case study aims to

Currigate is a software service that offers highly customizable subscription packages to banks, brokers, and investors in the mortgage lending market.

4. State the problem, consequences, & hesitations

Explain the issue the customer was facing or the goal they were having a hard time reaching—as well as the negative outcomes.

While this high level of customization is what sets Currigate apart from its competitors, it also requires multiple applications with disparate data and heavy manual work. Account owners were spending so much time manage invoicing, there was little left over to build relationships with clients, stay on top of overages, and upsell. This was leading to leaks in profitability and a weakening of customer service.

Include customer quotes as well as any hesitancies they had with using a product or service like yours.

“We were getting in our own way,” said Melanie Grigham, Currigate’s VP of Operations. “Our customer relationships were starting to falter, and we knew we had to do something. But the thought of manipulating just one of our data sources—let alone all seven—was scary. There were so many random connections in place and so much confidential information, we couldn’t risk it all breaking.”

5. Describe the solution

Share how the customer found your business and why they chose you.

Grigham learned about Kumbo Digital through none other than Google research and decided to get in touch. “The thought of explaining the whole thing felt daunting, but I was relieved to hear [the rep] finishing my sentences for me!”

Include which specific product or service they chose, how it was implemented, and how the customer used it. Stay brief!

After learning the details of the situation, the Kumbo team proposed a custom solution that would integrate all of the data sources into one dashboard. “I was hesitant at first, but they showed me a small scale example which helped me to understand a little more about how it would work. I appreciated their patience with me as I took some time to make a decision.” Grigham finally went with it. The dashboard took three weeks to implement and the data migration took just under a day.

6. Share the results & benefits

Share how the client used your product/service, what the results were, and the benefits. Include direct quotes and clear evidence (statistical data, before-and-after images, time-lapse videos, etc.)

With the new platform, Currigate’s account managers could access all seven data sources—as well as generate, track, send, and approve invoices—all in one place. Time spent invoicing went from days to hours, freeing up time for them to engage with customers and work toward strategic goals. “Our staff are less bogged down to the point where they’re asking to take on more clients—which is unheard of.” The redesigned and simplified product catalog (206 product codes instead of 1,024) has also made it easier for them to upsell as well as recommend combinations for specific needs. “Sometimes our new clients don’t know what they want, and this is perfect for giving them a starting point.” In addition, Currigate was able to identify $12,403 worth of overages they wouldn’t have caught otherwise. “Now, we can be sure that their customers are being billed appropriately (which is great for us) and receiving the services best fit for their dynamic needs (which is great for them). It’s a win-win.”

7. Conclude with words of advice and a CTA

Share where the client is headed, any additional quotes or praise, and/or their advice for similar potential clients.

Today, Currigate’s unique subscription model is as strong as ever. It’s even considering opening up to new markets. “We never thought we’d reach this point so soon—we thought new markets was years down the line,” said Melanie. When asked what advice she had for other businesses like hers, she talked about mixing faith and facts. “You’ve got to do your research to find a trusted provider, but at the end of the day, it all comes down to a leap of faith, and sometimes you just have to do it.”

Finish off with a CTA to contact your business and/or a link to view more case studies.

Tips on how to write a case study that prospects will want to read

Alright, so that was a basic example of a case study, but there’s more to it than just the words that comprise it. Here are eight tips to write a great case study that prospects will want to read and that will help close deals.

1. Make it as easy as possible for the client

Just like when asking for reviews , it’s important to make the process as clear and easy as possible for the client. When you reach out, ask if you can use their story of achievement as a case study for your business.

Make the details as clear as possible, including:

The clearer the picture you paint for them, the more receptive they’ll be to sharing their time with you.

2. Include a prominent snapshot with the results

While a good case study is like a story, you don’t want to hold out on your reader until the end. You want them to know the results right off the bat, then they can read further to find out how those results were achieved. In the example below, the overall picture is made clear with the title ( The Loot Box Uses Ad Factory and Content Marketing to Drive Sales ) and the three stats below it.

how to write a case study - make results clear

Image source

3. Choose an interesting angle

Apart from kitchen remodeling and website makeovers, it can be hard to make a case study compelling. But there is always room for creativity.

The more compelling your angle, the better the story. The better the story, the more engaging your case study will be. In Mailchimp’s case study example below, the customer name (Good Dye Young), compelling headline , and expressive image all work together to give this case study life.

4. But make it relatable to all prospects

Your angle is the “hook” that will catch your audience’s attention, but it’s essential that ALL prospects can relate to and identify with the problems encountered by your case study’s “protagonist.” This means catering to your core demographics and target markets , and solving the problems most commonly experienced by your customers.

The same Mailchimp case study example above finishes off with an “advice for other small businesses” section:

5. Make them visually appealing (and consistent)

We already know that case studies aren’t the most exciting reads, so don’t make it worse by throwing a bunch of text and numbers onto a page. A good case study is skimmable, visual, and organized.

6. Be the supporting character, not the hero

Your company should always be positioned as a helping hand that helped the real hero of the story—your client—overcome their obstacle. There are two reasons this approach is so effective. Firstly, you want your audience to visualize themselves as the protagonist of the case study. This is much more difficult if you won’t stop talking about how great your company or product is. Secondly, adopting a more humble tone can help increase your credibility in the mind of the reader.

how to write a case study - shopify examples

7. Let your clients tell their own story

As a storyteller, it’s your job to craft a compelling narrative about how your featured client triumphed over the forces of evil using your product or service, but that doesn’t mean your protagonist doesn’t have their own voice.

Let them tell the story in their own words and then incorporate direct quotes into your narrative. This will break up your text, increase credibility, and make your protagonist a tangible character that readers can relate to. Take an interview style format and use paraphrasing and annotations so the text isn’t repetitive. Set up the segue and create room for your client’s quote, and let them do the rest.

View the full case study example here.

8. Have realistic expectations

Yes, we want to create a useful, helpful resource for prospective customers, but let’s be real—nobody’s winning a Pulitzer for a case study, and it won’t be going viral on social media, no matter how well-written it is.

Case studies are little more than tools to be used by either self-motivated prospects researching your company, or by sales professionals as tools to help convince prospects to convert. Nothing more. They’re designed for audiences that are already strongly considering becoming your customers, which is a smaller but more qualified group of people than your general audience.

So don’t be disheartened if your case study content doesn’t attract as much traffic or engagement as your best or even average content. They’re not meant to. But that doesn’t mean you should stop creating them or start obsessing over how to improve them.

Business case study examples

Here are some business case study examples that put the tips in this guide into play.

Call us biased, but LOCALiQ’s case study format is pretty rad. What we like about it:

Read this case study example.

You saw a sneak peek of this above! What we like about it:

After the “Good Dye Young” example earlier, how could we not include another Mailchimp case study? What we like about it:

Wrike takes the case study snapshot to the next level in this example. What we like about it:

Our final marketing case study example comes from Slintel, a go-to-market intelligence software. What we like about it:

View full case study here

Marketing case study templates

To make things easy for you, I’ve compiled the tips and examples into a marketing case study template, in document form, that you can use to write your own.

Use these case study examples & tips to get started with your own

No two businesses are alike, and case studies vary widely in terms of style, tone, and format . One thing that all marketing case studies share, however, is their purpose – to convince prospects that doing business with you is a good idea. With these case study steps, tips, examples, and templates, you’ll be well on your way to producing stories your prospects will actually want to read.

Meet The Author

Kristen mccormick.

Kristen is the Senior Managing Editor at WordStream, where she helps businesses to make sense of their online marketing and advertising. She specializes in SEO and copywriting and finds life to be exponentially more delightful on a bicycle.

See other posts by Kristen McCormick

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The case study approach

BMC Medical Research Methodology volume 11 , Article number: 100 ( 2011 ) Cite this article

The case study approach allows in-depth, multi-faceted explorations of complex issues in their real-life settings. The value of the case study approach is well recognised in the fields of business, law and policy, but somewhat less so in health services research. Based on our experiences of conducting several health-related case studies, we reflect on the different types of case study design, the specific research questions this approach can help answer, the data sources that tend to be used, and the particular advantages and disadvantages of employing this methodological approach. The paper concludes with key pointers to aid those designing and appraising proposals for conducting case study research, and a checklist to help readers assess the quality of case study reports.

Peer Review reports

Introduction

The case study approach is particularly useful to employ when there is a need to obtain an in-depth appreciation of an issue, event or phenomenon of interest, in its natural real-life context. Our aim in writing this piece is to provide insights into when to consider employing this approach and an overview of key methodological considerations in relation to the design, planning, analysis, interpretation and reporting of case studies.

The illustrative 'grand round', 'case report' and 'case series' have a long tradition in clinical practice and research. Presenting detailed critiques, typically of one or more patients, aims to provide insights into aspects of the clinical case and, in doing so, illustrate broader lessons that may be learnt. In research, the conceptually-related case study approach can be used, for example, to describe in detail a patient's episode of care, explore professional attitudes to and experiences of a new policy initiative or service development or more generally to 'investigate contemporary phenomena within its real-life context' [ 1 ]. Based on our experiences of conducting a range of case studies, we reflect on when to consider using this approach, discuss the key steps involved and illustrate, with examples, some of the practical challenges of attaining an in-depth understanding of a 'case' as an integrated whole. In keeping with previously published work, we acknowledge the importance of theory to underpin the design, selection, conduct and interpretation of case studies[ 2 ]. In so doing, we make passing reference to the different epistemological approaches used in case study research by key theoreticians and methodologists in this field of enquiry.

This paper is structured around the following main questions: What is a case study? What are case studies used for? How are case studies conducted? What are the potential pitfalls and how can these be avoided? We draw in particular on four of our own recently published examples of case studies (see Tables 1 , 2 , 3 and 4 ) and those of others to illustrate our discussion[ 3 – 7 ].

What is a case study?

A case study is a research approach that is used to generate an in-depth, multi-faceted understanding of a complex issue in its real-life context. It is an established research design that is used extensively in a wide variety of disciplines, particularly in the social sciences. A case study can be defined in a variety of ways (Table 5 ), the central tenet being the need to explore an event or phenomenon in depth and in its natural context. It is for this reason sometimes referred to as a "naturalistic" design; this is in contrast to an "experimental" design (such as a randomised controlled trial) in which the investigator seeks to exert control over and manipulate the variable(s) of interest.

Stake's work has been particularly influential in defining the case study approach to scientific enquiry. He has helpfully characterised three main types of case study: intrinsic , instrumental and collective [ 8 ]. An intrinsic case study is typically undertaken to learn about a unique phenomenon. The researcher should define the uniqueness of the phenomenon, which distinguishes it from all others. In contrast, the instrumental case study uses a particular case (some of which may be better than others) to gain a broader appreciation of an issue or phenomenon. The collective case study involves studying multiple cases simultaneously or sequentially in an attempt to generate a still broader appreciation of a particular issue.

These are however not necessarily mutually exclusive categories. In the first of our examples (Table 1 ), we undertook an intrinsic case study to investigate the issue of recruitment of minority ethnic people into the specific context of asthma research studies, but it developed into a instrumental case study through seeking to understand the issue of recruitment of these marginalised populations more generally, generating a number of the findings that are potentially transferable to other disease contexts[ 3 ]. In contrast, the other three examples (see Tables 2 , 3 and 4 ) employed collective case study designs to study the introduction of workforce reconfiguration in primary care, the implementation of electronic health records into hospitals, and to understand the ways in which healthcare students learn about patient safety considerations[ 4 – 6 ]. Although our study focusing on the introduction of General Practitioners with Specialist Interests (Table 2 ) was explicitly collective in design (four contrasting primary care organisations were studied), is was also instrumental in that this particular professional group was studied as an exemplar of the more general phenomenon of workforce redesign[ 4 ].

What are case studies used for?

According to Yin, case studies can be used to explain, describe or explore events or phenomena in the everyday contexts in which they occur[ 1 ]. These can, for example, help to understand and explain causal links and pathways resulting from a new policy initiative or service development (see Tables 2 and 3 , for example)[ 1 ]. In contrast to experimental designs, which seek to test a specific hypothesis through deliberately manipulating the environment (like, for example, in a randomised controlled trial giving a new drug to randomly selected individuals and then comparing outcomes with controls),[ 9 ] the case study approach lends itself well to capturing information on more explanatory ' how ', 'what' and ' why ' questions, such as ' how is the intervention being implemented and received on the ground?'. The case study approach can offer additional insights into what gaps exist in its delivery or why one implementation strategy might be chosen over another. This in turn can help develop or refine theory, as shown in our study of the teaching of patient safety in undergraduate curricula (Table 4 )[ 6 , 10 ]. Key questions to consider when selecting the most appropriate study design are whether it is desirable or indeed possible to undertake a formal experimental investigation in which individuals and/or organisations are allocated to an intervention or control arm? Or whether the wish is to obtain a more naturalistic understanding of an issue? The former is ideally studied using a controlled experimental design, whereas the latter is more appropriately studied using a case study design.

Case studies may be approached in different ways depending on the epistemological standpoint of the researcher, that is, whether they take a critical (questioning one's own and others' assumptions), interpretivist (trying to understand individual and shared social meanings) or positivist approach (orientating towards the criteria of natural sciences, such as focusing on generalisability considerations) (Table 6 ). Whilst such a schema can be conceptually helpful, it may be appropriate to draw on more than one approach in any case study, particularly in the context of conducting health services research. Doolin has, for example, noted that in the context of undertaking interpretative case studies, researchers can usefully draw on a critical, reflective perspective which seeks to take into account the wider social and political environment that has shaped the case[ 11 ].

How are case studies conducted?

Here, we focus on the main stages of research activity when planning and undertaking a case study; the crucial stages are: defining the case; selecting the case(s); collecting and analysing the data; interpreting data; and reporting the findings.

Defining the case

Carefully formulated research question(s), informed by the existing literature and a prior appreciation of the theoretical issues and setting(s), are all important in appropriately and succinctly defining the case[ 8 , 12 ]. Crucially, each case should have a pre-defined boundary which clarifies the nature and time period covered by the case study (i.e. its scope, beginning and end), the relevant social group, organisation or geographical area of interest to the investigator, the types of evidence to be collected, and the priorities for data collection and analysis (see Table 7 )[ 1 ]. A theory driven approach to defining the case may help generate knowledge that is potentially transferable to a range of clinical contexts and behaviours; using theory is also likely to result in a more informed appreciation of, for example, how and why interventions have succeeded or failed[ 13 ].

For example, in our evaluation of the introduction of electronic health records in English hospitals (Table 3 ), we defined our cases as the NHS Trusts that were receiving the new technology[ 5 ]. Our focus was on how the technology was being implemented. However, if the primary research interest had been on the social and organisational dimensions of implementation, we might have defined our case differently as a grouping of healthcare professionals (e.g. doctors and/or nurses). The precise beginning and end of the case may however prove difficult to define. Pursuing this same example, when does the process of implementation and adoption of an electronic health record system really begin or end? Such judgements will inevitably be influenced by a range of factors, including the research question, theory of interest, the scope and richness of the gathered data and the resources available to the research team.

Selecting the case(s)

The decision on how to select the case(s) to study is a very important one that merits some reflection. In an intrinsic case study, the case is selected on its own merits[ 8 ]. The case is selected not because it is representative of other cases, but because of its uniqueness, which is of genuine interest to the researchers. This was, for example, the case in our study of the recruitment of minority ethnic participants into asthma research (Table 1 ) as our earlier work had demonstrated the marginalisation of minority ethnic people with asthma, despite evidence of disproportionate asthma morbidity[ 14 , 15 ]. In another example of an intrinsic case study, Hellstrom et al.[ 16 ] studied an elderly married couple living with dementia to explore how dementia had impacted on their understanding of home, their everyday life and their relationships.

For an instrumental case study, selecting a "typical" case can work well[ 8 ]. In contrast to the intrinsic case study, the particular case which is chosen is of less importance than selecting a case that allows the researcher to investigate an issue or phenomenon. For example, in order to gain an understanding of doctors' responses to health policy initiatives, Som undertook an instrumental case study interviewing clinicians who had a range of responsibilities for clinical governance in one NHS acute hospital trust[ 17 ]. Sampling a "deviant" or "atypical" case may however prove even more informative, potentially enabling the researcher to identify causal processes, generate hypotheses and develop theory.

In collective or multiple case studies, a number of cases are carefully selected. This offers the advantage of allowing comparisons to be made across several cases and/or replication. Choosing a "typical" case may enable the findings to be generalised to theory (i.e. analytical generalisation) or to test theory by replicating the findings in a second or even a third case (i.e. replication logic)[ 1 ]. Yin suggests two or three literal replications (i.e. predicting similar results) if the theory is straightforward and five or more if the theory is more subtle. However, critics might argue that selecting 'cases' in this way is insufficiently reflexive and ill-suited to the complexities of contemporary healthcare organisations.

The selected case study site(s) should allow the research team access to the group of individuals, the organisation, the processes or whatever else constitutes the chosen unit of analysis for the study. Access is therefore a central consideration; the researcher needs to come to know the case study site(s) well and to work cooperatively with them. Selected cases need to be not only interesting but also hospitable to the inquiry [ 8 ] if they are to be informative and answer the research question(s). Case study sites may also be pre-selected for the researcher, with decisions being influenced by key stakeholders. For example, our selection of case study sites in the evaluation of the implementation and adoption of electronic health record systems (see Table 3 ) was heavily influenced by NHS Connecting for Health, the government agency that was responsible for overseeing the National Programme for Information Technology (NPfIT)[ 5 ]. This prominent stakeholder had already selected the NHS sites (through a competitive bidding process) to be early adopters of the electronic health record systems and had negotiated contracts that detailed the deployment timelines.

It is also important to consider in advance the likely burden and risks associated with participation for those who (or the site(s) which) comprise the case study. Of particular importance is the obligation for the researcher to think through the ethical implications of the study (e.g. the risk of inadvertently breaching anonymity or confidentiality) and to ensure that potential participants/participating sites are provided with sufficient information to make an informed choice about joining the study. The outcome of providing this information might be that the emotive burden associated with participation, or the organisational disruption associated with supporting the fieldwork, is considered so high that the individuals or sites decide against participation.

In our example of evaluating implementations of electronic health record systems, given the restricted number of early adopter sites available to us, we sought purposively to select a diverse range of implementation cases among those that were available[ 5 ]. We chose a mixture of teaching, non-teaching and Foundation Trust hospitals, and examples of each of the three electronic health record systems procured centrally by the NPfIT. At one recruited site, it quickly became apparent that access was problematic because of competing demands on that organisation. Recognising the importance of full access and co-operative working for generating rich data, the research team decided not to pursue work at that site and instead to focus on other recruited sites.

Collecting the data

In order to develop a thorough understanding of the case, the case study approach usually involves the collection of multiple sources of evidence, using a range of quantitative (e.g. questionnaires, audits and analysis of routinely collected healthcare data) and more commonly qualitative techniques (e.g. interviews, focus groups and observations). The use of multiple sources of data (data triangulation) has been advocated as a way of increasing the internal validity of a study (i.e. the extent to which the method is appropriate to answer the research question)[ 8 , 18 – 21 ]. An underlying assumption is that data collected in different ways should lead to similar conclusions, and approaching the same issue from different angles can help develop a holistic picture of the phenomenon (Table 2 )[ 4 ].

Brazier and colleagues used a mixed-methods case study approach to investigate the impact of a cancer care programme[ 22 ]. Here, quantitative measures were collected with questionnaires before, and five months after, the start of the intervention which did not yield any statistically significant results. Qualitative interviews with patients however helped provide an insight into potentially beneficial process-related aspects of the programme, such as greater, perceived patient involvement in care. The authors reported how this case study approach provided a number of contextual factors likely to influence the effectiveness of the intervention and which were not likely to have been obtained from quantitative methods alone.

In collective or multiple case studies, data collection needs to be flexible enough to allow a detailed description of each individual case to be developed (e.g. the nature of different cancer care programmes), before considering the emerging similarities and differences in cross-case comparisons (e.g. to explore why one programme is more effective than another). It is important that data sources from different cases are, where possible, broadly comparable for this purpose even though they may vary in nature and depth.

Analysing, interpreting and reporting case studies

Making sense and offering a coherent interpretation of the typically disparate sources of data (whether qualitative alone or together with quantitative) is far from straightforward. Repeated reviewing and sorting of the voluminous and detail-rich data are integral to the process of analysis. In collective case studies, it is helpful to analyse data relating to the individual component cases first, before making comparisons across cases. Attention needs to be paid to variations within each case and, where relevant, the relationship between different causes, effects and outcomes[ 23 ]. Data will need to be organised and coded to allow the key issues, both derived from the literature and emerging from the dataset, to be easily retrieved at a later stage. An initial coding frame can help capture these issues and can be applied systematically to the whole dataset with the aid of a qualitative data analysis software package.

The Framework approach is a practical approach, comprising of five stages (familiarisation; identifying a thematic framework; indexing; charting; mapping and interpretation) , to managing and analysing large datasets particularly if time is limited, as was the case in our study of recruitment of South Asians into asthma research (Table 1 )[ 3 , 24 ]. Theoretical frameworks may also play an important role in integrating different sources of data and examining emerging themes. For example, we drew on a socio-technical framework to help explain the connections between different elements - technology; people; and the organisational settings within which they worked - in our study of the introduction of electronic health record systems (Table 3 )[ 5 ]. Our study of patient safety in undergraduate curricula drew on an evaluation-based approach to design and analysis, which emphasised the importance of the academic, organisational and practice contexts through which students learn (Table 4 )[ 6 ].

Case study findings can have implications both for theory development and theory testing. They may establish, strengthen or weaken historical explanations of a case and, in certain circumstances, allow theoretical (as opposed to statistical) generalisation beyond the particular cases studied[ 12 ]. These theoretical lenses should not, however, constitute a strait-jacket and the cases should not be "forced to fit" the particular theoretical framework that is being employed.

When reporting findings, it is important to provide the reader with enough contextual information to understand the processes that were followed and how the conclusions were reached. In a collective case study, researchers may choose to present the findings from individual cases separately before amalgamating across cases. Care must be taken to ensure the anonymity of both case sites and individual participants (if agreed in advance) by allocating appropriate codes or withholding descriptors. In the example given in Table 3 , we decided against providing detailed information on the NHS sites and individual participants in order to avoid the risk of inadvertent disclosure of identities[ 5 , 25 ].

What are the potential pitfalls and how can these be avoided?

The case study approach is, as with all research, not without its limitations. When investigating the formal and informal ways undergraduate students learn about patient safety (Table 4 ), for example, we rapidly accumulated a large quantity of data. The volume of data, together with the time restrictions in place, impacted on the depth of analysis that was possible within the available resources. This highlights a more general point of the importance of avoiding the temptation to collect as much data as possible; adequate time also needs to be set aside for data analysis and interpretation of what are often highly complex datasets.

Case study research has sometimes been criticised for lacking scientific rigour and providing little basis for generalisation (i.e. producing findings that may be transferable to other settings)[ 1 ]. There are several ways to address these concerns, including: the use of theoretical sampling (i.e. drawing on a particular conceptual framework); respondent validation (i.e. participants checking emerging findings and the researcher's interpretation, and providing an opinion as to whether they feel these are accurate); and transparency throughout the research process (see Table 8 )[ 8 , 18 – 21 , 23 , 26 ]. Transparency can be achieved by describing in detail the steps involved in case selection, data collection, the reasons for the particular methods chosen, and the researcher's background and level of involvement (i.e. being explicit about how the researcher has influenced data collection and interpretation). Seeking potential, alternative explanations, and being explicit about how interpretations and conclusions were reached, help readers to judge the trustworthiness of the case study report. Stake provides a critique checklist for a case study report (Table 9 )[ 8 ].

Conclusions

The case study approach allows, amongst other things, critical events, interventions, policy developments and programme-based service reforms to be studied in detail in a real-life context. It should therefore be considered when an experimental design is either inappropriate to answer the research questions posed or impossible to undertake. Considering the frequency with which implementations of innovations are now taking place in healthcare settings and how well the case study approach lends itself to in-depth, complex health service research, we believe this approach should be more widely considered by researchers. Though inherently challenging, the research case study can, if carefully conceptualised and thoughtfully undertaken and reported, yield powerful insights into many important aspects of health and healthcare delivery.

Yin RK: Case study research, design and method. 2009, London: Sage Publications Ltd., 4

Google Scholar

Keen J, Packwood T: Qualitative research; case study evaluation. BMJ. 1995, 311: 444-446.

Article CAS PubMed PubMed Central Google Scholar

Sheikh A, Halani L, Bhopal R, Netuveli G, Partridge M, Car J, et al: Facilitating the Recruitment of Minority Ethnic People into Research: Qualitative Case Study of South Asians and Asthma. PLoS Med. 2009, 6 (10): 1-11.

Article Google Scholar

Pinnock H, Huby G, Powell A, Kielmann T, Price D, Williams S, et al: The process of planning, development and implementation of a General Practitioner with a Special Interest service in Primary Care Organisations in England and Wales: a comparative prospective case study. Report for the National Co-ordinating Centre for NHS Service Delivery and Organisation R&D (NCCSDO). 2008, [ http://www.sdo.nihr.ac.uk/files/project/99-final-report.pdf ]

Robertson A, Cresswell K, Takian A, Petrakaki D, Crowe S, Cornford T, et al: Prospective evaluation of the implementation and adoption of NHS Connecting for Health's national electronic health record in secondary care in England: interim findings. BMJ. 2010, 41: c4564-

Pearson P, Steven A, Howe A, Sheikh A, Ashcroft D, Smith P, the Patient Safety Education Study Group: Learning about patient safety: organisational context and culture in the education of healthcare professionals. J Health Serv Res Policy. 2010, 15: 4-10. 10.1258/jhsrp.2009.009052.

Article PubMed Google Scholar

van Harten WH, Casparie TF, Fisscher OA: The evaluation of the introduction of a quality management system: a process-oriented case study in a large rehabilitation hospital. Health Policy. 2002, 60 (1): 17-37. 10.1016/S0168-8510(01)00187-7.

Stake RE: The art of case study research. 1995, London: Sage Publications Ltd.

Sheikh A, Smeeth L, Ashcroft R: Randomised controlled trials in primary care: scope and application. Br J Gen Pract. 2002, 52 (482): 746-51.

PubMed PubMed Central Google Scholar

King G, Keohane R, Verba S: Designing Social Inquiry. 1996, Princeton: Princeton University Press

Doolin B: Information technology as disciplinary technology: being critical in interpretative research on information systems. Journal of Information Technology. 1998, 13: 301-311. 10.1057/jit.1998.8.

George AL, Bennett A: Case studies and theory development in the social sciences. 2005, Cambridge, MA: MIT Press

Eccles M, the Improved Clinical Effectiveness through Behavioural Research Group (ICEBeRG): Designing theoretically-informed implementation interventions. Implementation Science. 2006, 1: 1-8. 10.1186/1748-5908-1-1.

Article PubMed Central Google Scholar

Netuveli G, Hurwitz B, Levy M, Fletcher M, Barnes G, Durham SR, Sheikh A: Ethnic variations in UK asthma frequency, morbidity, and health-service use: a systematic review and meta-analysis. Lancet. 2005, 365 (9456): 312-7.

Sheikh A, Panesar SS, Lasserson T, Netuveli G: Recruitment of ethnic minorities to asthma studies. Thorax. 2004, 59 (7): 634-

CAS PubMed PubMed Central Google Scholar

Hellström I, Nolan M, Lundh U: 'We do things together': A case study of 'couplehood' in dementia. Dementia. 2005, 4: 7-22. 10.1177/1471301205049188.

Som CV: Nothing seems to have changed, nothing seems to be changing and perhaps nothing will change in the NHS: doctors' response to clinical governance. International Journal of Public Sector Management. 2005, 18: 463-477. 10.1108/09513550510608903.

Lincoln Y, Guba E: Naturalistic inquiry. 1985, Newbury Park: Sage Publications

Barbour RS: Checklists for improving rigour in qualitative research: a case of the tail wagging the dog?. BMJ. 2001, 322: 1115-1117. 10.1136/bmj.322.7294.1115.

Mays N, Pope C: Qualitative research in health care: Assessing quality in qualitative research. BMJ. 2000, 320: 50-52. 10.1136/bmj.320.7226.50.

Mason J: Qualitative researching. 2002, London: Sage

Brazier A, Cooke K, Moravan V: Using Mixed Methods for Evaluating an Integrative Approach to Cancer Care: A Case Study. Integr Cancer Ther. 2008, 7: 5-17. 10.1177/1534735407313395.

Miles MB, Huberman M: Qualitative data analysis: an expanded sourcebook. 1994, CA: Sage Publications Inc., 2

Pope C, Ziebland S, Mays N: Analysing qualitative data. Qualitative research in health care. BMJ. 2000, 320: 114-116. 10.1136/bmj.320.7227.114.

Cresswell KM, Worth A, Sheikh A: Actor-Network Theory and its role in understanding the implementation of information technology developments in healthcare. BMC Med Inform Decis Mak. 2010, 10 (1): 67-10.1186/1472-6947-10-67.

Article PubMed PubMed Central Google Scholar

Malterud K: Qualitative research: standards, challenges, and guidelines. Lancet. 2001, 358: 483-488. 10.1016/S0140-6736(01)05627-6.

Article CAS PubMed Google Scholar

Yin R: Case study research: design and methods. 1994, Thousand Oaks, CA: Sage Publishing, 2

Yin R: Enhancing the quality of case studies in health services research. Health Serv Res. 1999, 34: 1209-1224.

Green J, Thorogood N: Qualitative methods for health research. 2009, Los Angeles: Sage, 2

Howcroft D, Trauth E: Handbook of Critical Information Systems Research, Theory and Application. 2005, Cheltenham, UK: Northampton, MA, USA: Edward Elgar

Book Google Scholar

Blakie N: Approaches to Social Enquiry. 1993, Cambridge: Polity Press

Doolin B: Power and resistance in the implementation of a medical management information system. Info Systems J. 2004, 14: 343-362. 10.1111/j.1365-2575.2004.00176.x.

Bloomfield BP, Best A: Management consultants: systems development, power and the translation of problems. Sociological Review. 1992, 40: 533-560.

Shanks G, Parr A: Positivist, single case study research in information systems: A critical analysis. Proceedings of the European Conference on Information Systems. 2003, Naples

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Acknowledgements

We are grateful to the participants and colleagues who contributed to the individual case studies that we have drawn on. This work received no direct funding, but it has been informed by projects funded by Asthma UK, the NHS Service Delivery Organisation, NHS Connecting for Health Evaluation Programme, and Patient Safety Research Portfolio. We would also like to thank the expert reviewers for their insightful and constructive feedback. Our thanks are also due to Dr. Allison Worth who commented on an earlier draft of this manuscript.

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Sarah Crowe & Anthony Avery

Centre for Population Health Sciences, The University of Edinburgh, Edinburgh, UK

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AS conceived this article. SC, KC and AR wrote this paper with GH, AA and AS all commenting on various drafts. SC and AS are guarantors.

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What is a Case Study? Definition and Method

Many students don’t know how to write a case study and find it a very difficult assignment even before getting started. Of course, it can be quite a challenging task but with the help of various recommendations and case study examples, you will be able to complete the assignment in a blink of an eye!

A case study is a task, which aims to teach the student how to analyze the causes and consequences of an event or activity by creating its role model. Such assignments show how complexities may influence various decisions and that is what makes case studies so important.

In most of the cases, your professor will give the same topic to a whole class and it will become a sort of a discussion, after processing all available data. That is why you need to use all of your thinking skills and knowledge to get a chance to analyze the situation properly.

How to Write a Case Study

Here are some recommendations, which will be helpful in completing a case study:

There are also a few problems you need to avoid to make your case study as interesting and catchy, as possible:

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Examples & Samples of Case Study

There are multiple ways of making the process of completing the assignment easier, including ordering a task at a writing service or asking other students for help. However, most of the students decide to download a case study template and try to complete the assignment on their own, using an example.

It can be a great option for those, who easily process information and can analyze the template structure to apply it in their own works. Such samples can be of a great help, as they contain a proper formatting style, content and other important elements, which distinguish a first-class paper. With the help of a sample case study you will be able to complete the assignment quicker and with less efforts.

This is only a sample, to get your own paper you need to:

Case Study Template and Format

You have already learned what a case study is and how it should look like, so it is time to learn more about the structure of assignment and its content. However, every research greatly differs depending on the topic, so you should carefully note down all the guidelines your professor provides not to miss anything.

Here is a general structure of a study, which can be applied in most of the cases:

When you complete such assignment, you should never forget about case study format, as it can greatly influence the result. Your professor may ask you to use a certain formatting style, which will be much easier for you and will help to avoid the most common mistakes.

Сase Study topics

The first challenge when writing a case study comes with choosing the best case study topics. As a rule, students are offers to pick the topic themselves. This is how instructors encourage them to express your understating of the subject as well as the entire course. Once you fail to generate the right case study ideas, benefit from our list of classical topics to start with:

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Descriptive Research | Definition, Types, Methods & Examples

Published on May 15, 2019 by Shona McCombes . Revised on October 10, 2022.

Descriptive research aims to accurately and systematically describe a population, situation or phenomenon. It can answer what , where , when and how questions , but not why questions.

A descriptive research design can use a wide variety of research methods to investigate one or more variables . Unlike in experimental research , the researcher does not control or manipulate any of the variables, but only observes and measures them.

When to use a descriptive research design, descriptive research methods.

Descriptive research is an appropriate choice when the research aim is to identify characteristics, frequencies, trends, and categories.

It is useful when not much is known yet about the topic or problem. Before you can research why something happens, you need to understand how, when and where it happens.

Descriptive research question examples

Descriptive research is usually defined as a type of quantitative research , though qualitative research can also be used for descriptive purposes. The research design should be carefully developed to ensure that the results are valid and reliable .

Survey research allows you to gather large volumes of data that can be analyzed for frequencies, averages and patterns. Common uses of surveys include:

Observations

Observations allow you to gather data on behaviours and phenomena without having to rely on the honesty and accuracy of respondents. This method is often used by psychological, social and market researchers to understand how people act in real-life situations.

Observation of physical entities and phenomena is also an important part of research in the natural sciences. Before you can develop testable hypotheses , models or theories, it’s necessary to observe and systematically describe the subject under investigation.

Case studies

A case study can be used to describe the characteristics of a specific subject (such as a person, group, event or organization). Instead of gathering a large volume of data to identify patterns across time or location, case studies gather detailed data to identify the characteristics of a narrowly defined subject.

Rather than aiming to describe generalizable facts, case studies often focus on unusual or interesting cases that challenge assumptions, add complexity, or reveal something new about a research problem .

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How to Analyse a Case Study

Last Updated: October 10, 2022 References

wikiHow is a “wiki,” similar to Wikipedia, which means that many of our articles are co-written by multiple authors. To create this article, 19 people, some anonymous, worked to edit and improve it over time. This article has been viewed 394,759 times. Learn more...

Case studies are used in many professional education programs, primarily in business school, to present real-world situations to students and to assess their ability to parse out the important aspects of a given dilemma. In general, a case study should include, in order: background on the business environment, description of the given business, identification of a key problem or issue, steps taken to address the issue, your assessment of that response, and suggestions for better business strategy. The steps below will guide you through the process of analyzing a business case study in this way.

Image titled Analyse a Case Study Step 1

Describe the nature of the organization under consideration and its competitors. Provide general information about the market and customer base. Indicate any significant changes in the business environment or any new endeavors upon which the business is embarking.

Image titled Analyse a Case Study Step 2

Analyze its management structure, employee base, and financial history. Describe annual revenues and profit. Provide figures on employment. Include details about private ownership, public ownership, and investment holdings. Provide a brief overview of the business's leaders and command chain.

Image titled Analyse a Case Study Step 3

In all likelihood, there will be several different factors at play. Decide which is the main concern of the case study by examining what most of the data talks about, the main problems facing the business, and the conclusions at the end of the study. Examples might include expansion into a new market, response to a competitor's marketing campaign, or a changing customer base. [4] X Research source

Image titled Analyse a Case Study Step 4

Draw on the information you gathered and trace a chronological progression of steps taken (or not taken). Cite data included in the case study , such as increased marketing spending, purchasing of new property, changed revenue streams, etc.

Image titled Analyse a Case Study Step 5

Indicate whether or not each aspect of the response met its goal and whether the response overall was well-crafted. Use numerical benchmarks, like a desired customer share, to show whether goals were met; analyze broader issues, like employee management policies, to talk about the response as a whole. [5] X Research source

Image titled Analyse a Case Study Step 6

Suggest alternative or improved measures that could have been taken by the business, using specific examples and backing up your suggestions with data and calculations.

Image titled Analyse a Case Study Step 7

Community Q&A

Do not use impassioned or emphatic language in your analysis. Business case studies are a tool for gauging your business acumen, not your personal beliefs. When assigning blame or identifying flaws in strategy, use a detached, disinterested tone. ⧼thumbs_response⧽ Helpful 15 Not Helpful 4

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Exploratory Data Analysis (EDA) – Credit Card Fraud Detection Case Study

This article was published as a part of the Data Science Blogathon .

Lots of financial losses are caused every year due to credit card fraud transactions, the financial industry has switched from a posterior investigation approach to an a priori predictive approach with the design of fraud detection algorithms to warn and help fraud investigators.

This case study is focused to give you an idea of applying Exploratory Data Analysis (EDA) in a real business scenario. In this case study, apart from applying the various Exploratory Data Analysis (EDA) techniques, you will also develop a basic understanding of risk analytics and understand how data can be utilized in order to minimise the risk of losing money while lending to customers.

Business Problem Understanding

The loan providing companies find it hard to give loans to people due to their inadequate or missing credit history. Some consumers use this to their advantage by becoming a defaulter. Let us consider your work for a consumer finance company that specialises in lending various types of loans to customers. You must use Exploratory Data Analysis (EDA) to analyse the patterns present in the data which will make sure that the loans are not rejected for the applicants capable of repaying.

When the company receives a loan application, the company has to rights for loan approval based on the applicant’s profile. Two types of risks are associated with the bank’s or company’s decision:

The data contains information about the loan application.

When a client applies for a loan, there are four types of decisions that could be taken by the bank/company:

Unused offer: The loan has been cancelled by the applicant but at different stages of the process.

In this case study, you will use Exploratory Data Analysis(EDA) to understand how consumer attributes and loan attributes impact the tendency of default.

Business Goal

This case study aims to identify patterns that indicate if an applicant will repay their instalments which may be used for taking further actions such as denying the loan, reducing the amount of loan, lending at a higher interest rate, etc. This will make sure that the applicants capable of repaying the loan are not rejected. Recognition of such aspirants using Exploratory Data Analysis (EDA) techniques is the main focus of this case study.

You can get access to data here.

Importing Necessary Packages

Here, we will use two datasets for our analysis as follows,

Let’s start with reading those files, we’ll start with df1,

Source: Author

Data Inspection

Before starting Exploratory Data Analysis (EDA) procedures we will start with inspecting the data.

Here, by giving verbose = True, it will give all the information about all the columns. Try it and see the results.

By describing (), you will get all the statistical information for the numeric columns and get an idea about their distribution and outliers.

Handling Null Values

After all the data inspecting, let’s check for the null values,

As you can see we are getting lots of null values. Let’s analyse this further.

Theoretically, 25 to 30% is the maximum missing values are allowed, beyond which we might want to drop the variable from analysis. But practically we get variables with ~50% of missing values but still, the customer insists to have it for analyzing. In those cases, we have to treat them accordingly. Here, we will remove columns with null values of more than 35% after observing those columns.

Let’s check how many columns are there with null values greater than 35%. And remove those.

After removing null values, check the percentage of null values for each column again.

Let’s handle these missing values by observing them.

Checking null values again after imputing null values.

We didn’t impute OCCUPATION_TYPE because it may contain some useful information, so imputing it with mean or median doesn’t make any sense.

We’ll impute ‘OCCUOATION_TYPE” later by analyzing it.

If you observe the columns carefully, you will find that some columns contain an error. So let’s make some changes.

If you see the data carefully, you will find that though these are days, it contains negative values which is not valid. So let’s make changes accordingly.

As you can see all the columns starts with DAYS, let’s make a list of columns we want to change for ease of change.

Some columns contain Y/N type of values, let’s make it 1/0 for ease of understanding.

Let’s check the distribution for columns having categorical values. After checking for all the columns, we get to know that some columns contain ‘XNA’ values which mean null. Let’s impute it accordingly.

Let’s impute these values. let’s check whether these values are missing at random or are there any pattern between missing values. You can read more about this here.

Here we observe that wherever NAME_INCOME_TYPE is Pensioner there only we have null values in ORGANIZATON_TYPE column.Let’s see count of Pensioner and then we’ll decide whether to impute null values of ORGANIZATION_TYPE with Pensioner or not.

We have some columns which have nominal categorical values. So let’s impute them accordingly. You can read more about this here.

Let’s Bin ‘DAYS_BIRTH’ column by converting it to years based on various “AGE_GROUP”

Again check the datatypes for all the columns and change them accordingly.

By checking the data types we found the following columns to change their data types.

After observing all the columns, we found some columns which don’t add any value to our analysis, so simply drop them so that the data looks clear.

Outlier Analysis

Outlier detection for any data science process is very important. Sometimes removing outliers tend to improve our model meanwhile sometimes outliers may give you a very different approach to your analysis.

So let’s make a list of all the numeric columns and plot boxplots to understand the outliers in the data.

You will get a 7×5 boxplot matrix. Let’s have a look at a very small portion.

Observe the plot and try to make your own insights.

Before we start analysing our data, let’s check the data imbalance. It’s a very important to step in any machine learning or deep learning process.

The Imbalance ratio we got is "11.39"

Let’s check the distribution of the target variable visually using a pie chart.

df1 dataframe that is application data is highly imbalanced. Defaulted population is 8.1 % and non- defaulted population is 91.9% .Ratio is 11.3

We will separately analyse the data based on the target variable for a better understanding.

Age Distribution | Exploratory Data Analysis

Organization’s Distribution Based on Target 0 and Target 1

Creating a plot for each feature manually becomes a too tedious task. So we will define a function and use a loop to iterate through each categorical column.

Let’s create a list for all categorical columns.

Most of the clients have applied for Cash Loan while very small proportion have applied for Revolving loan for both Defaulters as well as Non-defaulters.

Most of the clients were accompanied while applying for the loan.And with few clients a family member was accompanying for both Defaulters and Non-Defaulters. But who was accompanying client while applying for the loan doesn’t impact on the default.Also both the populations have same proportions.

Clients who applied for loans were getting income by Working,Commercial associate and Pensioner are more likely to apply for the loan, highest being the Working class category . Businessman, students and Unemployed less likely to apply for loan . Working category have high risk to default. State Servant is at Minimal risk to default.

Clients having education Secondary or Secondary Special are more likey to apply for the loan. Clients having education Secondary or Secondary Special have higher risk to default.Other education types have minimal risk.

Married Clients seems to be applied most for the loan compared to others for both Defaulters and Non-Defaulters. In case of Defaulters,Clients having single relationship are less risky In case of Defaulters, Widows shows Minimal risk .

From the bar chart, it is clear that Most of the clients own a house or living in a apartment for both Defaulters and Non-Defaulters.

Pensioners have applied the most for the loan in case of Defaulters and Non-Defaulters. Pensioner being highest followed by laborers have high risk to default.

There is no considerable difference in days for both Defaulters and Non-defaulters.

Clients having Medium salary range are more likely to apply for the loan for both Defaulters and Non-defaulters. Clients having low and medium income are at high risk to default.

Most of the clients applied for Medium Credit Amount of the loan for both Defaulters and Non-defaulters. Clients applying for high and low credit are at high risk of default.

Univariate Analysis of Numerical Columns W.R.T Target Variable

Bivariate Analysis: Numerical & Categorical W.R.T Target variables

Let’s check the required columns for analysis.

For Target 0

Bivariate Analysis of Categorical-Categorical to Find the Maximum % Clients with Loan-Payment Difficulties

Define a function for bivariate plots

Distribution of Amount Income Range and the category with maximum % Loan-Payment Difficulties

Distribution of Type of Income and the category with maximum Loan-Payment Difficulties

Distribution of Contract Type and the category with maximum Loan-Payment Difficulties

Distribution of Education Type and the category with maximum Loan-Payment Difficulties

Distribution of Housing Type and the category with maximum Loan-Payment Difficulties

Distribution of Occupation Type and the category with maximum Loan-Payment Difficulties

You may be wondering here why I haven’t attached screenshots here. Well, plot the charts and try to give insights based on that on your own. That’s the best way to learn.

Distribution of CODE_GENDER with respect to AMT_INCOME_RANGE to find maximum % Loan-Payment Difficulties using pivot table

Let’s check correlations in the data visually. For that make a list of all numeric features.

Correlations between numerical variables

Let’s use pairplot to get the required charts.

Now, let’s check correlations using heatmaps.

This is the analysis of current application data. We have one more data for the previous applications & have to analyse that also. Consider that data and do the analysis. Try to give insight s.

Now that we have understood and gained insight into the dataset ie performed an Exploratory Data Analysis, try to use ML algorithms to classify fraudulently. So let’s summarize what we have learnt in this case study,

Find the link to the source code here .

Hope you enjoyed my article on exploratory data analysis. Thank you for reading!

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About the Author

Kavita mali.

A Mathematics student turned Data Scientist. I am an aspiring data scientist who aims at learning all the necessary concepts in Data Science in detail. I am passionate about Data Science knowing data manipulation, data visualization, data analysis, EDA, Machine Learning, etc which will help to find valuable insights from the data.

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Published: 06 March 2023

The Use of the Constructivist Teaching Sequence (CTS) to Facilitate Changes in the Visual Representations of Fifth-Grade Elementary School Students: A Case Study on Teaching Heat Convection Concepts

International Journal of Science and Mathematics Education ( 2023 ) Cite this article

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Most primary school students, although they grasp the scientific concepts of heat convection at the macroscopic level, commonly fail to visualize those concepts. Therefore, our research aims to enact a constructivist teaching sequence (CTS) to restructure students’ visualization changes, ultimately enabling them to synergize macroscopic and sub-microscopic levels of understanding and visual representation. This study has employed a case study, combining qualitative and quantitative data to obtain an in-depth explanation. The quantitative data represent the percentage of the students’ visual representation category and their understanding of pattern changes before and after the intervention. Meanwhile, the ways students presented their thoughts about a concept based on their visual representation are presented via qualitative data. All data come from the participants, comprising 69 fifth-grade elementary school students at one public school in Indonesia. Our research findings show that students’ understanding of heat convection at both macroscopic and sub-microscopic levels improved to scientific conception, after undertaking the learning process using CTS. In addition, the use of CTS fostered a level of visual representation change regarding “construction” that dominated compared with other approaches: students shifted their visual representations from the varying styles of undefined drawing (UD), non-microscopic drawing (NMD), or no drawing (ND), to partial drawing (PD) and scientific drawing (SD).

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For supporting data can consider the appendixes and can refer to previous article made by author.

Anam, R. S., Widodo, A., Sopandi, W., & Wu, H.-K. (2019). Developing a five-tier diagnostic test to identify students’ misconceptions in science: An example of the heat transfer concepts. Elementary Education Online, 18 (3), 1014–1029. https://doi.org/10.17051/ilkonline.2019.609690

Ainsworth, S. (2008). The educational value of multiple-representations when learning complex scientific concepts. In J. K. Gilbert, M. Reiner, & M. Nakhleh (Eds.), Visualization: Theory and practice in science education. Models and modeling in science education (pp. 191–208). Springer. https://doi.org/10.1007/978-1-4020-5267-5_9

Ainsworth, S. (2010). Improving learning by drawing. Proceedings of the 9th International Conference of the Learning Sciences-Volume, 2 (c), 167–168.

Google Scholar

Ainsworth, S., Prain, V., & Tytler, R. (2011). Drawing to learn in science. Science, 333 (5977), 1096–1097. https://doi.org/10.1126/science.1204153

Article Google Scholar

Anderson, G., & Arsenault, N. (1998). Fundamentals of educational research (2nd ed.). Routledge. https://doi.org/10.4324/9780203978221

Bächtold, M. (2013). What do students “construct” according to constructivism in science education? Research in Science Education, 43 (6), 2477–2496. https://doi.org/10.1007/s11165-013-9369-7

Banda, A., Mumba, F., Chabalengula, V. M., & Mbewe, S. (2011). Teachers’ understanding of the particulate nature of matter: The case of Zambian pre-service science teachers. Asia-Pacific Forum on Science Learning and Teaching, 12 (2), 1–16.

Baviskar, S. N., Todd Hartle, R., & Whitney, T. (2009). Essential criteria to characterize constructivist teaching: Derived from a review of the literature and applied to five constructivist-teaching method articles. International Journal of Science Education, 31 (4), 541–550. https://doi.org/10.1080/09500690701731121

Beerenwinkel, A., & von Arx, M. (2017). Constructivism in practice: An exploratory study of teaching patterns and student motivation in physics classrooms in Finland, Germany and Switzerland. Research in Science Education, 47 (2), 237–255. https://doi.org/10.1007/s11165-015-9497-3

Boddy, N., Watson, K., & Aubusson, P. (2003). A trial of the five Es: A referent model for constructivist teaching and learning. Research in Science Education, 33 (1), 27–42. https://doi.org/10.1023/A:1023606425452

Boz, N., & Boz, Y. (2008). A qualitative case study of prospective chemistry teachers’ knowledge about instructional strategies: Introducing particulate theory. Journal of Science Teacher Education, 19 (2), 135–156. https://doi.org/10.1007/s10972-007-9087-y

Chang, W. (2005). Impact of constructivist teaching on students’ beliefs about teaching and learning in introductory physics. Canadian Journal of Science, Mathematics and Technology Education, 5 (1), 95–109. https://doi.org/10.1080/14926150509556646

Chi, M. T. H. (2008). Three types of conceptual change: Belief revision, mental model transformation, and categorical shift. In S. Vosniadou (Ed.), Handbook of research on conceptual change (pp. 61–82). Erlbaum.

Chiou, G. L. (2013). Reappraising the relationships between physics students’ mental models and predictions: An example of heat convection. Physical Review Special Topics - Physics Education Research, 9 (1), 1–15. https://doi.org/10.1103/PhysRevSTPER.9.010119

Clement, C. A. (2002). Learning with analogies, cases, and computers. Journal of the Learning Sciences, 11 (1), 127–138. https://doi.org/10.1207/S15327809JLS1101

Çoruhlu, T. Ş. (2017). Pre-service science teachers ’ conceptions of the “ conduction of heat in solids.” Journal of Baltic Science Education, 16 (2), 163–174.

Creswell, J. W., & Plano Clark, V. (2007). Designing and Conducting Mixed Methods Research . Sage.

Dikmenli, M. (2010). Misconceptions of cell division held by student teachers in biology: A drawing analysis. Scientific Research and Essays, 5 (2), 235–247. https://doi.org/10.1073/pnas.1306508110

diSessa, A. A., & Sherin, B. L. (1998). What changes in conceptual change? International Journal of Science Education, 20 (10), 1155–1191. https://doi.org/10.1080/0950069980201002

Duit, R., Widodo, A., & Wodzinski, C. T. (2007). Conceptual change ideas: Teachers’ views and their instructional practice. In S. Vosniadou, A. Baltas, & X. Vamvakoussi (Eds.), Reframing the conceptual change approach in learning and instruction (pp. 197–217). Elsevier Science.

Einarsdottir, J., Dockett, S., & Perry, B. (2009). Making meaning: Children’s perspectives expressed through drawings. Early Child Development and Care, 179 (2), 217–232. https://doi.org/10.1080/03004430802666999

Enyedy, N. (2005). Inventing mapping: Creating cultural forms to solve collective problems. Cognition and Instruction, 23 (4), 427–466. https://doi.org/10.1207/s1532690xci2304_1

Erickson, G. L. (1979). Children’s conceptions of heat and temperature. Science Education, 63 (2), 221–230.

Fiorella, L., & Zhang, Q. (2018). Drawing boundary conditions for learning by drawing. Educational Psychology Review, 30 (3), 1115–1137. https://doi.org/10.1007/s10648-018-9444-8

Glynn, S., & Muth, K. D. (2008). Using drawing strategically drawing activities make life science meaningful to third- and fourth-grade students. Science and Children, 45 , 48–51.

Guida, A., & Lavielle-Guida, M. (2014). 2011 Space Odyssey: Spatialization as a mechanism to code order allows a close encounter between memory expertise and classic immediate memory studies. Psychological Perspectives on Expertise, 5 (573), 176–189. https://doi.org/10.3389/fpsyg.2014.00573

Haney, W., Russell, M., & Bebell, D. (2004). Drawing on education: using drawings to document schooling and support change. Harvard Educational Review, 74 (3), 241–272. https://doi.org/10.17763/haer.74.3.w0817u84w7452011

Harrison, A. G., & Treagust, D. F. (2002). The particulate nature of matter: Challenges in understanding the submicroscopic world. Chemical Education: Towards Research-Based Practice, 17 , 189–212. https://doi.org/10.1007/0-306-47977-X_9

Iofciu, F., Miron, C., & Antohe, S. (2010). Interactive conceptual maps part of constructivist environment for advanced physics teaching. In Proceedings of The 5th International Conference on Virtual Learning, 1 (1), 95–100.

Izquierdo-Aymerich, M., & Adúriz-Bravo, A. (2003). Epistemological foundations of science education. Science & Education, 12 (1), 27–43.

Jansoon, N., Coll, R. K., & Somsook, E. (2009). Understanding mental models of dilution in Thai students. International Journal of Environment & Science Education, 4 (2), 147–168.

Johnstone, A. H. (1991). Why is science difficult to learn? Things are seldom what they seem. Journal of Computer Assisted Learning, 7 , 75–83. https://doi.org/10.1111/j.1365-2729.1991.tb00230.x

Kesidou, S., Duit, R., & Glynn, S. M. (1995). Conceptual development in physics: Students’ understanding of heat. In S. M. Glynn & R. Duit (Eds.), Learning science in the schools: Research reforming practice (pp. 179–198). Erlbaum.

Kozma, R., & Russell, J. (2005). Students becoming chemists: Developing representational competence. In J. K. Gilbert (Ed.), Visualization in science education. Models and modeling in science education (pp. 121–145). Springer. https://doi.org/10.1007/1-4020-3613-2_8

Krajcik, J. S., & Sutherland, L. M. (2010, April 23). Supporting students in developing literacy in science. Science, 328 , 456–459. https://doi.org/10.1126/science.1182593

Kuo, Y. R., Won, M., Zadnik, M., Siddiqui, S., & Treagust, D. F. (2017). Learning optics with multiple representations: Not as simple as expected. In D. Treagust, R. Duit, & H. Fischer (Eds.), Multiple representations in physics education. Models and modeling in science education (pp. 123–138). Springer. https://doi.org/10.1007/978-3-319-58914-5_6

Lewis, E. L., & Linn, M. C. U. C. B. (1994). Heat energy and temperature concepts of adolescents, adults, and experts. Journal of Research in Science Teaching, 31 (6), 657–677. https://doi.org/10.1002/tea.3660310607

Lin, J. W., Yen, M. H., Liang, J. C., Chiu, M. H., & Guo, C. J. (2016). Examining the factors that influence students’ science learning processes and their learning outcomes: 30 years of conceptual change research. Eurasia Journal of Mathematics, Science and Technology Education, 12 (9), 2617–2646. https://doi.org/10.12973/eurasia.2016.000600a

Martin, D. J. (2009). Elementary science methods: a constructivist approach (6th ed.). Cengage Learning.

Merino, C., & Sanmartí, N. (2008). How young children model chemical change. Chemistry Education Research and Practice, 9 (3), 196–207. https://doi.org/10.1039/b812408f

Nelson, P. G. (2002). Teaching chemistry progressively: From substances, to atoms and molecules, to electrons and nuclei. Chemical Education Research and Practice, 3 (2), 215–228. https://doi.org/10.1039/b2rp90017c

Opfermann, M., Schmeck, A., & Fischer, H. E. (2017). Multiple representations in physics and science education – Why should we use them?. In D. Treagust, R. Duit, & H. Fischer (Eds.), Multiple representations in physics education. Models and modeling in science education (pp. 1–22). Springer. https://doi.org/10.1007/978-3-319-58914-5_1

Park, M., Nam, Y., Moore, T., & Roehrig, G. (2011). The impact of integrating engineering into science learning on student’s conceptual understandings of the concept of heat transfer. Journal of the Korean Society of Earth Science Education, 4 (2), 89–101.

Posner, G. J., Strike, K. A., Hewson, P. W., & Gertzog, W. A. (1982). Accommodation of a scientific conception: Toward a theory of conceptual change. Science Education, 66 (2), 211–227. https://doi.org/10.1002/sce.3730660207

Quillin, K., & Thomas, S. (2015). Drawing-to-learn: A framework for using drawings to promote model-based reasoning in biology. CBE Life Sciences Education, 14 (1), 1–16. https://doi.org/10.1187/cbe.14-08-0128

Rau, M. A. (2017). Conditions for the effectiveness of multiple visual representations in enhancing STEM learning. Educational Psychology Review, 29 (4), 717–761. https://doi.org/10.1007/s10648-016-9365-3

Rule, A., & Furletti, C. (2004). Using form and function analogy object boxes to teach human body systems. School Science and Mathematics, 104 (4), 155–169. https://doi.org/10.1111/j.1949-8594.2004.tb18237.x

Schnittka, C., & Bell, R. (2011). Engineering design and conceptual change in science: Addressing thermal energy and heat transfer in eighth grade. International Journal of Science Education, 33 (13), 1861–1887. https://doi.org/10.1080/09500693.2010.529177

Selley, N. J. (2000). Students’ spontaneous use of a particulate model for dissolution. Research in Science Education, 30 (4), 389–402. https://doi.org/10.1007/BF02461558

Skamp, K. (Ed.). (1998). Teaching primary science constructively . Harcourt Publishers.

Taber, K. S. (2006). Beyond constructivism: The progressive research programme into learning science. Studies in Science Education, 42 (1), 125–184. https://doi.org/10.1080/03057260608560222

Talanquer, V. (2009). On cognitive constraints and learning progressions: The case of “structure of matter.” International Journal of Science Education, 31 (15), 2123–2136. https://doi.org/10.1080/09500690802578025

Tang, K. S., Delgado, C., & Moje, E. B. (2014). An integrative framework for the analysis of multiple and multimodal representations for meaning-making in science education. Science Education, 98 (2), 305–326. https://doi.org/10.1002/sce.21099

Tekos, G., & Solomonidou, C. (2009). Constructivist learning and teaching of optics concepts using ICT tools in Greek primary school: A pilot study. Journal of Science Education and Technology, 18 (5), 415–428. https://doi.org/10.1007/s10956-009-9158-2

Tippett, C. D. (2016). What recent research on diagrams suggests about learning with rather than learning from visual representations in science. International Journal of Science Education, 38 (5), 725–746. https://doi.org/10.1080/09500693.2016.1158435

Treagust, D. F., & Chittleborough, G. (2007). The modelling ability of non-major chemistry students and their understanding of the sub-microscopic level. Chemistry Education Research and Practice, 8 (3), 274–361.

Treagust, D. F., Chittleborough, G., & Mamiala, T. L. (2003). The role of submicroscopic and symbolic representations in chemical explanations. International Journal of Science Education, 25 (11), 1353–1368. https://doi.org/10.1080/0950069032000070306

Tuckey, H., & Selvaratnam, M. (1993). Studies involving three-dimensional visualisation skills in chemistry: A review. Studies in Science Education, 21 (1), 99–121. https://doi.org/10.1080/03057269308560015

Van Meter, P., & Garner, J. (2005). The promise and practice of learner-generated drawing: Literature review and synthesis. Educational Psychology Review, 17 (4), 285–325. https://doi.org/10.1007/s10648-005-8136-3

Vosniadou, S. (1994). Capturing and modeling the process of conceptual change. Learning and Instruction, 4 (1), 45–69. https://doi.org/10.1016/0959-4752(94)90018-3

Widodo, A. (2004). Constructivist oriented lesson: The learning enviroments and the teaching sequance . Peter Lang.

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Department of Primary Teacher Education, Universitas Terbuka, Tangerang Selatan, Indonesia

Rifat Shafwatul Anam

Department of Physics Education, Institut Pendidikan Indonesia, Garut, Indonesia

Surya Gumilar

Faculty of Mathematics and Science Education, Universitas Pendidikan Indonesia, Bandung, Indonesia

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Please see Table 7 .

Appendix 2. Heat convection question

Question: The main question about the conception.

Fiyya is conducting an experiment by heating water in a clear container which there is contains wood powder. The aim of this experiment is to know how the movement of water is represented by the movement of the wood powder. For more details, look at the picture below!

Macroscopic level

What will happen to that experiment?

The closest water with the heat source will rise and the far ones will be above it.

The closest water with the heat source will rise and the far ones will replace their positions.

The near and far water from the heat source will stay in its position or have no movement at all.

If you have your own answer, please write it here.

Sub-microscopic level

Why can it happen in that experiment?

The hotter water will have the same arrangement of particles with the cooler one and there are no changes in position in both water conditions.

The hotter water will have more dense particles or become heavier than cooler one; therefore, the particles of hot water will go down and cooler water will go up.

The hotter water will have more tenuous particles or become lighter than the cooler one, the result hot water will go up and cooler water will go down.

Visual representation

Based on your explanation, how do you draw the flow and particle of water at points A and B (in the circle provided) in that experiment?

Please see Table 8 .

Please see Table 9 .

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Anam, R.S., Gumilar, S. & Widodo, A. The Use of the Constructivist Teaching Sequence (CTS) to Facilitate Changes in the Visual Representations of Fifth-Grade Elementary School Students: A Case Study on Teaching Heat Convection Concepts. Int J of Sci and Math Educ (2023). https://doi.org/10.1007/s10763-023-10358-x

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