resources. Since lower prices entice customers to purchase more, “Flightless” sales might perform better given a reduction in its price.

In this example, the recommendation was formed with the help of a decision matrix. Each ACA was given a score of between 1 – 4 for each criterion. Note that the criterion used depends on the priorities of an organization, so there’s no standardized way to make this matrix. 

Meanwhile, the recommendation we’ve made here consists of only one paragraph. Although the matrix already revealed that ACA 3 tops the selection, we still provided a clear explanation of why it is the best. 

  • Recommend with persuasion 4 . You may use data and statistics to back up your claim. Another option is to show that your preferred solution fits your theoretical knowledge about the case. For instance, if your recommendation involves reducing prices to entice customers to buy higher quantities of your products, you may invoke the “law of demand” 5 as a theoretical foundation of your recommendation. 
  • Be prepared to make an implementation plan. Some case study formats require an implementation plan integrated with your recommendation. Basically, the implementation plan provides a thorough guide on how to execute your chosen solution (e.g., a step-by-step plan with a schedule).
  • Manalili, K. (2021 – 2022). Selection of Best Applicant (Unpublished master’s thesis). Bulacan Agricultural State College. Retrieved September 23, 2022, from https://www.studocu.com/ph/document/bulacan-agricultural-state-college/business-administration/case-study-human-rights/19062233.
  • How to Analyze a Case Study. (n.d.). Retrieved September 23, 2022, from https://wps.prenhall.com/bp_laudon_essbus_7/48/12303/3149605.cw/content/index.html
  • Nguyen, C. (2022, April 13). How to Use a Decision Matrix to Assist Business Decision Making. Retrieved September 23, 2022, from https://venngage.com/blog/decision-matrix/
  • Case Study Analysis: Examples + How-to Guide & Writing Tips. (n.d.). Retrieved September 23, 2022, from https://custom-writing.org/blog/great-case-study-analysis
  • Hayes, A. (2022, January O8). Law of demand. Retrieved September 23, 2022, from https://www.investopedia.com/terms/l/lawofdemand.asp

Written by Jewel Kyle Fabula

in Career and Education , Juander How

Last Updated September 23, 2022 07:23 PM

conclusion and recommendation in case study example

Jewel Kyle Fabula

Jewel Kyle Fabula is a Bachelor of Science in Economics student at the University of the Philippines Diliman. His passion for learning mathematics developed as he competed in some mathematics competitions during his Junior High School years. He loves cats, playing video games, and listening to music.

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conclusion and recommendation in case study example

How to write the conclusion of your case study

You worked on an amazing UX project. You documented every detail and deliverable and when the time came, you began to write a UX case study about it. In the case study, you highlighted how you worked through a Design Thinking process to get to the end result; so, can you stop there and now move on to the next thing? Well, no! There’s just one more bit left to finish up and make the perfect case study. So, get ready; we will now explore how you can write the perfect conclusion to wrap it all up and leave a lasting great impression.

Every start has an end – we’re not just repeating the famous quote here, because for case studies, a proper end is your last and final chance to leave a lasting great (at the very least, good) impression with whoever is reading your work (typically, recruiters!). Many junior UX designers often forget about the conclusion part of the case study, but this is a costly mistake to make. A well-written case study must end with an appropriate final section, in which you should summarize the key takeaways that you want others to remember about you and your work. Let’s see why.

Last impressions are just as important as first ones

We’ll go to some length here to convince you about the importance of last impressions, especially as we can understand the reason behind not wanting to pay very much attention to the end of your case study, after all the hard work you put into writing the process section. You are tired, and anyone who’s read your work should already have a good idea about your skills, anyway. Surely—you could be forgiven for thinking, at least—all that awesome material you put in the start and middle sections must have built up the momentum to take your work into orbit and make the recruiter’s last impression of you a lasting—and very good—one, and all you need to do now is take your leave. However, psychologist Saul McLeod (2008) explains how early work by experimental psychology pioneers Atkinson & Shriffin (1968) demonstrated that when humans are presented with information, they tend to remember the first and last elements and are more likely to forget the middle ones.

This is known as the “ serial position effect ” (more technically, the tendency to remember the first elements is known as the “ primacy effect ”, while the tendency to remember the last elements is known as the “ recency effect ”). Further work in human experiences discovered that the last few things we see or hear at the end of an experience can generate the most powerful memories that come back to us when we come across a situation or when we think about it. For example, let’s say you stayed in a hotel room that left a bit to be desired. Maybe the room was a little cramped, or the towels were not so soft. But if the receptionist, as you leave, shakes your hand warmly, smiles and thanks you sincerely for your custom, and goes out of his way to help you with your luggage, or to get you a taxi, you will remember that person’s kind demeanor more than you will remember the fact that the room facilities could be improved.

A good ending to your case study can help people forget some of the not-so-good points about your case study middle. For example, if you missed out a few crucial details but can demonstrate some truly interesting takeaways, they can always just ask you about these in an interview. Inversely, a bad ending leaves the recruiter with some doubt that will linger. Did this person learn nothing interesting from all this work? Did their work have no impact at all? Did they even write the case study themselves? A bad last impression can certainly undo much of the hard work you’ve put into writing the complicated middle part of your case study.

What to put in your case study conclusions

A case study ending is your opportunity to bring some closure to the story that you are writing. So, you can use it to mention the status of the project (e.g., is it ongoing or has it ended?) and then to demonstrate the impact that your work has had. By presenting some quantifiable results (e.g., data from end evaluations, analytics, key performance indicators ), you can demonstrate this impact. You can also discuss what you learned from this project, making you wiser than the next applicant – for example, something about a special category of users that the company might be interested in developing products for, or something that is cutting-edge and that advances the frontiers of science or practice.

As you can see, there are a few good ways in which you can end your case study. Next, we will outline four options that can be part of your ending: lessons learned, the impact of the project, reflections, and acknowledgements.

Lessons learned

A recruiter wants to see how you improve yourself by learning from the projects you work on. You can discuss interesting insights that you learned from user research or the evaluation of your designs – for example, surprising behaviors that you found out about the technology use in a group of users who are not typically considered to be big proponents of technology (e.g., older adults), or, perhaps, the reasons a particular design pattern didn’t work as well as expected under the context of your project.

Another thing you can discuss is your opinion on what the most difficult challenge of the project was, and comment on how you managed to overcome it. You can also discuss here things that you found out about yourself as a professional – for example, that you enjoyed taking on a UX role that you didn’t have previous experience with, or that you were able to overcome some personal limitations or build on your existing skills in a new way.

Impact of the project

Showing impact is always good. How did you measure the impact of your work? By using analytics, evaluation results, and even testimonials from your customers or users, or even your development or marketing team, you can demonstrate that your methodical approach to work brought about some positive change. Use before-after comparison data to demonstrate the extent of your impact. Verbatim positive quotes from your users or other project stakeholders are worth their weight (or rather, sentence length) in gold. Don’t go overboard, but mix and match the best evidence for the quality of your work to keep the end section brief and to the point.

conclusion and recommendation in case study example

Copyright holder: Andreas Komninos, Interaction Design Foundation. Copyright terms and license: CC BY-SA 3.0

User reviews from app stores are a great source of obtaining testimonials to include in your case studies. Overall app ratings and download volumes are also great bits of information to show impact.

conclusion and recommendation in case study example

An excerpt from a case study ending section. Here, text and accompanying charts are used to demonstrate the impact of the work done by the UX professional.

Reflections on your experiences

You can include some information that shows you have a clear understanding of how further work can build on the success of what you’ve already done. This demonstrates forward thinking and exploratory desire. Something else you can reflect on is your choices during the project. In every project, there might be things you could do differently or improve upon. But be aware that the natural question that follows such statements is this: “Well, so why haven’t you done it?”

Don’t shoot yourself in the foot by listing all the things you wish you could have done, but focus on what you’ve actually done and lay out future directions. For example, if you’ve done the user research in an ongoing project, don’t say, “ After all this user research, it would have been great to progress to a prototype, but it’s not yet done ”; instead, say, “ This user research is now enabling developers to quickly progress to the prototyping stage. ”

Acknowledgments

The end of the case study section is where you should put in your acknowledgments to any other members of your team, if this wasn’t a personal project. Your goal by doing so is to highlight your team spirit and humility in recognizing that great projects are most typically the result of collaboration . Be careful here, because it’s easy to make the waters muddy by not being explicit about what YOU did. So, for example, don’t write something like “ I couldn’t have done it without John X. and Jane Y. ”, but instead say this: “ My user research and prototype design fed into the development work carried out by John X. User testing was carried out by Jane Y., whose findings informed further re-design that I did on the prototypes. ”

What is a good length for a UX case study ending?

UX case studies must be kept short, and, when considering the length of your beginning, process and conclusion sections, it’s the beginning and the conclusion sections that should be the shortest of all. In some case studies, you can keep the ending to two or three short phrases. Other, longer case studies about more complex projects may require a slightly longer section.

Remember, though, that the end section is your chance for a last, short but impactful impression. If the hotel receptionist from our early example started to say goodbye and then went on and on to ask you about your experience, sharing with you the comments of other clients, or started talking to you about where you are going next, and why, and maybe if he had been there himself, started to tell you all about where to go and what to see, well… you get the point. Keep it short, sincere and focused. And certainly, don’t try to make the project sound more important than it was. Recruiters are not stupid – they’ve been there and done that, so they know.

Putting it all together

In the example below, we will show how you can address the points above using text. We are going to focus on the three main questions here, so you can see an example of this in action, for a longer case study.

conclusion and recommendation in case study example

An example ending section for a longer case study, addressing all aspects: Lessons, impact, reflection and acknowledgments.

Here is how we might structure the text for a shorter version of the same case study, focusing on the bare essentials:

conclusion and recommendation in case study example

An example ending section for a shorter case study, addressing the most critical aspects: Lessons, impact and reflection. Acknowledgments are being sacrificed for the sake of brevity here, but perhaps that’s OK – you might mention it in the middle part of the case study.

The Take Away

The end part of your case study needs as much care and attention as the rest of it does. You shouldn’t neglect it just because it’s the last thing in the case study. It’s not hard work if you know the basics, and here, we’ve given you the pointers you need to ensure that you don’t miss out anything important. The end part of the case study should leave your recruiters with a good (hopefully, very good) last impression of you and your work, so give it the thorough consideration it needs, to ensure it doesn’t undo all the hard work you’ve put into the case study.

References & Where to Learn More

Copyright holder: Andrew Hurley, Flickr. Copyright terms and license: CC BY-SA 2.0

Atkinson, R. C., & Shiffrin, R. M. (1968). Chapter: Human memory : A proposed system and its control processes. In Spence, K. W., & Spence, J. T. The psychology of learning and motivation (Volume 2). New York: Academic Press. pp. 89–195.

McLeod, S. (2008). Serial Position Effect

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Writing the parts of scientific reports

22 Writing the conclusion & recommendations

There are probably some overlaps between the Conclusion and the Discussion section. Nevertheless, this section gives you the opportunity to highlight the most important points in your report, and is sometimes the only section read. Think about what your research/ study has achieved, and the most important findings and ideas you want the reader to know. As all studies have limitations also think about what you were not able to cover (this shows that you are able to evaluate your own work objectively).

Possible structure of this section:

conclusion and recommendation in case study example

Use present perfect to sum up/ evaluate:

This study has explored/ has attempted …

Use past tense to state what your aim was and to refer to actions you carried out:

  • This study was intended to analyse …
  • The aim of this study was to …

Use present tense to evaluate your study and to state the generalizations and implications that you draw from your findings.

  • The results add to the knowledge of …
  • These findings s uggest that …

You can either use present tense or past tense to summarize your results.

  • The findings reveal …
  • It was found that …

Achievements of this study (positive)

  • This study provides evidence that …
  • This work has contributed to a number of key issues in the field such as …

Limitations of the study (negative)

  • Several limitations should be noted. First …

Combine positive and negative remarks to give a balanced assessment:

  • Although this research is somewhat limited in scope, its findings can provide a basis for future studies.
  • Despite the limitations, findings from the present study can help us understand …

Use more cautious language (modal verbs may, can, could)

  • There are a number of possible extensions of this research …
  • The findings suggest the possibility for future research on …
  • These results may be important for future studies on …
  • Examining a wider context could/ would lead …

Or indicate that future research is needed

  • There is still a need for future research to determine …
  • Further studies should be undertaken to discover…
  • It would be worthwhile to investigate …

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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

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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.

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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 .

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conclusion and recommendation in case study example

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!

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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

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George, T. & McCombes, S. (2023, November 20). How to Write a Thesis or Dissertation Conclusion. Scribbr. Retrieved February 22, 2024, from https://www.scribbr.com/dissertation/write-conclusion/

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How to Write a Conclusion for Research Papers (with Examples)

How to Write a Conclusion for Research Papers (with Examples)

The conclusion of a research paper is a crucial section that plays a significant role in the overall impact and effectiveness of your research paper. However, this is also the section that typically receives less attention compared to the introduction and the body of the paper. The conclusion serves to provide a concise summary of the key findings, their significance, their implications, and a sense of closure to the study. Discussing how can the findings be applied in real-world scenarios or inform policy, practice, or decision-making is especially valuable to practitioners and policymakers. The research paper conclusion also provides researchers with clear insights and valuable information for their own work, which they can then build on and contribute to the advancement of knowledge in the field.

The research paper conclusion should explain the significance of your findings within the broader context of your field. It restates how your results contribute to the existing body of knowledge and whether they confirm or challenge existing theories or hypotheses. Also, by identifying unanswered questions or areas requiring further investigation, your awareness of the broader research landscape can be demonstrated.

Remember to tailor the research paper conclusion to the specific needs and interests of your intended audience, which may include researchers, practitioners, policymakers, or a combination of these.

Table of Contents

What is a conclusion in a research paper, summarizing conclusion, editorial conclusion, externalizing conclusion, importance of a good research paper conclusion, how to write a conclusion for your research paper, research paper conclusion examples, frequently asked questions.

A conclusion in a research paper is the final section where you summarize and wrap up your research, presenting the key findings and insights derived from your study. The research paper conclusion is not the place to introduce new information or data that was not discussed in the main body of the paper. When working on how to conclude a research paper, remember to stick to summarizing and interpreting existing content. The research paper conclusion serves the following purposes: 1

  • Warn readers of the possible consequences of not attending to the problem.
  • Recommend specific course(s) of action.
  • Restate key ideas to drive home the ultimate point of your research paper.
  • Provide a “take-home” message that you want the readers to remember about your study.

conclusion and recommendation in case study example

Types of conclusions for research papers

In research papers, the conclusion provides closure to the reader. The type of research paper conclusion you choose depends on the nature of your study, your goals, and your target audience. I provide you with three common types of conclusions:

A summarizing conclusion is the most common type of conclusion in research papers. It involves summarizing the main points, reiterating the research question, and restating the significance of the findings. This common type of research paper conclusion is used across different disciplines.

An editorial conclusion is less common but can be used in research papers that are focused on proposing or advocating for a particular viewpoint or policy. It involves presenting a strong editorial or opinion based on the research findings and offering recommendations or calls to action.

An externalizing conclusion is a type of conclusion that extends the research beyond the scope of the paper by suggesting potential future research directions or discussing the broader implications of the findings. This type of conclusion is often used in more theoretical or exploratory research papers.

The conclusion in a research paper serves several important purposes:

  • Offers Implications and Recommendations : Your research paper conclusion is an excellent place to discuss the broader implications of your research and suggest potential areas for further study. It’s also an opportunity to offer practical recommendations based on your findings.
  • Provides Closure : A good research paper conclusion provides a sense of closure to your paper. It should leave the reader with a feeling that they have reached the end of a well-structured and thought-provoking research project.
  • Leaves a Lasting Impression : Writing a well-crafted research paper conclusion leaves a lasting impression on your readers. It’s your final opportunity to leave them with a new idea, a call to action, or a memorable quote.

conclusion and recommendation in case study example

Writing a strong conclusion for your research paper is essential to leave a lasting impression on your readers. Here’s a step-by-step process to help you create and know what to put in the conclusion of a research paper: 2

  • Research Statement : Begin your research paper conclusion by restating your research statement. This reminds the reader of the main point you’ve been trying to prove throughout your paper. Keep it concise and clear.
  • Key Points : Summarize the main arguments and key points you’ve made in your paper. Avoid introducing new information in the research paper conclusion. Instead, provide a concise overview of what you’ve discussed in the body of your paper.
  • Address the Research Questions : If your research paper is based on specific research questions or hypotheses, briefly address whether you’ve answered them or achieved your research goals. Discuss the significance of your findings in this context.
  • Significance : Highlight the importance of your research and its relevance in the broader context. Explain why your findings matter and how they contribute to the existing knowledge in your field.
  • Implications : Explore the practical or theoretical implications of your research. How might your findings impact future research, policy, or real-world applications? Consider the “so what?” question.
  • Future Research : Offer suggestions for future research in your area. What questions or aspects remain unanswered or warrant further investigation? This shows that your work opens the door for future exploration.
  • Closing Thought : Conclude your research paper conclusion with a thought-provoking or memorable statement. This can leave a lasting impression on your readers and wrap up your paper effectively. Avoid introducing new information or arguments here.
  • Proofread and Revise : Carefully proofread your conclusion for grammar, spelling, and clarity. Ensure that your ideas flow smoothly and that your conclusion is coherent and well-structured.

Remember that a well-crafted research paper conclusion is a reflection of the strength of your research and your ability to communicate its significance effectively. It should leave a lasting impression on your readers and tie together all the threads of your paper. Now you know how to start the conclusion of a research paper and what elements to include to make it impactful, let’s look at a research paper conclusion sample.

conclusion and recommendation in case study example

The research paper conclusion is a crucial part of your paper as it provides the final opportunity to leave a strong impression on your readers. In the research paper conclusion, summarize the main points of your research paper by restating your research statement, highlighting the most important findings, addressing the research questions or objectives, explaining the broader context of the study, discussing the significance of your findings, providing recommendations if applicable, and emphasizing the takeaway message. The main purpose of the conclusion is to remind the reader of the main point or argument of your paper and to provide a clear and concise summary of the key findings and their implications. All these elements should feature on your list of what to put in the conclusion of a research paper to create a strong final statement for your work.

A strong conclusion is a critical component of a research paper, as it provides an opportunity to wrap up your arguments, reiterate your main points, and leave a lasting impression on your readers. Here are the key elements of a strong research paper conclusion: 1. Conciseness : A research paper conclusion should be concise and to the point. It should not introduce new information or ideas that were not discussed in the body of the paper. 2. Summarization : The research paper conclusion should be comprehensive enough to give the reader a clear understanding of the research’s main contributions. 3 . Relevance : Ensure that the information included in the research paper conclusion is directly relevant to the research paper’s main topic and objectives; avoid unnecessary details. 4 . Connection to the Introduction : A well-structured research paper conclusion often revisits the key points made in the introduction and shows how the research has addressed the initial questions or objectives. 5. Emphasis : Highlight the significance and implications of your research. Why is your study important? What are the broader implications or applications of your findings? 6 . Call to Action : Include a call to action or a recommendation for future research or action based on your findings.

The length of a research paper conclusion can vary depending on several factors, including the overall length of the paper, the complexity of the research, and the specific journal requirements. While there is no strict rule for the length of a conclusion, but it’s generally advisable to keep it relatively short. A typical research paper conclusion might be around 5-10% of the paper’s total length. For example, if your paper is 10 pages long, the conclusion might be roughly half a page to one page in length.

In general, you do not need to include citations in the research paper conclusion. Citations are typically reserved for the body of the paper to support your arguments and provide evidence for your claims. However, there may be some exceptions to this rule: 1. If you are drawing a direct quote or paraphrasing a specific source in your research paper conclusion, you should include a citation to give proper credit to the original author. 2. If your conclusion refers to or discusses specific research, data, or sources that are crucial to the overall argument, citations can be included to reinforce your conclusion’s validity.

The conclusion of a research paper serves several important purposes: 1. Summarize the Key Points 2. Reinforce the Main Argument 3. Provide Closure 4. Offer Insights or Implications 5. Engage the Reader. 6. Reflect on Limitations

Remember that the primary purpose of the research paper conclusion is to leave a lasting impression on the reader, reinforcing the key points and providing closure to your research. It’s often the last part of the paper that the reader will see, so it should be strong and well-crafted.

  • Makar, G., Foltz, C., Lendner, M., & Vaccaro, A. R. (2018). How to write effective discussion and conclusion sections. Clinical spine surgery, 31(8), 345-346.
  • Bunton, D. (2005). The structure of PhD conclusion chapters.  Journal of English for academic purposes ,  4 (3), 207-224.

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Case Study Conclusion

The end is sometimes the most visible piece of academic writing. The conclusion of the case study is an ignored portion. Several students make case study research papers every year on the demand of their tutors. But, very few of them realize the importance of every segment of it. From the introduction to the case study conclusion, every single thing matters. As it’s a matter of your future academic success, it is equally beneficial for the students to craft valuable endings for their case studies.

Students may question themselves about, what makes a brilliant conclusion? Well, there are plenty of rules that should be applied while making one. For example, there are a few things to be kept in mind for writing the introductions. Similarly, extensive research is required to make an impactful conclusion for a case study.

Importance OF A Conclusion In The Case Study For A Student  

It’s a years-long pattern that the last part of any content gets neglected. The reasons are quite clear, either you lose interest in your topic, or you want to finish it in a hurry. But whatever the reason it is, it’s not ideal to ignore the end of your case study solutions writing. Various elements define the importance of the concluding part.

The ending is the most read portion of the content as it summarizes all the vital points of the introduction of your case study. So if you have not paid much attention to your conclusions, there are high chance that your case study will not look impressive.

The Common Sample OF Conclusion And Recommendation In The Case Study 

Students can feasibly go through our site to get samples of the conclusion of a case study. However, the most common things you can find in a case study sample are the proper solutions to your argued problems. Not to forget the requirements of the deep analysis on how to overcome them.

A good case study is nothing without the relevant samples and recommendations. Hence, it’s the most crucial part of the writings to list the proper recommendations for your tutors. Students are advised that all of their suggestions must include specific reports of all the emerging limitations. They can address all of the issues with the possible solutions to them that would be helpful for future work.

It doesn’t matter if you are concluding a long report or a short one. The recommendations should be listed in pointers to avoid any confusion and add more to the clarity.

What Case Study Conclusions Should Look Like?

Your conclusion is the most integral part of your research papers. If a good conclusion has been provided to the case study, there are high chances that your not-so-good point in the middle of the starting sections gets blurred. The conclusion part of the case study that brings closure to your story is the reformed way. All of your researched data can have more impact if the ending part of your case study states the solutions to the key issues.

Example OF The Case Studies Conclusion   

Students can list what they have learned from this particular topic in their conclusion. It can make you wiser in comparison to the next applicant. For example, you can discuss any special category of the users related to the company you are conducting a case study on. You can highlight the new products which they are interested in launching. You can also discuss something that is cutting-edge and advances the boundaries of practice or science.

As you can see, there are various ways by which you can create a lasting impact on your conclusions.

Get Our Help To Write An Impressive Conclusion For Your Case Study

Writing an excellent case study is not an easy task to accomplish. Moreover, its different sections from the beginning to the conclusion demand immense intensity and research. But, we assure our students that our case study writers can deliver quality case studies to you. They are experts in creating unique content. Hence, you can freely rely on our case study services to attain the utmost satisfaction.

How Do You Write A Conclusion?

The conclusion of a case study comprises of the following important steps:

  • Look out for the logical connections.
  • Make sure your conclusion has a direct link to your introduction.
  • Keep the basic logic in mind.
  • Encourage the reader to draw their own conclusions.
  • Provide recommendations.
  • Conclusions should be definite.
  • The recommendations should directly adhere to your conclusion.

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  • How to Write a Thesis or Dissertation Conclusion

How to Write a Dissertation Conclusion | Checklist and Examples

Published on 9 September 2022 by Tegan George and Shona McCombes. Revised on 10 October 2022.

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
  • Summarise and reflect on your research process
  • Make recommendations for future work on your topic
  • Show what new knowledge you have contributed to your field
  • Wrap up your thesis or dissertation

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Table of contents

Discussion vs. conclusion, how long should your conclusion be, step 1: answer your research question, step 2: summarise and reflect on your research, step 3: make future recommendations, step 4: emphasise your contributions to your field, step 5: wrap up your thesis or dissertation, full conclusion example, conclusion checklist, 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.

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

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.

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:

  • 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

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George, T. & McCombes, S. (2022, October 10). How to Write a Dissertation Conclusion | Checklist and Examples. Scribbr. Retrieved 22 February 2024, from https://www.scribbr.co.uk/thesis-dissertation/conclusion/

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National Academies Press: OpenBook

Conducting Biosocial Surveys: Collecting, Storing, Accessing, and Protecting Biospecimens and Biodata (2010)

Chapter: 5 findings, conclusions, and recommendations, 5 findings, conclusions, and recommendations.

A s the preceding chapters have made clear, incorporating biological specimens into social science surveys holds great scientific potential, but also adds a variety of complications to the tasks of both individual researchers and institutions. These complications arise in a number of areas, including collecting, storing, using, and distributing biospecimens; sharing data while protecting privacy; obtaining informed consent from participants; and engaging with Institutional Review Boards (IRBs). Any effort to make such research easier and more effective will need to address the issues in these areas.

In considering its recommendations, the panel found it useful to think of two categories: (1) recommendations that apply to individual investigators, and (2) recommendations that are addressed to the National Institute on Aging (NIA) or other institutions, particularly funding agencies. Researchers who wish to collect biological specimens with social science data will need to develop new skills in a variety of areas, such as the logistics of specimen storage and management, the development of more diverse informed consent forms, and ways of dealing with the disclosure risks associated with sharing biogenetic data. At the same time, NIA and other funding agencies must provide researchers the tools they need to succeed. These tools include such things as biorepositories for maintaining and distributing specimens, better guidance on informed consent policies, and better ways to share data without risking confidentiality.

TAKING ADVANTAGE OF EXISTING EXPERTISE

Although working with biological specimens will be new and unfamiliar to many social scientists, it is an area in which biomedical researchers have a great deal of expertise and experience. Many existing documents describe recommended procedures and laboratory practices for the handling of biospecimens. These documents provide an excellent starting point for any social scientist who is interested in adding biospecimens to survey research.

Recommendation 1: Social scientists who are planning to add biological specimens to their survey research should familiarize themselves with existing best practices for the collection, storage, use, and distribution of biospecimens. First and foremost, the design of the protocol for collec tion must ensure the safety of both participants and survey staff (data and specimen collectors and handlers).

Although existing best-practice documents were not developed with social science surveys in mind, their guidelines have been field-tested and approved by numerous IRBs and ethical oversight committees. The most useful best-practice documents are updated frequently to reflect growing knowledge and changing opinions about the best ways to collect, store, use, and distribute biological specimens. At the same time, however, many issues arising from the inclusion of biospecimens in social science surveys are not fully addressed in the best-practice documents intended for biomedical researchers. For guidance on these issues, it will be necessary to seek out information aimed more specifically at researchers at the intersection of social science and biomedicine.

COLLECTING, STORING, USING, AND DISTRIBUTING BIOSPECIMENS

As described in Chapter 2 , the collection, storage, use, and distribution of biospecimens and biodata are tasks that are likely to be unfamiliar to many social scientists and that raise a number of issues with which even specialists are still grappling. For example, which biospecimens in a repository should be shared, given that in most cases the amount of each specimen is limited? And given that the available technology for cost-efficient analysis of biospecimens, particularly genetic analysis, is rapidly improving, how much of any specimen should be used for immediate research and analysis, and how much should be stored for analysis at a later date? Collecting, storing, using, and distributing biological specimens also present significant practical and financial challenges for social scientists. Many of the questions they must address, such as exactly what should be held, where it should be held, and what should be shared or distributed, have not yet been resolved.

Developing Data Sharing Plans

An important decision concerns who has access to any leftover biospecimens. This is a problem more for biospecimens than for biodata because in most cases, biospecimens can be exhausted. Should access be determined according to the principle of first funded, first served? Should there be a formal application process for reviewing the scientific merits of a particular investigation? For studies that involve international collaboration, should foreign investigators have access? And how exactly should these decisions be made? Recognizing that some proposed analyses may lie beyond the competence of the original investigators, as well as the possibility that principal investigators may have a conflict of interest in deciding how to use any remaining biospecimens, one option is for a principal investigator to assemble a small scientific committee to judge the merits of each application, including the relevance of the proposed study to the parent study and the capacities of the investigators. Such committees should publish their review criteria to help prospective applicants. A potential problem with such an approach, however, is that many projects may not have adequate funding to carry out such tasks.

Recommendation 2: Early in the planning process, principal investigators who will be collecting biospecimens as part of a social science survey should develop a complete data sharing plan.

This plan should spell out the criteria for allowing other researchers to use (and therefore deplete) the available stock of biospecimens, as well as to gain access to any data derived therefrom. To avoid any appearance of self-interest, a project might empower an external advisory board to make decisions about access to its data. The data sharing plan should also include provisions for the storage and retrieval of biospecimens and clarify how the succession of responsibility for and control of the biospecimens will be handled at the conclusion of the project.

Recommendation 3: NIA (or preferably the National Institutes of Health [NIH]) should publish guidelines for principal investigators containing a list of points that need to be considered for an acceptable data sharing plan. In addition to staff review, Scientific Review Panels should read and comment on all proposed data sharing plans. In much the same way as an unacceptable human subjects plan, an inadequate data sharing plan should hold up an otherwise acceptable proposal.

Supporting Social Scientists in the Storage of Biospecimens

The panel believes that many social scientists who decide to add the collection of biospecimens to their surveys may be ill equipped to provide for the storage and distribution of the specimens.

Conclusion: The issues related to the storage and distribution of biospecimens are too complex and involve too many hidden costs to assume that social scientists without suitable knowledge, experience, and resources can handle them without assistance.

Investigators should therefore have the option of delegating the storage and distribution of biospecimens collected as part of social science surveys to a centralized biorepository. Depending on the circumstances, a project might choose to utilize such a facility for immediate use, long-term or archival storage, or not at all.

Recommendation 4: NIA and other relevant funding agencies should support at least one central facility for the storage and distribution of biospecimens collected as part of the research they support.

PROTECTING PRIVACY AND CONFIDENTIALITY: SHARING DIGITAL REPRESENTATIONS OF BIOLOGICAL AND SOCIAL DATA

Several different types of data must be kept confidential: survey data, data derived from biospecimens, and all administrative and operational data. In the discussion of protecting confidentiality and privacy, this report has focused on biodata, but the panel believes it is important to protect all the data collected from survey participants. For many participants, for example, data on wealth, earnings, or sexual behavior can be as or more sensitive than genetic data.

Conclusion: Although biodata tend to receive more attention in discussions of privacy and confidentiality, social science and operational data can be sensitive in their own right and deserve similar attention in such discussions.

Protecting the participants in a social science survey that collects biospecimens requires securing the data, but data are most valuable when they are made available to researchers as widely as possible. Thus there is an inherent tension between the desire to protect the privacy of the participants and the desire to derive as much scientific value from the data as possible, particularly since the costs of data collection and analysis are so high. The following recommendations regarding confidentiality are made in the spirit of balancing these equally important needs.

Genomic data present a particular challenge. Several researchers have demonstrated that it is possible to identify individuals with even modest amounts of such data. When combined with social science data, genomic data may pose an even greater risk to confidentiality. It is difficult to know how much or which genomic data, when combined with social science data, could become critical identifiers in the future. Although the problem is most significant with genomic data, similar challenges can arise with other kinds of data derived from biospecimens.

Conclusion: Unrestricted distribution of genetic and other biodata risks violating promises of confidentiality made to research participants.

There are two basic approaches to protecting confidentiality: restricting data and restricting access. Restricting data—for example, by stripping individual and spatial identifiers and modifying the data to make it difficult or impossible to trace them back to their source—usually makes it possible to release social science data widely. In the case of biodata, however, there is no answer to how little data is required to make a participant uniquely identifiable. Consequently, any release of biodata must be carefully managed to protect confidentiality.

Recommendation 5: No individual-level data containing uniquely identify ing variables, such as genomic data, should be publicly released without explicit informed consent.

Recommendation 6: Genomic data and other individual-level data con taining uniquely identifying variables that are stored or in active use by investigators on their institutional or personal computers should be encrypted at all times.

Even if specific identifying variables, such as names and addresses, are stripped from data, it is still often possible to identify the individuals associated with the data by other means, such as using the variables that remain (age, sex, marital status, family income, etc.) to zero in on possible candidates. In the case of biodata that do not uniquely identify individuals and can change with time, such as blood pressure and physical measurements, it may be possible to share the data with no more protection than stripping identifying variables. Even these data, however, if known to intruders, can increase identification disclosure risk when combined with enough other data. With sufficient characteristics to match, intruders can uniquely identify individuals in shared data if given access to another data source that contains the same information plus identifiers.

Conclusion: Even nonunique biodata, if combined with social science data, may pose a serious risk of reidentification.

In the case of high-dimensional genomic data, standard disclosure limitation techniques, such as data perturbation, are not effective with respect to preserving the utility of the data because they involve such extreme alterations that they would severely distort analyses aimed at determining gene–gene and gene–environment interactions. Standard disclosure limitation methods could be used to generate public-use data sets that would enable low-dimensional analyses involving genes, for example, one gene at a time. However, with several such public releases, it may be possible for a key match to be used to construct a data set with higher-dimensional genomic data.

Conclusion: At present, no data restriction strategy has been demonstrated to protect confidentiality while preserving the usefulness of the data for drawing inferences involving high-dimensional interactions among genomic and social science variables, which are increasingly the target of research. Providing public-use genomic data requires such intense data masking to protect confidentiality that it would distort the high-dimensional analyses that could result in ground-breaking research progress.

Recommendation 7: Both rich genomic data acquired for research and sensitive and potentially identifiable social science data that do not change (or change very little) with time should be shared only under restricted circumstances, such as licensing and (actual or virtual) data enclaves.

As discussed in Chapter 3 , the four basic ways to restrict access to data are licensing, remote execution centers, data enclaves, and virtual data enclaves. Each has its advantages and disadvantages. 1 Licensing, for example, is the least restrictive for a researcher in terms of access to the data, but the licensing process itself can be lengthy and burdensome. Thus it would be useful if the licensing process could be facilitated.

Recommendation 8: NIA (or preferably NIH) should develop new stan dards and procedures for licensing confidential data in ways that will maximize timely access while maintaining security and that can be used by data repositories and by projects that distribute data.

Ways to improve the other approaches to restricted access are needed as well. For example, improving the convenience and availability of virtual data enclaves could increase the use of combined social science and biodata without

a significant increase in risk to confidentiality. The panel notes that much of the discussion of the confidentiality risk posed by the various approaches is theoretical; no one has a clear idea of just what disclosure risks are associated with the various ways of sharing data. It is important to learn more about these disclosure risks for a variety of reasons—determining how to minimize the risks, for instance, or knowing which approaches to sharing data pose the least risk. It would also be useful to be able to describe disclosure risks more accurately to survey participants.

Recommendation 9: NIA and other funding agencies should assess the strength of confidentiality protections through periodic expert audits of confidentiality and computer security. Willingness to participate in such audits should be a condition for receipt of NIA support. Beyond enforce ment, the purpose of such audits would be to identify challenges and solutions.

Evaluating risks and applying protection methods, whether they involve restricted access or restricted data, is a complex process requiring expertise in disclosure protection methods that exceeds what individual principal investigators and their institutions usually possess. Currently, not enough is known to be able to represent these risks either fully or accurately. The NIH requirement for data sharing necessitates a large investment of resources to anticipate which variables are potentially available to intruders and to alter data in ways that reduce disclosure risks while maintaining the utility of the data. Such resources are better spent by principal investigators on collecting and analyzing the data.

Recommendation 10: NIH should consider funding Centers of Excellence to explore new ways of protecting digital representations of data and to assist principal investigators wishing to share data with others. NIH should also support research on disclosure risks and limitations.

Principal investigators could send digital data to these centers, which would organize and manage any restricted access or restricted data policies or provide advisory services to investigators. NIH would maintain the authority to penalize those who violated any confidentiality agreements, for example, by denying them or their home institution NIH funding. Models for these centers include the Inter-university Consortium for Political and Social Research (ICPSR) and its projects supported by NIH and the Eunice Kennedy Shriver National Institute of Child Health and Human Development (NICHD) and the UK data sharing archive. The centers would alleviate the burden of data sharing as mandated of principal investigators by NIH and place it in expert hands. However, excellence in the design of data access and control systems

is likely to require intimate knowledge of each specific data resource, so data producers should be involved in the systems’ development.

INFORMED CONSENT

As described in Chapter 4 , informed consent is a complex subject involving many issues that are still being debated; the growing power of genetic analysis techniques and bioinformatics has only added to this complexity. Given the rapid pace of advances in scientific knowledge and in the technology used to analyze biological materials, it is impossible to predict what information might be gleaned from biological specimens just a few years hence; accordingly, it is impossible, even in theory, to talk about perfectly informed consent. The best one can hope for is relatively well-informed consent from a study’s participants, but knowing precisely what that means is difficult. Determining the scope of informed consent adds another layer of complexity. Will new analyses be covered under the existing consent, for example? There are no clear guidelines on such questions, yet specific details on the scope of consent will likely affect an IRB’s reaction to a study proposal.

What Individual Researchers Need to Know and Do Regarding Informed Consent

To be sure, there is a wide range of views about the practicality of providing adequate protection to participants while proceeding with the scientific enterprise, from assertions that it is simply not possible to provide adequate protection to offers of numerous procedural safeguards but no iron-clad guarantees. This report takes the latter position—that investigators should do their best to communicate adequately and accurately with participants, to provide procedural safeguards to the extent possible, and not to promise what is not possible. 2 Social science researchers need to know that adding the collection of biospecimens to social science surveys changes the nature of informed consent. Informed consent for a traditional social science survey may entail little more than reading a short script over the phone and asking whether the participant is willing to continue; obtaining informed consent for the collection and use of biospecimens and biodata is generally a much more involved process.

Conclusion: Social scientists should be made aware that the process of obtaining informed consent for the use of biospecimens and biodata typically differs from social science norms.

If participants are to provide truly informed consent to taking part in any study, they must be given a certain minimum amount of information. They should be told, for example, what the purpose of the study is, how it is to be carried out, and what participants’ roles are. In addition, because of the unique risks associated with providing biospecimens, participants in a social science survey that involves the collection of such specimens should be provided with other types of information as well. In particular, they should be given detail on the storage and use of the specimens that relates to those risks and can assist them in determining whether to take part in the study.

Recommendation 11: In designing a consent form for the collection of biospecimens, in addition to those elements that are common to social science and biomedical research, investigators should ensure that certain other information is provided to participants:

how long researchers intend to retain their biospecimens and the genomic and other biodata that may be derived from them;

both the risks associated with genomic data and the limits of what they can reveal;

which other researchers will have access to their specimens, to the data derived therefrom, and to information collected in a survey questionnaire;

the limits on researchers’ ability to maintain confidentiality;

any potential limits on participants’ ability to withdraw their speci mens or data from the research;

the penalties 3 that may be imposed on researchers for various types of breaches of confidentiality; and

what plans have been put in place to return to them any medically relevant findings.

Researchers who fail to properly plan for and handle all of these issues before proceeding with a study are in essence compromising assurances under informed consent. The literature on informed consent emphasizes the importance of ensuring that participants understand reasonably well what they are consenting to. This understanding cannot be taken for granted, particularly as it pertains to the use of biological specimens and the data derived therefrom.

While it is not possible to guarantee that participants have a complete understanding of the scientific uses of their specimens or all the possible risks of their participation, they should be able to make a relatively well-informed decision about whether to take part in the study. Thus the ability of various participants to understand the research and the informed consent process must be considered. Even impaired individuals may be able to participate in research if their interests are protected and they can do so only through proxy consent. 4

Recommendation 12: NIA should locate and publicize positive examples of the documentation of consent processes for the collection of biospeci mens. In particular, these examples should take into account the special needs of certain individuals, such as those with sensory problems and the cognitively impaired.

Participants in a biosocial survey are likely to have different levels of comfort concerning how their biospecimens and data will be used. Some may be willing to provide only answers to questions, for example, while others may both answer questions and provide specimens. Among those who provide specimens, some may be willing for the specimens to be used only for the current study, while others may consent to their use in future studies. One effective way to deal with these different comfort levels is to offer a tiered approach to consent that allows participants to determine just how their specimens and data will be used. Tiers might include participating in the survey, providing specimens for genetic and/or nongenetic analysis in a particular study, and allowing the specimens and data to be stored for future uses (genetic and/or nongenetic). For those participants who are willing to have their specimens and data used in future studies, researchers should tell them what sort of approval will be obtained for such use. For example, an IRB may demand reconsent, in which case participants may have to be contacted again before their specimens and data can be used. Ideally, researchers should design their consent forms to avoid the possibility that an IRB will demand a costly or infeasible reconsent process.

Recommendation 13: Researchers should consider adopting a tiered approach to obtaining consent. Participants who are willing to have their specimens and data used in future studies should be informed about the process that will be used to obtain approval for such uses.

What Institutions Should Do Regarding Informed Consent

Because the details of informed consent vary from study to study, individual investigators must bear ultimate responsibility for determining the details of informed consent for any particular study. Thus researchers must understand the various issues and concerns surrounding informed consent and be prepared to make decisions about the appropriate approach for their research in consultation with staff of survey organizations. These decisions should be addressed in the training of survey interviewers. As noted above, however, the issues surrounding informed consent are complex and not completely resolved, and researchers have few options for learning about informed consent as it applies to social science studies that collect biospecimens. Thus it makes sense for agencies funding this research, the Office for Human Research Protection (OHRP), or other appropriate organizations (for example, Public Responsibility in Medicine and Research [PRIM&R]) to provide opportunities for such learning, taking into account the fact that the issues arising in biosocial research do not arise in the standard informed consent situations encountered in social science research. It should also be made clear that the researchers’ institution is usually deemed (e.g., in the courts) to bear much of the responsibility for informed consent.

Recommendation 14: NIA, OHRP, and other appropriate organizations should sponsor training programs, create training modules, and hold informational workshops on informed consent for investigators, staff of survey organizations, including field staff, administrators, and mem bers of IRBs who oversee surveys that collect social science data and biospecimens.

The Return of Medically Relevant Information

An issue related to informed consent is how much information to provide to survey participants once their biological specimens have been analyzed and in particular, how to deal with medically relevant information that may arise from the analysis. What, for example, should a researcher do if a survey participant is found to have a genetic disease that does not appear until later in life? Should the participant be notified? Should participants be asked as part of the initial interview whether they wish to be notified about such a discovery? At this time, there are no generally agreed-upon answers to such questions, but researchers should expect to have to deal with these issues as they analyze the data derived from biological specimens.

Recommendation 15: NIH should direct investigators to formulate a plan in advance concerning the return of any medically relevant findings to

survey participants and to implement that plan in the design and conduct of their informed consent procedures.

INSTITUTIONAL REVIEW BOARDS

Investigators seeking IRB approval for biosocial research face a number of challenges. Few IRBs are familiar with both social and biological science; thus, investigators may find themselves trying to justify standard social science protocols to a biologically oriented IRB or explaining standard biological protocols to an IRB that is used to dealing with social science—or sometimes both. Researchers can expect these obstacles, which arise from the interdisciplinary nature of their work, to be exacerbated by a number of other factors that are characteristic of IRBs in general (see Chapter 4 ).

Recommendation 16: In institutions that have separate biomedical and social science IRBs, mechanisms should be created for sharing expertise during the review of biosocial protocols. 5

What Individual Researchers Need to Do Regarding IRBs

Because the collection of biospecimens as part of social science surveys is still relatively unfamiliar to many IRBs, researchers planning such a study can expect their interactions with the IRB overseeing the research to involve a certain learning curve. The IRB may need extra time to become familiar and comfortable with the proposed practices of the survey, and conversely, the researchers will need time to learn what the IRB will require. Thus it will be advantageous if researchers conducting such studies plan from the beginning to devote additional time to working with their IRBs.

Recommendation 17: Investigators considering collecting biospecimens as part of a social science survey should consult with their IRBs early and often.

What Research Agencies Should Do Regarding IRBs

One way to improve the IRB process would be to give members of IRBs an opportunity to learn more about biosocial research and the risks it entails.

This could be done by individual institutions, but it would be more effective if a national funding agency took the lead (see Recommendation 14).

It is the panel’s hope that its recommendations will support the incorporation of social science and biological data into empirical models, allowing researchers to better document the linkages among social, behavioral, and biological processes that affect health and other measures of well-being while avoiding or minimizing many of the challenges that may arise. Implementing these recommendations will require the combined efforts of both individual investigators and the agencies that support them.

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Recent years have seen a growing tendency for social scientists to collect biological specimens such as blood, urine, and saliva as part of large-scale household surveys. By combining biological and social data, scientists are opening up new fields of inquiry and are able for the first time to address many new questions and connections. But including biospecimens in social surveys also adds a great deal of complexity and cost to the investigator's task. Along with the usual concerns about informed consent, privacy issues, and the best ways to collect, store, and share data, researchers now face a variety of issues that are much less familiar or that appear in a new light.

In particular, collecting and storing human biological materials for use in social science research raises additional legal, ethical, and social issues, as well as practical issues related to the storage, retrieval, and sharing of data. For example, acquiring biological data and linking them to social science databases requires a more complex informed consent process, the development of a biorepository, the establishment of data sharing policies, and the creation of a process for deciding how the data are going to be shared and used for secondary analysis--all of which add cost to a survey and require additional time and attention from the investigators. These issues also are likely to be unfamiliar to social scientists who have not worked with biological specimens in the past. Adding to the attraction of collecting biospecimens but also to the complexity of sharing and protecting the data is the fact that this is an era of incredibly rapid gains in our understanding of complex biological and physiological phenomena. Thus the tradeoffs between the risks and opportunities of expanding access to research data are constantly changing.

Conducting Biosocial Surveys offers findings and recommendations concerning the best approaches to the collection, storage, use, and sharing of biospecimens gathered in social science surveys and the digital representations of biological data derived therefrom. It is aimed at researchers interested in carrying out such surveys, their institutions, and their funding agencies.

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Bresnen M, Hodgson D, Bailey S, et al. Being a manager, becoming a professional? A case study and interview-based exploration of the use of management knowledge across communities of practice in health-care organisations. Southampton (UK): NIHR Journals Library; 2014 May. (Health Services and Delivery Research, No. 2.14.)

Cover of Being a manager, becoming a professional? A case study and interview-based exploration of the use of management knowledge across communities of practice in health-care organisations

Being a manager, becoming a professional? A case study and interview-based exploration of the use of management knowledge across communities of practice in health-care organisations.

Chapter 8 conclusion and recommendations.

In exploring how managers in health care encounter and apply management knowledge, our study has focused on three main aspects: management and leadership in the health-care context, knowledge, knowledge mobilisation and learning processes, and NoPs and CoPs. In this final chapter, we summarise our main conclusions in each of these areas, preceding this with a consideration of the effects of organisational and managerial diversity, before turning to assess the limitations and implications for future research and, finally, drawing out the recommendations from our study.

  • Effects of organisational and managerial diversity

The study was designed to enable analytical generalisation reflecting the diversity in the range of trusts within the NHS and across the range of employees in the NHS charged with management responsibilities.

To capture organisational diversity, three case study organisations were chosen: an acute trust, a care trust and a specialist trust. Our assumption was that these trusts would vary in terms of geographical spread, the number of locations from which services are provided, the diversity of services provided and the number of organisations purchasing services from them. Empirically, these presumed differences were confirmed, although two of the three trusts did undergo substantial changes during the course of the research. However, contextual influences are not merely objective forces acting on organisations: their impact is moderated by individual and collective perception and interpretation in each case. Therefore, a core element of our study was to identify organisational factors and aspects of change which interviewees themselves saw as impacting most powerfully on management practice and knowledge sharing. Collectively, these differences provided a detailed and complex picture of the context within which our managers operated and represented a key element in developing our empirical and thematic analysis.

Managerial diversity was equally important, particularly in the light of the contested nature of management (and leadership) in the NHS discussed in Chapters 3 and 4 . A key objective was to ensure that the study fully captured the distributed nature of the management and leadership in the modern NHS and avoided a too simplistic and misleading dichotomy between management and clinicians.

To ensure that this happened in a structured and meaningful way, a model of management in the NHS was developed and refined, based around a continuum of clinical and managerial training and experience (see Figure 1 ). The main purpose of this model was to guide us in the recruitment of research participants in each trust, using purposive and non-random samples to differentiate between broad clusters of clinical, general and functional managers in each trust. As with the selection of case studies, these differences were necessarily broad-brush, but the empirical research was then used to reveal the substantial richness and complexity encapsulated within this simple model. Nonetheless, these three broad management groups, alongside the three case study organisations, did provide a valuable analytical tool in our empirical and thematic analysis. Therefore, the model itself represents a novel feature and direct deliverable from our research as it provides a tool that allows us to differentiate between these three managerial groups.

  • Management and leadership in the health-care context

As noted in the discussion in Chapter 1 , the study of management in health-care organisations faces a number of theoretical and empirical challenges, one of which is to work with the complex relationship between management and leadership, a theme that has been explored at long length in academic and practitioner literatures. 27 , 28 , 89 This distinction typically contrasts visionary, strategic and transformative leadership, with a more procedural, operational and bureaucratic approach to management. 28

Within the NHS, the management/leadership distinction is probably more sharply defined and has greater palpable weight and political significance than in many other sectors, for the reasons outlined in Chapter 4 . In particular, historical tensions between management and clinical professions result in an ongoing suspicion of (and resistance to) management both as a function and as a cadre. Our analysis of health-care management, therefore, recognises the evolution of terminology in the NHS, in the first instance in the privileging of management over administration, and more recently in moves to celebrate leadership, including clinical leadership, over management. 70 , 89

The consequence is a complex and delicate ontological landscape, in which many NHS employees who manage will, for a variety of reasons, be reluctant or conflicted over the title ‘manager’ and indeed may not recognise their practice as ‘managing’, typically identifying instead with the role of leader and the practice of leadership. To address management effectively, paying full recognition to its political complexity in this context, our approach in this study was to address management inductively: as a question, informed by extant research on management and leadership within the NHS, and more widely. The first aim of our empirical research was to draw out and differentiate understandings of management and leadership as understood and practised by respondents in our study, rather than imposing meaning externally. The result is a more complicated and contested, but nevertheless richer, picture of management in our subject organisations, as understood, practised and articulated by managers both formally and informally.

This mapping out of meanings of management in our study, assisted through the development of our selection framework for managers (see Figure 1 ), led to two key findings from our research. First, management in the NHS is not only a heterogeneous activity, but also a heterogeneous identity, in that it is distributed among a wide range of occupational groups (classified by ourselves into the aggregate categories of clinical, general and functional), which draw upon highly diverse sources of knowledge, learning and experience and who interact through very diverse and open distinct networks of interaction and CoPs. Second, in this milieu, it is general managers who face the greatest challenge in sharpening their sense of professional identity based around a distinct and coherent managerial knowledge base.

  • Knowledge, knowledge mobilisation and learning

To examine these knowledge processes further, the report drew upon a classical differentiation between explicit and tacit forms of (management) knowledge and between abstract learning and learning that is situated in practice. This enables us to distinguish between four primary types of knowledge in our study: 125

  • knowledge encultured in the norms, values and practices of managers
  • knowledge embedded in local management systems and processes
  • knowledge encoded in management tools and techniques
  • knowledge embodied in the skill sets of individuals.

In turn, this system helps to draw out the challenges involved in attempting to mobilise knowledge between contexts and to abstract it from, and translate it into, practice, through processes of socialisation, externalisation, combination and internalisation. 37 As a consequence, our study focused substantially on issues of knowledge translation, of putting encoded knowledge such as lean thinking into practice, for instance. Equally, however, there was the challenge of translating local and embodied solutions and innovations into generalisable and transferable knowledge. Similarly, this focus enabled the identification of particular barriers and gaps in this mobilisation process. A particular theme of interest in light of this framing was the role of formal training and development in management and its impact and importance when compared with other, more experiential modes of learning.

Although focused on management knowledge, the elephant in the room throughout our discussions has been the particularly influential body of professional knowledge associated with clinicians, against which managerial knowledge and understanding are often juxtaposed. It was therefore necessary to pay attention to the ways in which management knowledge was perceived to be in competition with, or judged against, medical bodies of knowledge in the process of collective decision-making, for example. At the same time, as many of our managers were simultaneously, or formerly, clinicians, the performance of their role often relied as much on their clinical or other professional knowledge and experience (and the credibility it gave them) as it did on their managerial know-how.

Taking these two aspects together points to a third key finding to emerge from the research, namely the strong tendency for managerial knowledge, particularly that harnessed by general managers, to be more home grown (situated in local practices) and experiential. Local pressures associated with trust reporting and management requirements combined with the hegemony of clinical know-how and the influence of a financial discourse tended to create a strong reliance on local and experiential knowledge (notwithstanding the potential value of alternative, external forms of knowledge and learning).

Although our theoretical framing was substantially informed by contemporary thinking on knowledge sharing and learning, which emphasises the socially situated nature of knowledge, it also emphasises the importance of learning or knowing through social interaction in NoPs and CoPs and this is what we turn to next as the third of our major themes.

  • Networks and communities of practice

An understanding of flows of knowledge requires an insight into the nature and dynamics of the networks and communities within which practitioners are located, opening up a consideration of the various NoPs and CoPs to which managers may belong, their role and organisation, the relationship between the interactions they enable (or constrain) and associated processes of socialisation and learning (or exclusion and non-learning).

Despite the value of the substantial literature on CoPs that highlights the interpenetration of socialisation and knowledge-sharing processes, we also recognise the limitations of too exclusive a focus on this type of arrangement. 151 Membership of a CoP revolves around shared narratives of experience, shared paradigmatic modes of analysis and shared modes of representation. 46 Although CoPs are typically defined as closely related groups of practitioners who develop and share common understandings through frequent and close interaction, we aimed to remain sensitive to the variety of groups and communities to which managers may belong and to potential interplays between them. Therefore, we focus on a broader and more extensive concept of networks, a concept which allows for a greater diversity in terms of their degree of co-ordination and cohesion, strictures on membership, the ways in which they are formed and their location within or across organisational boundaries. To be clear, several of the networks examined empirically in the study do indeed display the cohesion of a CoP, but many are significantly more informal, loose, open and flat or distributed networks, which nonetheless play a key role in knowledge mobilisation and socialisation for the managers in our study.

To capture the meaning and significance of these networks, we set out to discover what networks exist, how they function and what purpose they serve for the managers in each trust. In other words, the process was an inductive one of ascertaining the network connections of salience and importance to managers, rather than a narrow but more constrained focus on formal, closed or centralised networks and, especially, those with a highly performative focus on narrow instrumental goals. Through this flexibility, we were able to explore the diverse range of inter-related purposes served by networks, including not only knowledge acquisition but also career advancement, influencing policy and practice, and personal/emotional support. We examined these outcomes in terms of both individual and organisational benefits, cognisant of recent and on-going debates on the value of social capital but, again, without reducing networks and the activity of forging relationships to narrowly instrumental motives.

Perhaps the key general finding to emerge in this respect was the challenges faced by general managers in being able to access fully and be actively engaged with wider networks of professionals (not only across trusts but within them too). Not only did this mean that general managers had less opportunity to gain potentially valuable knowledge and support, but also that it tended to reinforce any reliance on local and experiential knowledge, adding to any inward-looking tendencies.

  • Limitations and directions for future research

Our research has lent strong support to the framework developed in Figure 1 as a means of differentiating between relatively distinct managerial groups and the quite different NoPs and CoPs they tend to engage with. It has also demonstrated the value of situating analysis of management knowledge mobilisation and utilisation in the context of the particular organisational conditions and challenges facing those diverse managerial groups. However, that very complexity and diversity also inevitably creates limitations for how qualitative research is able to tap into the processes concerned.

One obvious limitation is in the restriction in the range of case organisations to three types of trust. The research has adopted standard and accepted protocols for case study design and selection that emphasise the importance of choosing cases that show variation in key conditions (in this research, expected variation in managerial knowledge networks) and which rely on analytical, rather than statistical, generalisability to extrapolate findings to different types of setting. 52 , 53 Consequently, it becomes possible to conclude, for example, that challenges to management networking may equally be found in other highly differentiated forms of trust. However, the importance of a holistic understanding of case conditions and their effects also alerts one to the possibility that different constellations of conditions may create different outcomes in other types of trust. Only by extending the research systematically to consider all potential types of trust would it be possible to conclude that the range of likely conditions are fully captured in the research design.

Second, a similar limitation is in the number and range of participants included in the research. Again, the research has applied small-scale purposive sampling, rather than large-scale random sampling methods to systematically select participants for interview. As such, the findings are inevitably restricted to the range of experiences and conditions faced by the selected group of managers. The qualitative nature of the study has allowed us to choose our participants carefully in order to ensure an appropriate range of respondents and then to examine their experiences in considerable depth. Moreover, respondents have also effectively acted as key informants on the issues faced by managers generally and we have been able to augment interview data with direct observation of management practices. However, there is clearly scope here for more extended research that explores the issues raised through larger-scale systematic or random sampling of respondents both within and across trusts. This could be based on the use of the framework of management types developed in our study.

Third, the ethnographic study of the managers, their access to knowledge sources and their involvement in networks is also inevitably constrained by the resources available to conduct such research in the depth that would be required to get a complete picture of managerial knowledge mobilisation and utilisation. The data obtained have provided rich insights into the ways in which different managers access, share and use managerial knowledge and how this relates to diverse organisational and professional circumstances. However, each of these networks of interaction in which specific groups of managers are involved is worthy of study in their own right. Studying wider networks of activity has been beyond the scope of the current study, as the emphasis has been on managers’ perceptions. Consequently, there is clearly further scope for exploring in greater depth any or all of the networks of interaction that involve the managers we studied (and others) effectively in their own right. Research of this type may employ similar ethnographic methods, but could also use more quantitative techniques, such as social network analysis. This research has signposted areas in which further research may reveal important details about the structure and dynamics of such networks of interaction, knowledge creation and sharing, but has not been able to capture these in full.

Fourth, the ethnographic element of the research has been important in helping to understand and situate management knowledge and learning processes in practice. But there is more that could be done to extend this type of work to get deeper insights into these processes. Resource constraints meant that it was not possible to extend this aspect of the work fully, for example through extended periods of stay or shadowing of managers or tracking interaction further into external NoPs and interaction. Selection of managerial events and encounters to observe also means that a standard criticism of ethnography (that findings from observations are inevitably restricted to what is observed) apply to this research as well. More extended ethnographic study is one way to build on the insights from this study to get further insights into the processes involved.

Last but not least, recent changes to the relationships between primary and secondary health care pose a number of further important potential questions about the nature, sources and application of management knowledge in a changing health-care environment. The scope of this research has not extended to primary-care organisations, so there is a need for further research to explore management knowledge and learning processes in the primary-care domain as well as in the changing interface between secondary and primary care.

  • Recommendations

There are seven general recommendations that emerge from the research, each of which has a number of implications for practice at, variously, national, regional or trust level. These are particularly in the realm of management training and development, but also encompass steps that trusts and other agencies might take to improve the structural context within which managers work and are embedded.

  • Leadership training and development programmes (e.g. via the NHS Leadership Academy) need to ensure that the development of leadership takes account of the complex relationship between leadership skills and management practice on the ground.
  • Such programmes also need to balance an emphasis on leadership with continued attention to the importance of management skills (especially leadership-related skills, such as interpersonal communication).
  • Local trust training and development programmes can help maximise the transferability of context-specific leadership training to management practice by ensuring that analysis of leadership challenges and solutions continue to be firmly situated in management problem-solving and decision-making scenarios.
  • Training and development programmes provided at trust level need to ensure a balance of emphasis on learning from experience with the use of more codified systems of knowledge that can effectively challenge received wisdom and accepted practices.
  • Trusts need to be aware of the need to capture and share knowledge and learning that may be localised in specific parts of the organisation (e.g. tender bidding skills), such knowledge may be particularly important to generalise across trusts in the light of recent changes to the organisation of primary, secondary and tertiary health-care provision.
  • Trusts need to carefully consider how they attempt to bridge the clinical–managerial divide and tailor their approaches to achieving this to match the specific context of interaction (e.g. by combining structural adjustments with the relational skills of key individuals for whom status differentials are high, or by relying on embodied experience when there is more of a blending of clinical and managerial orientations).
  • National leadership programmes should be considered as an opportunity for cultivating networked interaction between distinct types of managerial groups (especially clinical and general). This approach would encourage development of shared perspectives between the CoPs on the use and application of specific types of managerial knowledge.
  • There may also be opportunities for trusts to develop mechanisms for such networked interaction focused on management issues and solutions at a more local level, provided that they occur away from immediate operational pressures. Such initiatives may be particularly important in the context of significant recent changes in the relationship between secondary and primary care.
  • Middle managers, especially those in general management positions, need more access to leadership development and training opportunities that are better synchronised with the demands of their role and the stage of their career. There is currently a gap in the more strategic (as opposed to operational) training opportunities that tie in with middle managers’ needs.
  • Wider (national) leadership training programmes can help bridge that gap, provided that the knowledge base they impart (e.g. lean thinking, strategic analysis) is not abstracted from health-care practice but used instead in a more heuristic way to inform analysis of health-care management problems.
  • Trusts also need to find ways of giving middle managers time out from busy schedules to take up any opportunities afforded by more advanced training and development programmes that are based on such reflective learning processes.
  • Opportunities provided for networking through national leadership development programmes are recognised as valuable but can also be sporadic or limited in their availability. More could be done to encourage continued interaction through these networks at a regional or local level following core programme activities.
  • Recognition needs to be given (in national and more local training programmes) to the importance and benefits of both formal and informal networks of interaction as sources of knowledge and support for managers and how specific mechanisms for middle managers may help significantly (e.g. mentoring).
  • Initiatives at national, regional or individual trust level need to recognise that networked interaction among managers, when it occurs, does so largely within the distinct CoPs associated with general, clinical and functional managerial groups (as opposed to there being one distinct and coherent CoP).
  • External (regional, area) networks of managers could be actively cultivated (either by individual trusts or through intertrust collaboration). These external networks should be focused on particular knowledge and learning themes (e.g. aspects of management best practice), as opposed to being driven primarily by operational requirements.
  • Trusts that are highly differentiated (geographically, organisationally, professionally) may benefit particularly from taking their own internal networking initiatives that have the dual advantage of helping managers share best practice as well as improving organisational integration.
  • Trusts faced with recent challenges associated with changes in secondary/primary care may find managerial networking of increased relevance and importance to the achievement of their goals.
  • National leadership development programmes should continue to build on the networking opportunities they offer and networking skill development they aspire to provide.
  • In addition, such programmes should also build on the potential they offer for greater collective development and further institutionalisation of a distinct body of health-care management knowledge and practice.

Included under terms of UK Non-commercial Government License .

  • Cite this Page Bresnen M, Hodgson D, Bailey S, et al. Being a manager, becoming a professional? A case study and interview-based exploration of the use of management knowledge across communities of practice in health-care organisations. Southampton (UK): NIHR Journals Library; 2014 May. (Health Services and Delivery Research, No. 2.14.) Chapter 8, Conclusion and recommendations.
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Home Blog Education Learning Objectives Examples: How to Create High-Quality Educational Slides

Learning Objectives Examples: How to Create High-Quality Educational Slides

Cover for how to write learning objectives examples

Learning objectives are the foundations of any course or training program. They provide a clear roadmap for both educators and learners. They set a direction for the learning journey by outlining the expected outcomes. Therefore, trainers need to ensure their programs are purposeful, engaging, and aligned with their educational goals.

In this article, we’ll explore learning objectives, why they matter, and how they differ from other goals in terms of creating presentation slides to depict them. 

Table of Contents

Defining Learning Objectives

Characteristics of good learning objectives, steps to write learning objectives, training learning objectives examples, lesson objective examples, common mistakes to avoid when writing learning objective examples, tools and resources to represent learning objective examples.

According to Melton (1997), learning objectives, also known as learning outcomes, are concise statements that outline the specific achievements expected from trainees after receiving training or a lesson [1]. Unlike general learning goals, these objectives offer explicit criteria, enabling instructors to evaluate whether students have successfully attained the intended learning outcomes. Using clearly defined and actionable learning objectives enhances your ability to assess texts or activities for appropriateness and relevance.[1] Learning objectives are specific statements that describe the measurable and observable skills, knowledge, or attitudes that learners should acquire after completing a training program. In training programs , these objectives act as a guide, helping to focus instructional efforts and assess the effectiveness of the learning experience.

Learning objectives play a crucial role for instructors and trainers in developing assessments that align with the course’s learning activities and training materials . Alignment is how effectively learning objectives, assessments, and instructional materials collaborate to accomplish the intended learning goals. Learning objectives indicate that assessments are focused on the materials covered in the course, simplifying the process of creating assessment items for instructors [2]. Learning objectives communicate what is essential for learning. Without learning objectives, students struggle to identify their learning and areas that demand specific attention. Clearly, articulated learning objectives contribute to students or trainees adopting more efficient and effective study approaches. Moreover, well-crafted learning objectives help them acquire new knowledge that can be applied flexibly and appropriately across various contexts, both in the short term and in the future. This application of knowledge, termed “transfer,” as emphasized by Barnett and Ceci (2002), is a significant indicator of profound learning [3].

Learning objectives should be short and clear statements about what learners can do after a lesson.  These objectives can be based on three things: what learners know, their skills, and their attitudes [4]. A good learning objective has these characteristics:

Clear and Concise

Learners must understand the objectives clearly. Learning objectives should be expressed straightforwardly, avoiding unnecessary complexity or ambiguity [10]. Everyone needs to be aware of what they are learning and the reasons behind it. They need to grasp how these objectives fit into the broader picture – connecting with the previous lesson, the ongoing course, and the overall goal [5]. Merely writing the objectives on the board and expecting students or trainees to copy them isn’t sufficient. It requires thorough explanation in context, active engagement from the learners, and the ability to articulate and explain the objectives to any observer.

A learning objective should be created with a specific action verb representing an observable and measurable outcome related to the identified knowledge or skills. The use of action verbs conveys what learners are expected to accomplish, ensuring a tangible and quantifiable outcome [7].

Make sure each goal focuses on one thing the learner should be able to show or perform. Actionable goals should start with a word like “recall,” “describe,” “explain,” or “select,” not unclear words like “understand” or “know” that you can’t see or measure. Keep it simple and practical.

Learning Objectives word cloud

Learning objectives, serving as evaluation criteria, should assist trainers in assessing the extent to which learners achieve the intended learning outcomes. Much of the impact training has on learners is internal and remains unseen. Learners may alter their perspectives, shift attitudes, and acquire new knowledge [6]; however, trainers cannot directly observe the internal processes of a trainee’s mind. They must rely on external indicators (observable actions or statements) to gauge the trainee’s progress. Therefore, assessing progress based on what a student “learns,” “understands,” “knows,” or “feels” becomes challenging. Learning objectives, therefore, should focus on observable and measurable changes. An objective can be made measurable by adding specific criteria. It could specify a percentage of accuracy, a number of items, a time frame, or other measurable criteria. For example, the learner will solve 90% of math problems correctly.

Relevant to the Training Program

Objectives must directly contribute to the overall goals and purpose of the training program, maintaining relevance and coherence. Learning objectives should address these questions. Is the objective aligned with the program’s primary goal(s)? Will achieving the objective contribute to reaching the main goal(s)? Design the course or training thoughtfully to ensure that each learning objective is relevant to training.  Likewise, the learning materials, activities, and assessments should be interlinked.

Time-Bound (SMART Objectives)

A learning goal needs a defined timeframe for completion, like the conclusion of a lesson, module, or entire course. It is crucial to allocate sufficient time within the lesson, module, or course to accomplish the necessary steps for reaching the goal.  In short, a learning objective should be smart;

SMART Goals in Learning Objective Examples

S- Specific : Effective learning objectives divide a broad subject into manageable parts and clearly outline the expected outcomes connected to these components.

M-Measurable: Learning objectives should be quantifiable, allowing for easy assessment of whether the desired outcome has been achieved.

A-Achievable: Considering the available resources, timeframe, Learner’s background, and readiness, set achievable objectives. The cognitive complexity of the learning goals should match both the training level and the learners’ proficiency. Therefore, take into account factors like whether it’s basic or advanced level training before making a learning objective.

R-Result Oriented: Learning objectives should emphasize the outcomes rather than the processes or tasks learners will undertake (such as presenting or completing a task). A good learning goal describes the end results – what knowledge, skills, or attitudes learners should gain based on what the trainer can assess.

T-Time bound: Clearly mention the timeframe if it’s relevant. This can assist in determining the level of performance learners need to demonstrate to be competent.

As you create your learning objectives, you need to follow these steps.

Step 1: Identify the Desired Outcome of the Training Program

Identifying the desired outcome sets the direction for your entire training program. It provides a clear goal for both trainers and learners. It aligns the training program with broader organizational goals. It sets expectations and helps measure the success of the program.

Begin by considering the broader organizational goals. What specific improvements in skills or performance will contribute to these goals?

Break down the outcome into measurable components. What specific skills or knowledge gaps exist? Then, envision the ideal scenario after the training – what should the team be capable of doing? What skills or knowledge do you want participants to gain?

The importance lies in setting a clear, achievable target that aligns with organizational objectives. When you identify the broader goal of the training program, narrow it down into a learning objective [8].

70-20-10 learning framework for learning objectives planning

This step is crucial because it sets the direction for your entire training program. It defines what success looks like and guides the subsequent steps in the process.  Consider the current state of the team, the challenges they face, and the skills they need to overcome those challenges.

Imagine you’ve assessed that your sales team struggles with closing deals effectively. The desired outcome, in this case, would be to improve their closing techniques and boost overall conversion rates. In the context of sales training, the desired result could be to enhance the sales team’s ability to close deals and increase conversion rates. Why is this important?

Step 2: Use Action Verbs to Describe What Trainees Will Be Able to Do

Now that we know what we want to achieve, the next step is to articulate it using action verbs. Action verbs make objectives actionable and observable. How do I choose these verbs? They should precisely convey the expected behaviors or skills. It’s essential to avoid vague verbs that can lead to unclear expectations. Action verbs are crucial in learning objectives as they define the observable behaviors or skills that learners should acquire. Choosing the proper verbs is essential for clarity and precision.

Action verbs describe an observable action, giving a clear picture of what learners are expected to do. Action verbs provide clarity on what exactly we expect our learners to do. They help in crafting specific and measurable objectives. When choosing action verbs, consider the level of performance you want to see. Words like ‘understand’ or ‘know’ are vague. Instead, opt for strong verbs that denote observable actions.

In our sales training program, we’ve chosen the action verb ‘demonstrate.’ This emphasizes the sales team’s importance in understanding and actively showcasing effective closing techniques.

We have come up with this learning objective so far;

“By the end of the training program, sales team members will be able to demonstrate effective closing techniques to increase conversion rates.”

‘Demonstrate’ is an intense action verb that implies a visible and practical application of knowledge. In sales, demonstrating effective closing techniques is a tangible and measurable skill.

Step 3: Ensure the Objective is Measurable

Measurability is crucial for assessing the success of your learning objective. It involves defining clear criteria to determine whether the desired outcome has been achieved. Without measurable criteria, evaluating the effectiveness of the training becomes challenging.

Attach specific metrics or criteria that provide a quantitative or observable way to assess success. This could involve percentages, numbers, or other tangible measures.

Think about how you can quantify or assess the outcome. In our example, we set a measurable criterion: a 15% increase in the overall conversion rate within the next quarter.

KPIs for learning objectives

Step 4: Align the Objective with the Overall Goals of the Training Program

Aligning the objective with the overall goals ensures coherence and relevance. The aim should not be an isolated achievement but a meaningful contribution to the broader success of the training program.

Consider how achieving this specific objective fits into the larger picture. How does it support your training program’s overall goals and objectives and, by extension, your organization?

In our case, the overall goal is to improve the sales team’s performance to meet and exceed quarterly revenue targets. Our learning objective aligns perfectly by directly contributing to this overarching goal.

“By the end of the training program, sales team members will be able to demonstrate effective closing techniques, contributing to a 15% increase in the overall conversion rate within the next quarter, thereby supporting the overall goal of improving the sales team’s performance to meet and exceed quarterly revenue targets.”

Training needs assessment slide

Real-Life Case Studies of Learning Objective Examples

So far, we’ve analyzed how to write actionable and measurable learning objectives, but now it’s time to consider how to represent these learning objectives in presentation slides with the idea of stepping into the shoes of an instructor. Thinking about the design aspects can be challenging for some; thus, we will showcase a series of learning objective examples in two different categories: training and lesson planning. Below each case, you can find a visual representation of the learning objective to deliver more audience engagement.

A training is conducted by a firm on Time Management for Managers. This training is vital because effective time management is crucial for managers to maintain productivity and meet deadlines. It is realized that many managers struggle with task prioritization, leading to missed deadlines and increased stress.

Learning Objective Example 01

Use the Eisenhower Matrix to categorize tasks based on urgency and importance within two weeks.

This learning objective is evident in what managers need to do (Use the matrix), measurable by their ability to categorize tasks, achievable within two weeks, relevant to task prioritization, and time-bound.

Training learning objective example

Learning Objective Example 02

Implement project management software to streamline task organization and meet deadlines within one month.

This objective addresses the broader aspect of time management by introducing a tool. It specifies the action (implement software), is measurable through enhanced task organization, achievable in one month, relevant to meeting deadlines, and time-bound.

Training learning objective example for software implementation

A lesson is about understanding literary devices in poetry. Understanding literary devices is crucial for students to appreciate and analyze poetry effectively.

Example of Vague Objective

Learn about poetry devices.

This objective is too broad and lacks specificity. It doesn’t specify which poetry devices students should focus on. To enhance clarity, we should specify the devices, such as “Identify similes and metaphors in assigned poems.

A Well-Established Lesson Objective Example

Identify Similes and Metaphors in Assigned Poems during One Class Period

What is a learning objective example

It is a clear and concise objective focusing explicitly on identifying similes and metaphors in assigned poems. Students will actively read and analyze poems to “identify” and differentiate between similes and metaphors. “Identify” is used as an action verb here, so the objective is actionable. Success is observable when students accurately point out similes and metaphors in the assigned poems during the class period. At the same time, it is relevant to the lesson plan that directly addresses the challenge of understanding and recognizing literary devices in poetry. It is achievable within the timeframe of one class period.

Another example can be visualized in the format of an end-of-unit exercise:

Develop a strategy for effective delegation, reducing workload stress by 20% over the next quarter.

Focusing on delegation, this objective is specific in developing a strategy that is measurable by workload stress reduction, achievable in the next quarter, directly relevant to the issue, and time-bound, providing a clear timeframe for improvement.

conclusion and recommendation in case study example

Vague or Unclear Objectives

Vague or unclear objectives lack specificity, making it challenging for learners to understand what is expected. When a purpose is unclear, it can lead to confusion and misinterpretation. To address this, learning objectives should be articulated with precision, clearly outlining the specific skill or knowledge area that learners are expected to acquire. This clarity provides a roadmap for both learners and instructors, fostering a more effective learning process.

Example of Lack of Clarity – “Write better essays.”

The term “better” is subjective and doesn’t provide a clear benchmark for improvement. We should define the improvement to enhance clarity, such as “Organize ideas logically within paragraphs using transitions.”

Objectives That Are Not Measurable

Measurability is crucial for assessing progress and achievement. Objectives that lack a measurable component make it challenging to determine whether the desired outcome has been met. Learning objectives should incorporate specific criteria or actions that can be observed, evaluated, or quantified to enhance measurability. This not only provides a clear standard for success but also allows for practical evaluation and feedback. Measurable objectives contribute to a more transparent and accountable learning process.

Example of Non-Measurable Objective – “Enhance academic writing abilities.”

The term “enhance” is vague and lacks a measurable outcome. To make it more effective, we should make it measurable, like “Apply proper citation formats in academic writing.”

Indeed, let’s delve into a detailed discussion on common mistakes to avoid when writing learning objectives without relying on excessive adjectives.

Objectives That Are Not Aligned with the Training Program’s Goals

Alignment between individual learning objectives and the broader goals of the training program is essential for overall program success. When objectives are not in harmony with the program’s goals, there is a risk of diverging efforts that may not contribute to the desired outcomes. Ensuring alignment involves thoroughly understanding the overarching program goals and carefully crafting objectives that directly support those goals. This strategic alignment ensures that every learning objective plays a meaningful role in achieving the overall objectives of the training program. For instance, if a training program aims to enhance customer service skills, an objective like “Master advanced technical troubleshooting” might not align with the program’s focus. To ensure alignment, objectives should directly contribute to the overarching goals of the training program. An aligned objective would be to “Resolve customer issues efficiently following company protocols.”

You need resources like educational content guidelines, collaboration tools, and text editors to write practical learning objectives for courses or training. Presentation templates are crucial for efficiency, consistency, and visual appeal. They save time by providing pre-designed structures, ensuring a professional look, and allowing customization to match the course theme.

In essence, SlideModel offers a comprehensive toolkit for educators and trainers. From visual excellence to efficient customization and alignment with SMART goals , these templates elevate the process of creating learning objectives. 

Using visually engaging graphics and layouts adds more clarity to learning objectives. This makes the content more attractive and facilitates better understanding for your audience. SlideModel offers an extensive collection of Google Slides templates , providing educators and trainers with a visually stunning canvas for crafting learning objectives.

The ready-made nature of PowerPoint templates significantly accelerates the aim of the learning creation process. Instead of starting from scratch, you can use these templates to structure your content quickly. This time-saving advantage allows you to focus on the substance of your learning objectives without getting bogged down by formatting complexities.

1. E-Learning Objective Examples PowerPoint Template

conclusion and recommendation in case study example

If you intend to harness the power of visuals to boost your lesson objective examples, this is the slide deck to use. Filled with hand-made vector graphics, this learning objectives examples for training template allows us to present exercises to students, establish deadlines with clear requirements, express the learning objectives of each course unit, and more.

Use This Template

2. Employee Training Objectives PowerPoint Template

conclusion and recommendation in case study example

Display the learning objectives for your in-company training program, evaluate the training needs and where your employees currently stand, and properly plan the agenda for these professional training courses using a minimalistic layout PPT template. Easy to customize, we also include a roadmap and two slides for 3-month and 6-month training plans.

3. Course Syllabus Lesson Plan Objectives PowerPoint Templates

conclusion and recommendation in case study example

Teachers can easily connect with their students about the expected outcome of the course and learning objective examples by using this best PPT template. Explain the expectations for the course, the content that will be shared, the main learning objectives, and the required materials.

4. Creative Lessons Learned PowerPoint Template

conclusion and recommendation in case study example

Summarize the core points to be covered as learning objectives for any course or training program by using this slide deck. It allow us to work lesson by lesson, which is ideal for online courses, and also to brief students about the key takeaways of each unit.

5. Math Symbols PowerPoint Template

conclusion and recommendation in case study example

Present math-related learning objectives in a visually appealing format by using our Math Symbols PowerPoint Template. Instructors can find slides with math symbols, compass, calculators, and other relevant vector graphics to reinforce the topic they want to present as a lesson objective.

The Objective slide and other templates in SlideModel are customizable to suit the specific needs of your learning objectives. You can easily modify text, insert relevant images, and adapt the layout to align with your educational context. This customization feature ensures your learning objectives are visually appealing and tailored to your unique instructional requirements. Whether you are creating a detailed training module or a standalone learning objective presentation, these templates enhance the overall visual consistency, contributing to a polished and professional look.

Learning objectives are like guides in the learning world. Think of them as maps showing the way to knowledge and skills. With practical examples, we’ve made creating these objectives less of a mystery. They’re not just fancy educational talk; they’re like step-by-step plans for success. Whether you’re a trainer, someone designing lessons, or just curious about learning, nailing down these objectives becomes a shared way of talking about goals. The principles of specificity, measurability, relevance, and alignment are emphasized, showcasing the characteristics that make learning objectives genuinely effective.

[1] Melton, R. 1997. Objectives, Competencies, and Learning Outcomes: Developing Instructional Materials in Open and Distance Learning. London, UK: Kogan Page.

[2] Stapleton-Corcoran, E. 2023. Learning Objectives , Center for the Advancement of Teaching Excellence. University of Illinois Chicago. https://teaching.uic.edu/learning-objectives/ .

[3] Barnett, S. M., & Ceci, S. J. 2002. When and Where Do We Apply What We Learn? A Taxonomy for Far Transfer. Psychological Bulletin , 128(4), 612-637.

[4] https://www.sciencedirect.com/topics/social-sciences/learning-objective

[5] Course Objectives & Learning Outcomes. https://resources.depaul.edu/teaching-commons/teaching-guides/course-design/Pages/course-objectives-learning-outcomes.aspx

[6] Course design (no date) CTE Resources. https://cteresources.bc.edu/documentation/learning-objectives/

[7] Learning Objectives – Eberly center – Carnegie Mellon University (no date) Learning Objectives – Eberly Center – Carnegie Mellon University. https://www.cmu.edu/teaching/designteach/design/learningobjectives.html

[8] Course design CTE Resources. https://cteresources.bc.edu/documentation/learning-objectives/

[9] Chatterjee, D., & Corral, J. (2017). How to Write Well-Defined Learning Objectives. The journal of education in perioperative medicine : JEPM, 19(4), E610.

[10] http://batchwood.herts.sch.uk/files/Learning-Objectives.pdf

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How Machine Learning Will Transform Supply Chain Management

  • Narendra Agrawal,
  • Morris A. Cohen,
  • Rohan Deshpande,
  • Vinayak Deshpande

conclusion and recommendation in case study example

Businesses need better planning to make their supply chains more agile and resilient. After explaining the shortcomings of traditional planning systems, the authors describe their new approach, optimal machine learning (OML), which has proved effective in a range of industries. A central feature is its decision-support engine that can process a vast amount of historical and current supply-and-demand data, take into account a company’s priorities, and rapidly produce recommendations for ideal production quantities, shipping arrangements, and so on. The authors explain the underpinnings of OML and provide concrete examples of how two large companies implemented it and improved their supply chains’ performance.

It does a better job of using data and forecasts to make decisions.

Idea in Brief

The problem.

Flawed planning methods make it extremely difficult for companies to protect themselves against supply chain disruptions.

A new approach, called optimal machine learning (OML), can enable better decisions, without the mystery surrounding the planning recommendations produced by current machine-learning models.

The Elements

OML relies on a decision-support engine that connects input data directly to supply chain decisions and takes into account a firm’s performance priorities. Other features are a “digital twin” representation of the entire supply chain and a data storage system that integrates information throughout the supply chain and allows for quick data access and updating.

The Covid-19 pandemic, the Russia-Ukraine conflict, trade wars, and other events in recent years have disrupted supply chains and highlighted the critical need for businesses to improve planning in order to be more agile and resilient. Yet companies struggle with this challenge. One major cause is flawed forecasting, which results in delivery delays, inventory levels that are woefully out of sync with demand, and disappointing financial performance. Those consequences are hardly surprising. After all, how can inventory and production decisions be made effectively when demand forecasts are widely off?

  • Narendra Agrawal is the Benjamin and Mae Swig Professor of Information Systems and Analytics at Santa Clara University’s Leavey School of Business.
  • Morris A. Cohen is the Panasonic Professor Emeritus of Manufacturing & Logistics at the University of Pennsylvania’s Wharton School. He is also the founder of AD3 Analytics, a start-up that developed the OML methodology for supply chain management.
  • Rohan Deshpande is a machine learning scientist at Cerebras Systems and a former chief technology officer at AD3 Analytics.
  • Vinayak Deshpande is the Mann Family Distinguished Professor of Operations at the University of North Carolina’s Kenan-Flagler Business School.

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  1. (PDF) Case-Based Recommendation

    conclusion and recommendation in case study example

  2. Thesis Conclusion And Recommendation Sample

    conclusion and recommendation in case study example

  3. How to write a recommendation in a research paper

    conclusion and recommendation in case study example

  4. How to write the conclusion of your case study (2022)

    conclusion and recommendation in case study example

  5. How to Write a Thesis Conclusion and Recommendation Chapter

    conclusion and recommendation in case study example

  6. 49 Free Case Study Templates ( + Case Study Format Examples + )

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VIDEO

  1. How to Write a Case Study? A Step-By-Step Guide to Writing a Case Study

  2. How to ALIGN Your QUALITATIVE Study || Purpose, Problem, and Research Questions

  3. CHAPTER 5

  4. Writing Conclusion, Discussion and Recommendation Section in Research

  5. How to Write Chapter 5 Summary of Findings, Conclusion and Recommendation PPT

  6. How to Write a Conclusion for a Dissertation

COMMENTS

  1. How To Make Recommendation in Case Study (With Examples)

    1. Review Your Case Study's Problem 2. Assess Your Case Study's Alternative Courses of Action 3. Pick Your Case Study's Best Alternative Course of Action 4. Explain in Detail Why You Recommend Your Preferred Course of Action Examples of Recommendations in Case Study Tips and Warnings References What Is Recommendation in Case Study?

  2. How to write the conclusion of your case study

    UX case studies must be kept short, and, when considering the length of your beginning, process and conclusion sections, it's the beginning and the conclusion sections that should be the shortest of all. In some case studies, you can keep the ending to two or three short phrases. Other, longer case studies about more complex projects may ...

  3. 8: CONCLUSIONS AND RECOMMENDATIONS

    The Journal of Biological Chemistry, for example, has such a policy: ''Authors of papers published in the journal are obligated to honor any reasonable request by qualified investigators for unique propagative materials such as cell lines, hybridomas, and DNA clones that are described in the paper.''

  4. How to Write Recommendations in Research

    Recommendation in research example Other interesting articles Frequently asked questions about recommendations What should recommendations look like? Recommendations for future research should be: Concrete and specific Supported with a clear rationale Directly connected to your research

  5. 7 Conclusions and Recommendations

    The conclusions and recommendations presented below reflect the most critical steps that the committee thinks should be taken to improve the state of health care in the home, based on the literature reviewed in this report examined through a human factors lens.

  6. 22 Writing the conclusion & recommendations

    22 Writing the conclusion & recommendations General There are probably some overlaps between the Conclusion and the Discussion section. Nevertheless, this section gives you the opportunity to highlight the most important points in your report, and is sometimes the only section read.

  7. Writing a Research Paper Conclusion

    Step 1: Restate the problem The first task of your conclusion is to remind the reader of your research problem. You will have discussed this problem in depth throughout the body, but now the point is to zoom back out from the details to the bigger picture.

  8. 6

    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. ... Like the conclusions, the recommendations may be open to debate. You may feel that, on the basis of your conclusions, the organization you ...

  9. How to Write a Thesis or Dissertation Conclusion

    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

  10. How to Write Recommendations in Research

    Here's an example. Recommendation setup example

  11. How to Write a Conclusion for Research Papers (with Examples)

    The research paper conclusion serves the following purposes: 1 Warn readers of the possible consequences of not attending to the problem. Recommend specific course (s) of action. Restate key ideas to drive home the ultimate point of your research paper. Provide a "take-home" message that you want the readers to remember about your study.

  12. PDF Chapter 5 Conclusions and recommendations

    5.1 INTRODUCTION In this chapter the conclusions derived from the findings of this study on the experiences of registered nurses involved in the termination of pregnancy at Soshanguve Community Health Centre are described. The conclusions were based on the purpose, research questions and results of the study.

  13. (Pdf) Chapter 5 Summary, Conclusions, Implications and Recommendations

    5.6 Recommendations for Further Studies This study has contributed to the understanding of students' values reflected in their language use in a blended learning environment.

  14. Summary, Conclusions, and Recommendations

    and inter-relatedness of environmental problems leads us to conclude that a new balance of research programs may be helpful. This report describes a framework for conducting research in a way that will help alleviate the problems of the moment while providing a basis for solving tomorrow's problems.

  15. Best Case Study Conclusion Guidelines For Students

    Example OF The Case Studies Conclusion Students can list what they have learned from this particular topic in their conclusion. It can make you wiser in comparison to the next applicant. For example, you can discuss any special category of the users related to the company you are conducting a case study on.

  16. Conclusions and recommendations for future research

    The initially stated overarching aim of this research was to identify the contextual factors and mechanisms that are regularly associated with effective and cost-effective public involvement in research. While recognising the limitations of our analysis, we believe we have largely achieved this in our revised theory of public involvement in research set out in Chapter 8. We have developed and ...

  17. Chapter 6 SUMMARY, CONCLUSIONS AND RECOMMENDATIONS

    Chapter 6 SUMMARY, CONCLUSIONS AND RECOMMENDATIONS Chapter: 6 Authors: Elock Emvula Shikalepo International University of Management, Namibia Abstract This Chapter provides an overview of the...

  18. Conclusions and recommendations

    The aim of this study was to explore the range and nature of influences on safety in decision-making by ambulance service staff (paramedics). A qualitative approach was adopted using a range of complementary methods. The study has provided insights on the types of decisions that staff engage in on a day-to-day basis. It has also identified a range of system risk factors influencing decisions ...

  19. (PDF) CHAPTER FIVE Summary, Conclusion and Recommendation

    Article Full-text available Efficacy of Rational Emotive Therapy in Remediating Proneness to Violent Behaviour among Secondary S... December 2020 Shehu Yahaya Tsagem The study investigated the...

  20. Conclusions-AND- Recommendations for case study

    Conclusion and recommendation for sample case study conclusions and recommendations conclusions: in terms of payback period, the planet karaoke pub is. Skip to document. University; ... Conclusion and recommendation for sample case study. Course. Fundamentals of Accountancy, Business and Management (ABM002) 296 Documents. Students shared 296 ...

  21. How to Write a Dissertation Conclusion

    Step 3: Make future recommendations. 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.. Example: Recommendation sentence. Based on these conclusions, practitioners should consider …

  22. Findings, Conclusions, and Recommendations

    Recommendation 1: Social scientists who are planning to add biological specimens to their survey research should familiarize themselves with existing best practices for the collection, storage, use, and distribution of biospecimens. First and foremost, the design of the protocol for collection must ensure the safety of both participants and survey staff (data and specimen collectors and handlers).

  23. Conclusion and recommendations

    In exploring how managers in health care encounter and apply management knowledge, our study has focused on three main aspects: management and leadership in the health-care context, knowledge, knowledge mobilisation and learning processes, and NoPs and CoPs. In this final chapter, we summarise our main conclusions in each of these areas, preceding this with a consideration of the effects of ...

  24. Full article: Perceptions of technology integration in algebra

    A descriptive case study is a research method that involves an in-depth and detailed examination of a particular individual, group, event, or situation. ... Recommendations. Based on the conclusions drawn from this study, the following recommendations can be made to support pre-service teachers in effectively integrating technology in algebra ...

  25. Learning Objectives Examples: How to Create High-Quality ...

    Teachers can easily connect with their students about the expected outcome of the course and learning objective examples by using this best PPT template. Explain the expectations for the course, the content that will be shared, the main learning objectives, and the required materials. Use This Template. 4.

  26. Downscaling Land Surface Temperature Derived from Microwave

    Optical sensors cannot penetrate clouds and can cause serious missing data problems in optical-based Land Surface Temperature (LST) products. Under cloudy conditions, microwave observations are usually utilized to derive the land surface temperature. However, microwave sensors usually have coarse spatial resolutions. High-Resolution (HR) LST data products are usually desired for many applications.

  27. How Machine Learning Will Transform Supply Chain Management

    The Problem. Flawed planning methods make it extremely difficult for companies to protect themselves against supply chain disruptions. A Remedy. A new approach, called optimal machine learning ...