research design phd

Doctor of Design Program (DDes)

Professor Martin Bechthold advises students at Autodesk's BUILD Space in Boston.

The Doctor of Design (DDes) program at the Harvard Graduate School of Design is a leading doctoral degree program for highly creative and motivated professionals who wish to conduct rigorous, intensive design research.

The program is geared towards applied research that advances design related knowledge in a broad range of scales from product design to buildings and landscapes to urban design and regional planning. Common to the diverse range of DDes research investigations is the belief that design research makes essential contributions to understanding, analyzing and ultimately improving the built environment in our increasingly complex world.

DDes research is often multidisciplinary and encompasses a broad range and combination of theoretical, applied and technological topics that represent the cutting edge of applied design investigation. DDes research is intimately linked to ongoing investigations of the GSD’s research labs and programs that integrate many DDes students both intellectually and operationally as investigators in ongoing research projects.

Research topics are proposed during admission and are decided upon entry into the program. Student research should align with current faculty research interests, allowing for affiliations with faculty and, possibly, the research labs. Applicants are expected to clearly articulate their research topics in the application by submitting a concise and well-structured research proposal. Typical research areas include studies in urban design and theory, landscape urbanism, novel design techniques and technologies including material systems, design computation, and building technologies, planning and real estate studies, and theoretical investigations of emerging trends in digital design culture. Thesis topics investigate more specific issues within individual or combined research areas, and do not necessarily correspond to individual academic disciplines. Instead, they are often interdisciplinary in nature, involving faculty and resources from other graduate schools at Harvard and contribute to expanding the intellectual range of design research.

The DDes program is highly regarded internationally, and DDes alumni have become thought leaders in their respective fields. Their work promotes and advances improvements of the built and the natural environment worldwide. They hold prestigious positions in private practice, industry, government and academia.

We invite you to review the program details at left. Please feel free to  contact us for more information.

Ali Malkawi Professor of Architectural Technology Director of the Doctor of Design Studies Program Founding Director of the Harvard Center for Green Buildings and Cities

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• Knowledge Base
• Methodology

Research Design | Step-by-Step Guide with Examples

Published on 5 May 2022 by Shona McCombes . Revised on 20 March 2023.

A research design is a strategy for answering your research question  using empirical data. Creating a research design means making decisions about:

• Your overall aims and approach
• The type of research design you’ll use
• Your sampling methods or criteria for selecting subjects
• Your data collection methods
• The procedures you’ll follow to collect data
• Your data analysis methods

A well-planned research design helps ensure that your methods match your research aims and that you use the right kind of analysis for your data.

Table of contents

Step 1: consider your aims and approach, step 2: choose a type of research design, step 3: identify your population and sampling method, step 4: choose your data collection methods, step 5: plan your data collection procedures, step 6: decide on your data analysis strategies, frequently asked questions.

• Introduction

Before you can start designing your research, you should already have a clear idea of the research question you want to investigate.

There are many different ways you could go about answering this question. Your research design choices should be driven by your aims and priorities – start by thinking carefully about what you want to achieve.

The first choice you need to make is whether you’ll take a qualitative or quantitative approach.

Qualitative research designs tend to be more flexible and inductive , allowing you to adjust your approach based on what you find throughout the research process.

Quantitative research designs tend to be more fixed and deductive , with variables and hypotheses clearly defined in advance of data collection.

It’s also possible to use a mixed methods design that integrates aspects of both approaches. By combining qualitative and quantitative insights, you can gain a more complete picture of the problem you’re studying and strengthen the credibility of your conclusions.

Practical and ethical considerations when designing research

As well as scientific considerations, you need to think practically when designing your research. If your research involves people or animals, you also need to consider research ethics .

• How much time do you have to collect data and write up the research?
• Will you be able to gain access to the data you need (e.g., by travelling to a specific location or contacting specific people)?
• Do you have the necessary research skills (e.g., statistical analysis or interview techniques)?
• Will you need ethical approval ?

At each stage of the research design process, make sure that your choices are practically feasible.

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Within both qualitative and quantitative approaches, there are several types of research design to choose from. Each type provides a framework for the overall shape of your research.

Types of quantitative research designs

Quantitative designs can be split into four main types. Experimental and   quasi-experimental designs allow you to test cause-and-effect relationships, while descriptive and correlational designs allow you to measure variables and describe relationships between them.

With descriptive and correlational designs, you can get a clear picture of characteristics, trends, and relationships as they exist in the real world. However, you can’t draw conclusions about cause and effect (because correlation doesn’t imply causation ).

Experiments are the strongest way to test cause-and-effect relationships without the risk of other variables influencing the results. However, their controlled conditions may not always reflect how things work in the real world. They’re often also more difficult and expensive to implement.

Types of qualitative research designs

Qualitative designs are less strictly defined. This approach is about gaining a rich, detailed understanding of a specific context or phenomenon, and you can often be more creative and flexible in designing your research.

The table below shows some common types of qualitative design. They often have similar approaches in terms of data collection, but focus on different aspects when analysing the data.

Your research design should clearly define who or what your research will focus on, and how you’ll go about choosing your participants or subjects.

In research, a population is the entire group that you want to draw conclusions about, while a sample is the smaller group of individuals you’ll actually collect data from.

Defining the population

A population can be made up of anything you want to study – plants, animals, organisations, texts, countries, etc. In the social sciences, it most often refers to a group of people.

For example, will you focus on people from a specific demographic, region, or background? Are you interested in people with a certain job or medical condition, or users of a particular product?

The more precisely you define your population, the easier it will be to gather a representative sample.

Sampling methods

Even with a narrowly defined population, it’s rarely possible to collect data from every individual. Instead, you’ll collect data from a sample.

To select a sample, there are two main approaches: probability sampling and non-probability sampling . The sampling method you use affects how confidently you can generalise your results to the population as a whole.

Probability sampling is the most statistically valid option, but it’s often difficult to achieve unless you’re dealing with a very small and accessible population.

For practical reasons, many studies use non-probability sampling, but it’s important to be aware of the limitations and carefully consider potential biases. You should always make an effort to gather a sample that’s as representative as possible of the population.

Case selection in qualitative research

In some types of qualitative designs, sampling may not be relevant.

For example, in an ethnography or a case study, your aim is to deeply understand a specific context, not to generalise to a population. Instead of sampling, you may simply aim to collect as much data as possible about the context you are studying.

In these types of design, you still have to carefully consider your choice of case or community. You should have a clear rationale for why this particular case is suitable for answering your research question.

For example, you might choose a case study that reveals an unusual or neglected aspect of your research problem, or you might choose several very similar or very different cases in order to compare them.

Data collection methods are ways of directly measuring variables and gathering information. They allow you to gain first-hand knowledge and original insights into your research problem.

You can choose just one data collection method, or use several methods in the same study.

Survey methods

Surveys allow you to collect data about opinions, behaviours, experiences, and characteristics by asking people directly. There are two main survey methods to choose from: questionnaires and interviews.

Observation methods

Observations allow you to collect data unobtrusively, observing characteristics, behaviours, or social interactions without relying on self-reporting.

Observations may be conducted in real time, taking notes as you observe, or you might make audiovisual recordings for later analysis. They can be qualitative or quantitative.

Other methods of data collection

There are many other ways you might collect data depending on your field and topic.

If you’re not sure which methods will work best for your research design, try reading some papers in your field to see what data collection methods they used.

Secondary data

If you don’t have the time or resources to collect data from the population you’re interested in, you can also choose to use secondary data that other researchers already collected – for example, datasets from government surveys or previous studies on your topic.

With this raw data, you can do your own analysis to answer new research questions that weren’t addressed by the original study.

Using secondary data can expand the scope of your research, as you may be able to access much larger and more varied samples than you could collect yourself.

However, it also means you don’t have any control over which variables to measure or how to measure them, so the conclusions you can draw may be limited.

As well as deciding on your methods, you need to plan exactly how you’ll use these methods to collect data that’s consistent, accurate, and unbiased.

Planning systematic procedures is especially important in quantitative research, where you need to precisely define your variables and ensure your measurements are reliable and valid.

Operationalisation

Some variables, like height or age, are easily measured. But often you’ll be dealing with more abstract concepts, like satisfaction, anxiety, or competence. Operationalisation means turning these fuzzy ideas into measurable indicators.

If you’re using observations , which events or actions will you count?

If you’re using surveys , which questions will you ask and what range of responses will be offered?

You may also choose to use or adapt existing materials designed to measure the concept you’re interested in – for example, questionnaires or inventories whose reliability and validity has already been established.

Reliability and validity

Reliability means your results can be consistently reproduced , while validity means that you’re actually measuring the concept you’re interested in.

For valid and reliable results, your measurement materials should be thoroughly researched and carefully designed. Plan your procedures to make sure you carry out the same steps in the same way for each participant.

If you’re developing a new questionnaire or other instrument to measure a specific concept, running a pilot study allows you to check its validity and reliability in advance.

Sampling procedures

As well as choosing an appropriate sampling method, you need a concrete plan for how you’ll actually contact and recruit your selected sample.

That means making decisions about things like:

• How many participants do you need for an adequate sample size?
• What inclusion and exclusion criteria will you use to identify eligible participants?
• How will you contact your sample – by mail, online, by phone, or in person?

If you’re using a probability sampling method, it’s important that everyone who is randomly selected actually participates in the study. How will you ensure a high response rate?

If you’re using a non-probability method, how will you avoid bias and ensure a representative sample?

Data management

It’s also important to create a data management plan for organising and storing your data.

Will you need to transcribe interviews or perform data entry for observations? You should anonymise and safeguard any sensitive data, and make sure it’s backed up regularly.

Keeping your data well organised will save time when it comes to analysing them. It can also help other researchers validate and add to your findings.

On their own, raw data can’t answer your research question. The last step of designing your research is planning how you’ll analyse the data.

Quantitative data analysis

In quantitative research, you’ll most likely use some form of statistical analysis . With statistics, you can summarise your sample data, make estimates, and test hypotheses.

Using descriptive statistics , you can summarise your sample data in terms of:

• The distribution of the data (e.g., the frequency of each score on a test)
• The central tendency of the data (e.g., the mean to describe the average score)
• The variability of the data (e.g., the standard deviation to describe how spread out the scores are)

The specific calculations you can do depend on the level of measurement of your variables.

Using inferential statistics , you can:

• Make estimates about the population based on your sample data.
• Test hypotheses about a relationship between variables.

Regression and correlation tests look for associations between two or more variables, while comparison tests (such as t tests and ANOVAs ) look for differences in the outcomes of different groups.

Your choice of statistical test depends on various aspects of your research design, including the types of variables you’re dealing with and the distribution of your data.

Qualitative data analysis

In qualitative research, your data will usually be very dense with information and ideas. Instead of summing it up in numbers, you’ll need to comb through the data in detail, interpret its meanings, identify patterns, and extract the parts that are most relevant to your research question.

Two of the most common approaches to doing this are thematic analysis and discourse analysis .

There are many other ways of analysing qualitative data depending on the aims of your research. To get a sense of potential approaches, try reading some qualitative research papers in your field.

A sample is a subset of individuals from a larger population. Sampling means selecting the group that you will actually collect data from in your research.

For example, if you are researching the opinions of students in your university, you could survey a sample of 100 students.

Statistical sampling allows you to test a hypothesis about the characteristics of a population. There are various sampling methods you can use to ensure that your sample is representative of the population as a whole.

Operationalisation means turning abstract conceptual ideas into measurable observations.

For example, the concept of social anxiety isn’t directly observable, but it can be operationally defined in terms of self-rating scores, behavioural avoidance of crowded places, or physical anxiety symptoms in social situations.

Before collecting data , it’s important to consider how you will operationalise the variables that you want to measure.

The research methods you use depend on the type of data you need to answer your research question .

• If you want to measure something or test a hypothesis , use quantitative methods . If you want to explore ideas, thoughts, and meanings, use qualitative methods .
• If you want to analyse a large amount of readily available data, use secondary data. If you want data specific to your purposes with control over how they are generated, collect primary data.
• If you want to establish cause-and-effect relationships between variables , use experimental methods. If you want to understand the characteristics of a research subject, use descriptive methods.

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Shona McCombes

Research Design 101

Everything You Need To Get Started (With Examples)

By: Derek Jansen (MBA) | Reviewers: Eunice Rautenbach (DTech) & Kerryn Warren (PhD) | April 2023

Navigating the world of research can be daunting, especially if you’re a first-time researcher. One concept you’re bound to run into fairly early in your research journey is that of “ research design ”. Here, we’ll guide you through the basics using practical examples , so that you can approach your research with confidence.

Overview: Research Design 101

What is research design.

• Research design types for quantitative studies
• Video explainer : quantitative research design
• Research design types for qualitative studies
• Video explainer : qualitative research design
• How to choose a research design
• Key takeaways

Research design refers to the overall plan, structure or strategy that guides a research project , from its conception to the final data analysis. A good research design serves as the blueprint for how you, as the researcher, will collect and analyse data while ensuring consistency, reliability and validity throughout your study.

Understanding different types of research designs is essential as helps ensure that your approach is suitable  given your research aims, objectives and questions , as well as the resources you have available to you. Without a clear big-picture view of how you’ll design your research, you run the risk of potentially making misaligned choices in terms of your methodology – especially your sampling , data collection and data analysis decisions.

The problem with defining research design…

One of the reasons students struggle with a clear definition of research design is because the term is used very loosely across the internet, and even within academia.

Some sources claim that the three research design types are qualitative, quantitative and mixed methods , which isn’t quite accurate (these just refer to the type of data that you’ll collect and analyse). Other sources state that research design refers to the sum of all your design choices, suggesting it’s more like a research methodology . Others run off on other less common tangents. No wonder there’s confusion!

In this article, we’ll clear up the confusion. We’ll explain the most common research design types for both qualitative and quantitative research projects, whether that is for a full dissertation or thesis, or a smaller research paper or article.

Research Design: Quantitative Studies

Quantitative research involves collecting and analysing data in a numerical form. Broadly speaking, there are four types of quantitative research designs: descriptive , correlational , experimental , and quasi-experimental . 

Descriptive Research Design

As the name suggests, descriptive research design focuses on describing existing conditions, behaviours, or characteristics by systematically gathering information without manipulating any variables. In other words, there is no intervention on the researcher’s part – only data collection.

For example, if you’re studying smartphone addiction among adolescents in your community, you could deploy a survey to a sample of teens asking them to rate their agreement with certain statements that relate to smartphone addiction. The collected data would then provide insight regarding how widespread the issue may be – in other words, it would describe the situation.

The key defining attribute of this type of research design is that it purely describes the situation . In other words, descriptive research design does not explore potential relationships between different variables or the causes that may underlie those relationships. Therefore, descriptive research is useful for generating insight into a research problem by describing its characteristics . By doing so, it can provide valuable insights and is often used as a precursor to other research design types.

Correlational Research Design

Correlational design is a popular choice for researchers aiming to identify and measure the relationship between two or more variables without manipulating them . In other words, this type of research design is useful when you want to know whether a change in one thing tends to be accompanied by a change in another thing.

For example, if you wanted to explore the relationship between exercise frequency and overall health, you could use a correlational design to help you achieve this. In this case, you might gather data on participants’ exercise habits, as well as records of their health indicators like blood pressure, heart rate, or body mass index. Thereafter, you’d use a statistical test to assess whether there’s a relationship between the two variables (exercise frequency and health).

As you can see, correlational research design is useful when you want to explore potential relationships between variables that cannot be manipulated or controlled for ethical, practical, or logistical reasons. It is particularly helpful in terms of developing predictions , and given that it doesn’t involve the manipulation of variables, it can be implemented at a large scale more easily than experimental designs (which will look at next).

That said, it’s important to keep in mind that correlational research design has limitations – most notably that it cannot be used to establish causality . In other words, correlation does not equal causation . To establish causality, you’ll need to move into the realm of experimental design, coming up next…

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Experimental Research Design

Experimental research design is used to determine if there is a causal relationship between two or more variables . With this type of research design, you, as the researcher, manipulate one variable (the independent variable) while controlling others (dependent variables). Doing so allows you to observe the effect of the former on the latter and draw conclusions about potential causality.

For example, if you wanted to measure if/how different types of fertiliser affect plant growth, you could set up several groups of plants, with each group receiving a different type of fertiliser, as well as one with no fertiliser at all. You could then measure how much each plant group grew (on average) over time and compare the results from the different groups to see which fertiliser was most effective.

Overall, experimental research design provides researchers with a powerful way to identify and measure causal relationships (and the direction of causality) between variables. However, developing a rigorous experimental design can be challenging as it’s not always easy to control all the variables in a study. This often results in smaller sample sizes , which can reduce the statistical power and generalisability of the results.

Moreover, experimental research design requires random assignment . This means that the researcher needs to assign participants to different groups or conditions in a way that each participant has an equal chance of being assigned to any group (note that this is not the same as random sampling ). Doing so helps reduce the potential for bias and confounding variables . This need for random assignment can lead to ethics-related issues . For example, withholding a potentially beneficial medical treatment from a control group may be considered unethical in certain situations.

Quasi-Experimental Research Design

Quasi-experimental research design is used when the research aims involve identifying causal relations , but one cannot (or doesn’t want to) randomly assign participants to different groups (for practical or ethical reasons). Instead, with a quasi-experimental research design, the researcher relies on existing groups or pre-existing conditions to form groups for comparison.

For example, if you were studying the effects of a new teaching method on student achievement in a particular school district, you may be unable to randomly assign students to either group and instead have to choose classes or schools that already use different teaching methods. This way, you still achieve separate groups, without having to assign participants to specific groups yourself.

Naturally, quasi-experimental research designs have limitations when compared to experimental designs. Given that participant assignment is not random, it’s more difficult to confidently establish causality between variables, and, as a researcher, you have less control over other variables that may impact findings.

All that said, quasi-experimental designs can still be valuable in research contexts where random assignment is not possible and can often be undertaken on a much larger scale than experimental research, thus increasing the statistical power of the results. What’s important is that you, as the researcher, understand the limitations of the design and conduct your quasi-experiment as rigorously as possible, paying careful attention to any potential confounding variables .

Research Design: Qualitative Studies

There are many different research design types when it comes to qualitative studies, but here we’ll narrow our focus to explore the “Big 4”. Specifically, we’ll look at phenomenological design, grounded theory design, ethnographic design, and case study design.

Phenomenological Research Design

Phenomenological design involves exploring the meaning of lived experiences and how they are perceived by individuals. This type of research design seeks to understand people’s perspectives , emotions, and behaviours in specific situations. Here, the aim for researchers is to uncover the essence of human experience without making any assumptions or imposing preconceived ideas on their subjects.

For example, you could adopt a phenomenological design to study why cancer survivors have such varied perceptions of their lives after overcoming their disease. This could be achieved by interviewing survivors and then analysing the data using a qualitative analysis method such as thematic analysis to identify commonalities and differences.

Phenomenological research design typically involves in-depth interviews or open-ended questionnaires to collect rich, detailed data about participants’ subjective experiences. This richness is one of the key strengths of phenomenological research design but, naturally, it also has limitations. These include potential biases in data collection and interpretation and the lack of generalisability of findings to broader populations.

Grounded Theory Research Design

Grounded theory (also referred to as “GT”) aims to develop theories by continuously and iteratively analysing and comparing data collected from a relatively large number of participants in a study. It takes an inductive (bottom-up) approach, with a focus on letting the data “speak for itself”, without being influenced by preexisting theories or the researcher’s preconceptions.

As an example, let’s assume your research aims involved understanding how people cope with chronic pain from a specific medical condition, with a view to developing a theory around this. In this case, grounded theory design would allow you to explore this concept thoroughly without preconceptions about what coping mechanisms might exist. You may find that some patients prefer cognitive-behavioural therapy (CBT) while others prefer to rely on herbal remedies. Based on multiple, iterative rounds of analysis, you could then develop a theory in this regard, derived directly from the data (as opposed to other preexisting theories and models).

Grounded theory typically involves collecting data through interviews or observations and then analysing it to identify patterns and themes that emerge from the data. These emerging ideas are then validated by collecting more data until a saturation point is reached (i.e., no new information can be squeezed from the data). From that base, a theory can then be developed .

As you can see, grounded theory is ideally suited to studies where the research aims involve theory generation , especially in under-researched areas. Keep in mind though that this type of research design can be quite time-intensive , given the need for multiple rounds of data collection and analysis.

Ethnographic Research Design

Ethnographic design involves observing and studying a culture-sharing group of people in their natural setting to gain insight into their behaviours, beliefs, and values. The focus here is on observing participants in their natural environment (as opposed to a controlled environment). This typically involves the researcher spending an extended period of time with the participants in their environment, carefully observing and taking field notes .

All of this is not to say that ethnographic research design relies purely on observation. On the contrary, this design typically also involves in-depth interviews to explore participants’ views, beliefs, etc. However, unobtrusive observation is a core component of the ethnographic approach.

As an example, an ethnographer may study how different communities celebrate traditional festivals or how individuals from different generations interact with technology differently. This may involve a lengthy period of observation, combined with in-depth interviews to further explore specific areas of interest that emerge as a result of the observations that the researcher has made.

As you can probably imagine, ethnographic research design has the ability to provide rich, contextually embedded insights into the socio-cultural dynamics of human behaviour within a natural, uncontrived setting. Naturally, however, it does come with its own set of challenges, including researcher bias (since the researcher can become quite immersed in the group), participant confidentiality and, predictably, ethical complexities . All of these need to be carefully managed if you choose to adopt this type of research design.

Case Study Design

With case study research design, you, as the researcher, investigate a single individual (or a single group of individuals) to gain an in-depth understanding of their experiences, behaviours or outcomes. Unlike other research designs that are aimed at larger sample sizes, case studies offer a deep dive into the specific circumstances surrounding a person, group of people, event or phenomenon, generally within a bounded setting or context .

As an example, a case study design could be used to explore the factors influencing the success of a specific small business. This would involve diving deeply into the organisation to explore and understand what makes it tick – from marketing to HR to finance. In terms of data collection, this could include interviews with staff and management, review of policy documents and financial statements, surveying customers, etc.

While the above example is focused squarely on one organisation, it’s worth noting that case study research designs can have different variation s, including single-case, multiple-case and longitudinal designs. As you can see in the example, a single-case design involves intensely examining a single entity to understand its unique characteristics and complexities. Conversely, in a multiple-case design , multiple cases are compared and contrasted to identify patterns and commonalities. Lastly, in a longitudinal case design , a single case or multiple cases are studied over an extended period of time to understand how factors develop over time.

As you can see, a case study research design is particularly useful where a deep and contextualised understanding of a specific phenomenon or issue is desired. However, this strength is also its weakness. In other words, you can’t generalise the findings from a case study to the broader population. So, keep this in mind if you’re considering going the case study route.

How To Choose A Research Design

Having worked through all of these potential research designs, you’d be forgiven for feeling a little overwhelmed and wondering, “ But how do I decide which research design to use? ”. While we could write an entire post covering that alone, here are a few factors to consider that will help you choose a suitable research design for your study.

Data type: The first determining factor is naturally the type of data you plan to be collecting – i.e., qualitative or quantitative. This may sound obvious, but we have to be clear about this – don’t try to use a quantitative research design on qualitative data (or vice versa)!

Research aim(s) and question(s): As with all methodological decisions, your research aim and research questions will heavily influence your research design. For example, if your research aims involve developing a theory from qualitative data, grounded theory would be a strong option. Similarly, if your research aims involve identifying and measuring relationships between variables, one of the experimental designs would likely be a better option.

Time: It’s essential that you consider any time constraints you have, as this will impact the type of research design you can choose. For example, if you’ve only got a month to complete your project, a lengthy design such as ethnography wouldn’t be a good fit.

Resources: Take into account the resources realistically available to you, as these need to factor into your research design choice. For example, if you require highly specialised lab equipment to execute an experimental design, you need to be sure that you’ll have access to that before you make a decision.

Keep in mind that when it comes to research, it’s important to manage your risks and play as conservatively as possible. If your entire project relies on you achieving a huge sample, having access to niche equipment or holding interviews with very difficult-to-reach participants, you’re creating risks that could kill your project. So, be sure to think through your choices carefully and make sure that you have backup plans for any existential risks. Remember that a relatively simple methodology executed well generally will typically earn better marks than a highly-complex methodology executed poorly.

Recap: Key Takeaways

We’ve covered a lot of ground here. Let’s recap by looking at the key takeaways:

• Research design refers to the overall plan, structure or strategy that guides a research project, from its conception to the final analysis of data.
• Research designs for quantitative studies include descriptive , correlational , experimental and quasi-experimenta l designs.
• Research designs for qualitative studies include phenomenological , grounded theory , ethnographic and case study designs.
• When choosing a research design, you need to consider a variety of factors, including the type of data you’ll be working with, your research aims and questions, your time and the resources available to you.

If you need a helping hand with your research design (or any other aspect of your research), check out our private coaching services .

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Is there any blog article explaining more on Case study research design? Is there a Case study write-up template? Thank you.

Thanks this was quite valuable to clarify such an important concept.

Thanks for this simplified explanations. it is quite very helpful.

This was really helpful. thanks

Thank you for your explanation. I think case study research design and the use of secondary data in researches needs to be talked about more in your videos and articles because there a lot of case studies research design tailored projects out there.

Please is there any template for a case study research design whose data type is a secondary data on your repository?

This post is very clear, comprehensive and has been very helpful to me. It has cleared the confusion I had in regard to research design and methodology.

This post is helpful, easy to understand, and deconstructs what a research design is. Thanks

how to cite this page

Thank you very much for the post. It is wonderful and has cleared many worries in my mind regarding research designs. I really appreciate .

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How to Write a Research Design – Guide with Examples

Published by Alaxendra Bets at August 14th, 2021 , Revised On October 3, 2023

A research design is a structure that combines different components of research. It involves the use of different data collection and data analysis techniques logically to answer the  research questions .

It would be best to make some decisions about addressing the research questions adequately before starting the research process, which is achieved with the help of the research design.

Below are the key aspects of the decision-making process:

• Data type required for research
• Research resources
• Participants required for research
• Hypothesis based upon research question(s)
• Data analysis  methodologies
• Variables (Independent, dependent, and confounding)
• The location and timescale for conducting the data
• The time period required for research

The research design provides the strategy of investigation for your project. Furthermore, it defines the parameters and criteria to compile the data to evaluate results and conclude.

Your project’s validity depends on the data collection and  interpretation techniques.  A strong research design reflects a strong  dissertation , scientific paper, or research proposal .

Step 1: Establish Priorities for Research Design

Before conducting any research study, you must address an important question: “how to create a research design.”

The research design depends on the researcher’s priorities and choices because every research has different priorities. For a complex research study involving multiple methods, you may choose to have more than one research design.

Multimethodology or multimethod research includes using more than one data collection method or research in a research study or set of related studies.

If one research design is weak in one area, then another research design can cover that weakness. For instance, a  dissertation analyzing different situations or cases will have more than one research design.

For example:

• Experimental research involves experimental investigation and laboratory experience, but it does not accurately investigate the real world.
• Quantitative research is good for the  statistical part of the project, but it may not provide an in-depth understanding of the  topic .
• Also, correlational research will not provide experimental results because it is a technique that assesses the statistical relationship between two variables.

While scientific considerations are a fundamental aspect of the research design, It is equally important that the researcher think practically before deciding on its structure. Here are some questions that you should think of;

• Do you have enough time to gather data and complete the write-up?
• Will you be able to collect the necessary data by interviewing a specific person or visiting a specific location?
• Do you have in-depth knowledge about the  different statistical analysis and data collection techniques to address the research questions  or test the  hypothesis ?

If you think that the chosen research design cannot answer the research questions properly, you can refine your research questions to gain better insight.

Step 2: Data Type you Need for Research

Decide on the type of data you need for your research. The type of data you need to collect depends on your research questions or research hypothesis. Two types of research data can be used to answer the research questions:

Primary Data Vs. Secondary Data

Qualitative vs. quantitative data.

Also, see; Research methods, design, and analysis .

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• Hire an expert from ResearchProspect today!
• Statistical analysis, research methodology, discussion of the results or conclusion – our experts can help you no matter how complex the requirements are.

Step 3: Data Collection Techniques

Once you have selected the type of research to answer your research question, you need to decide where and how to collect the data.

It is time to determine your research method to address the  research problem . Research methods involve procedures, techniques, materials, and tools used for the study.

For instance, a dissertation research design includes the different resources and data collection techniques and helps establish your  dissertation’s structure .

The following table shows the characteristics of the most popularly employed research methods.

Research Methods

Step 4: Procedure of Data Analysis

Use of the  correct data and statistical analysis technique is necessary for the validity of your research. Therefore, you need to be certain about the data type that would best address the research problem. Choosing an appropriate analysis method is the final step for the research design. It can be split into two main categories;

Quantitative Data Analysis

The quantitative data analysis technique involves analyzing the numerical data with the help of different applications such as; SPSS, STATA, Excel, origin lab, etc.

This data analysis strategy tests different variables such as spectrum, frequencies, averages, and more. The research question and the hypothesis must be established to identify the variables for testing.

Qualitative Data Analysis

Qualitative data analysis of figures, themes, and words allows for flexibility and the researcher’s subjective opinions. This means that the researcher’s primary focus will be interpreting patterns, tendencies, and accounts and understanding the implications and social framework.

You should be clear about your research objectives before starting to analyze the data. For example, you should ask yourself whether you need to explain respondents’ experiences and insights or do you also need to evaluate their responses with reference to a certain social framework.

Step 5: Write your Research Proposal

The research design is an important component of a research proposal because it plans the project’s execution. You can share it with the supervisor, who would evaluate the feasibility and capacity of the results  and  conclusion .

Read our guidelines to write a research proposal  if you have already formulated your research design. The research proposal is written in the future tense because you are writing your proposal before conducting research.

The  research methodology  or research design, on the other hand, is generally written in the past tense.

How to Write a Research Design – Conclusion

A research design is the plan, structure, strategy of investigation conceived to answer the research question and test the hypothesis. The dissertation research design can be classified based on the type of data and the type of analysis.

Above mentioned five steps are the answer to how to write a research design. So, follow these steps to  formulate the perfect research design for your dissertation .

ResearchProspect writers have years of experience creating research designs that align with the dissertation’s aim and objectives. If you are struggling with your dissertation methodology chapter, you might want to look at our dissertation part-writing service.

Our dissertation writers can also help you with the full dissertation paper . No matter how urgent or complex your need may be, ResearchProspect can help. We also offer PhD level research paper writing services.

Frequently Asked Questions

What is research design.

Research design is a systematic plan that guides the research process, outlining the methodology and procedures for collecting and analysing data. It determines the structure of the study, ensuring the research question is answered effectively, reliably, and validly. It serves as the blueprint for the entire research project.

How to write a research design?

To write a research design, define your research question, identify the research method (qualitative, quantitative, or mixed), choose data collection techniques (e.g., surveys, interviews), determine the sample size and sampling method, outline data analysis procedures, and highlight potential limitations and ethical considerations for the study.

How to write the design section of a research paper?

In the design section of a research paper, describe the research methodology chosen and justify its selection. Outline the data collection methods, participants or samples, instruments used, and procedures followed. Detail any experimental controls, if applicable. Ensure clarity and precision to enable replication of the study by other researchers.

How to write a research design in methodology?

To write a research design in methodology, clearly outline the research strategy (e.g., experimental, survey, case study). Describe the sampling technique, participants, and data collection methods. Detail the procedures for data collection and analysis. Justify choices by linking them to research objectives, addressing reliability and validity.

You May Also Like

This article is a step-by-step guide to how to write statement of a problem in research. The research problem will be half-solved by defining it correctly.

Find how to write research questions with the mentioned steps required for a perfect research question. Choose an interesting topic and begin your research.

Make sure that your selected topic is intriguing, manageable, and relevant. Here are some guidelines to help understand how to find a good dissertation topic.

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Research Design Considerations

Associated data.

Editor's Note: The online version of this article contains references and resources for further reading and the authors' professional information.

The Challenge

“I'd really like to do a survey” or “Let's conduct some interviews” might sound like reasonable starting points for a research project. However, it is crucial that researchers examine their philosophical assumptions and those underpinning their research questions before selecting data collection methods. Philosophical assumptions relate to ontology, or the nature of reality, and epistemology, the nature of knowledge. Alignment of the researcher's worldview (ie, ontology and epistemology) with methodology (research approach) and methods (specific data collection, analysis, and interpretation tools) is key to quality research design. This Rip Out will explain philosophical differences between quantitative and qualitative research designs and how they affect definitions of rigorous research.

What Is Known

Worldviews offer different beliefs about what can be known and how it can be known, thereby shaping the types of research questions that are asked, the research approach taken, and ultimately, the data collection and analytic methods used. Ontology refers to the question of “What can we know?” Ontological viewpoints can be placed on a continuum: researchers at one end believe that an observable reality exists independent of our knowledge of it, while at the other end, researchers believe that reality is subjective and constructed, with no universal “truth” to be discovered. 1,2 Epistemology refers to the question of “How can we know?” 3 Epistemological positions also can be placed on a continuum, influenced by the researcher's ontological viewpoint. For example, the positivist worldview is based on belief in an objective reality and a truth to be discovered. Therefore, knowledge is produced through objective measurements and the quantitative relationships between variables. 4 This might include measuring the difference in examination scores between groups of learners who have been exposed to 2 different teaching formats, in order to determine whether a particular teaching format influenced the resulting examination scores.

In contrast, subjectivists (also referred to as constructionists or constructivists ) are at the opposite end of the continuum, and believe there are multiple or situated realities that are constructed in particular social, cultural, institutional, and historical contexts. According to this view, knowledge is created through the exploration of beliefs, perceptions, and experiences of the world, often captured and interpreted through observation, interviews, and focus groups. A researcher with this worldview might be interested in exploring the perceptions of students exposed to the 2 teaching formats, to better understand how learning is experienced in the 2 settings. It is crucial that there is alignment between ontology (what can we know?), epistemology (how can we know it?), methodology (what approach should be used?), and data collection and analysis methods (what specific tools should be used?). 5

Key Differences in Qualitative and Quantitative Approaches

Use of theory.

Quantitative approaches generally test theory, while qualitative approaches either use theory as a lens that shapes the research design or generate new theories inductively from their data. 4

Use of Logic

Quantitative approaches often involve deductive logic, starting off with general arguments of theories and concepts that result in data points. 4 Qualitative approaches often use inductive logic or both inductive and deductive logic, start with the data, and build up to a description, theory, or explanatory model. 4

Purpose of Results

Quantitative approaches attempt to generalize findings; qualitative approaches pay specific attention to particular individuals, groups, contexts, or cultures to provide a deep understanding of a phenomenon in local context. 4

Establishing Rigor

Quantitative researchers must collect evidence of validity and reliability. Some qualitative researchers also aim to establish validity and reliability. They seek to be as objective as possible through techniques, including cross-checking and cross-validating sources during observations. 6 Other qualitative researchers have developed specific frameworks, terminology, and criteria on which qualitative research should be evaluated. 6,7 For example, the use of credibility, transferability, dependability, and confirmability as criteria for rigor seek to establish the accuracy, trustworthiness, and believability of the research, rather than its validity and reliability. 8 Thus, the framework of rigor you choose will depend on your chosen methodology (see “Choosing a Qualitative Research Approach” Rip Out).

View of Objectivity

A goal of quantitative research is to maintain objectivity, in other words, to reduce the influence of the researcher on data collection as much as possible. Some qualitative researchers also attempt to reduce their own influence on the research. However, others suggest that these approaches subscribe to positivistic ideals, which are inappropriate for qualitative research, 6,9,10 as researchers should not seek to eliminate the effects of their influence on the study but to understand them through reflexivity . 11 Reflexivity is an acknowledgement that, to make sense of the social world, a researcher will inevitably draw on his or her own values, norms, and concepts, which prevent a totally objective view of the social world. 12

Sampling Strategies

Quantitative research favors using large, randomly generated samples, especially if the intent of the research is to generalize to other populations. 6 Instead, qualitative research often focuses on participants who are likely to provide rich information about the study questions, known as purposive sampling . 6

How You Can Start TODAY

• Consider how you can best address your research problem and what philosophical assumptions you are making.
• Consider your ontological and epistemological stance by asking yourself: What can I know about the phenomenon of interest? How can I know what I want to know? W hat approach should I use and why? Answers to these questions might be relatively fixed but should be flexible enough to guide methodological choices that best suit different research problems under study. 5
• Select an appropriate sampling strategy. Purposive sampling is often used in qualitative research, with a goal of finding information-rich cases, not to generalize. 6
• Be reflexive: Examine the ways in which your history, education, experiences, and worldviews have affected the research questions you have selected and your data collection methods, analyses, and writing. 13

How You Can Start TODAY—An Example

Let's assume that you want to know about resident learning on a particular clinical rotation. Your initial thought is to use end-of-rotation assessment scores as a way to measure learning. However, these assessments cannot tell you how or why residents are learning. While you cannot know for sure that residents are learning, consider what you can know—resident perceptions of their learning experiences on this rotation.

Next, you consider how to go about collecting this data—you could ask residents about their experiences in interviews or watch them in their natural settings. Since you would like to develop a theory of resident learning in clinical settings, you decide to use grounded theory as a methodology, as you believe asking residents about their experience using in-depth interviews is the best way for you to elicit the information you are seeking. You should also do more research on grounded theory by consulting related resources, and you will discover that grounded theory requires theoretical sampling. 14,15 You also decide to use the end-of-rotation assessment scores to help select your sample.

Since you want to know how and why students learn, you decide to sample extreme cases of students who have performed well and poorly on the end-of-rotation assessments. You think about how your background influences your standpoint about the research question: Were you ever a resident? How did you score on your end-of-rotation assessments? Did you feel this was an accurate representation of your learning? Are you a clinical faculty member now? Did your rotations prepare you well for this role? How does your history shape the way you view the problem? Seek to challenge, elaborate, and refine your assumptions throughout the research.

As you proceed with the interviews, they trigger further questions, and you then decide to conduct interviews with faculty members to get a more complete picture of the process of learning in this particular resident clinical rotation.

What You Can Do LONG TERM

• Familiarize yourself with published guides on conducting and evaluating qualitative research. 5,16–18 There is no one-size-fits-all formula for qualitative research. However, there are techniques for conducting your research in a way that stays true to the traditions of qualitative research.
• Consider the reporting style of your results. For some research approaches, it would be inappropriate to quantify results through frequency or numerical counts. 19 In this case, instead of saying “5 respondents reported X,” you might consider “respondents who reported X described Y.”
• Review the conventions and writing styles of articles published with a methodological approach similar to the one you are considering. If appropriate, consider using a reflexive writing style to demonstrate understanding of your own role in shaping the research. 6

Supplementary Material

The PhD in Interdisciplinary Design and Media offers an innovative, globally-aware, human-centered approach to advanced graduate study, focusing on practice-based research and scholarship applied to or conducted through making or creation.

The PhD in Interdisciplinary Design and Media is designed to foster the integration of creative collaboration across disciplinary boundaries, offering an opportunity for candidates seeking to break new ground and invent new fields. Further, the program is unique in its focus on integrating either practice-led or practice-based research and scholarship, which incorporates creative work into research either as part of a traditional research framework, or as applied to or conducted through making or creation itself. This integration of research and practice is an emerging area that has been applied internationally to a wide range of creative fields and industries, many of which are represented within CAMD: music, theatre, design, studio art, games, architecture, communication, media studies, and journalism, among others.

The program emphasizes the importance and value of engaging with the nature of human experience through innovative, interdisciplinary approaches to design; investigating new forms of digital media and data-driven communication across diverse disciplines; articulating how creativity can embrace connections between artistic practices, social and racial justice, entrepreneurship, and research; and connecting with changing forms of technology and media to foster shared experiences and exchange within local and global communities. The curriculum will cultivate a culture of research and creative practice dedicated to integrating data, technological, and human literacies to provide students with a vision and template for collaborating across disciplines while building the creative fields of the future.

The program is composed of three elements: a core, which offers a common set of design research methods to establish interdisciplinary interaction; a research path, which is a customized program of study; and a research/creative project and dissertation. Paths will take advantage of each student’s expertise and will blend approaches to design research, creative practice, and critical theory and will examine societal, humanistic and historic implications of each.

The PhD in Interdisciplinary Design and Media is unique in its focus on practice-based research and rigorously supports the creation of artifacts as a mode of producing new knowledge, theories, and methodologies – all in the context of an experiential learning environment. Students will step outside of academic boundaries to work on complex, real-world projects in interdisciplinary collaboration with diverse industries, including the creative sector; government, NGOs and the nonprofit sector; business analytics, computer science, and the natural sciences; arts, education and healthcare organizations; and the larger community. They will conduct research and learn from and collaborate with Northeastern’s world-class faculty on real-world, global challenges.

From our Professors:

“The world today needs transdisciplinary creative leaders who pave new ways of thinking and working that will show what the world of tomorrow will look like. The CAMD PhD program in Interdisciplinary Design and Media seeks to cultivate such thought leaders.” – Casper Harteveld, Associate Professor and Associate Dean of CAMD Graduate Studies

“The Interdisciplinary Design and Media PhD will provide hands-on learning experiences in artistic and creative cross-disciplinary research, giving practitioners in the arts the language and the research skills to delve into their chosen creative work at the PhD level.” – Psyche Loui, Associate Professor, Music

“The knowledge of artists and designers and their methods for creating it are becoming increasingly important in today’s society – we have built the Interdisciplinary Design and Media PhD around the “elastic rigor” of creative researchers and provide the tools to make their voices heard.” – Dietmar Offenhuber, Associate Professor and Interim Chair of Art + Design

“The Interdisciplinary Design and Media PhD is ideal for self-motivated forward thinkers who want to invent and forge new media, art, design and research practices through integrative blending and appropriation across disciplines. It values creative practice as a form of knowledge creation and provides a platform for people whose work defies categorization.” – Celia Pearce, Professor, Art + Design

“Big social challenges require creative, interdisciplinary solutions. The Interdisciplinary Design and Media PhD will train future leaders in the tools and creative practices to integrate data, technology, and design into solutions that improve the human experience.” – Brooke Foucault Welles, Associate Professor and Interim Chair of Communication Studies

The CAMD PhD in Interdisciplinary Design and Media supports practice-based research that is:

• Interdisciplinary: Transcending traditional disciplinary boundaries by merging, blending, and integrating theories, principles, methods, and techniques from across disciplines and domains
• Integrative: Cultivating creative practice as a rigorous method for producing new knowledge, theories, and methodologies, embodied through artifacts, performance, and texts
• Experiential: Incubating “living labs” embedded in real-world contexts, both on and off campus, with local, networked, and global partners
• Impactful: Generating research within real-world contexts resulting in meaningful social impact
• Engage with the nature of human experience through innovative, interdisciplinary approaches to design, media and arts.
• Investigate new forms of digital media and data-driven communication across diverse disciplines.
• Articulate how creativity can embrace connections between artistic practices, innovation, entrepreneurship, and research.
• Connect with changing forms of technology and media to foster shared experiences and exchange within local and global communities.
• Cultivate a research culture dedicated to developing human literacies for new media technologies and collaboration across and beyond the university.

Application Materials

• Completed online application form
• $100 application fee
• Three letters of recommendation
• Transcripts from all institutions attended
• Personal Statement
• 1 -3 Work Samples
• TOEFL, IELTS, or Duolingo for international applicants

Application

• Program Website

Request Information for PhD in Interdisciplinary Design and Media

How do I formulate the research design for my PhD thesis?

The research design must be done correctly otherwise the dissertation will not be successful. But how do I create a suitable research design for my topic? How can I even know that my approach is appropriate? How can I be sure that I will gain the right insight? Question after question. Here are the answers.

What is the research design anyway and why do I need it?

The research design is a detailed and systematic description of all steps needed to answer the research question. It shows your way of discovering new knowledge and consists of many elements. It helps to have the design handy when you start to organize your project. The more detailed the better and the more concrete your design, the easier it will be to implement.

What belongs in the research design?

• The research question, detailed questions and possibly hypotheses, the design of YOUR research model with relevant variables and factors
• Methods of data collection such as interviews, surveys, observations, documentations, measurements etc.,
• Decisions on the type of data, data sources and description of the samples,
• Tools for data collection such as interview guidelines or questionnaires etc.,
• Methods and tools for data evaluation such as statistical methods, content analysis etc.,
• Timetable for implementation.

When and how do I develop the appropriate research design?

You start with the design already in the proposal. This is your first draft. Prerequisites for the research design are the subject, research question and goal. They are your compass. You also need models on the topic for the classification of your variables and thus of the data. Here is an example: digitization in SMEs. How is digitization evolving inside SMEs? Operationalized research question: Which concepts do SMEs use when digitizing their business processes? You can create case studies and conduct an expert survey. You need models on SMEs, digitization and business processes. These models contain players, data, processes, activities, regulations, IT system and much more. Then you can collect data on the concrete concepts the SMEs studies used for digitization.

How do I check the research design for completeness and correctness?

Your design must meet 3 requirements:

• The methodology must definitely work and it must lead to an insight. A good test is whether the methods have already worked in other studies. Completely new methods are risky.
• The data must be obtainable, in quality and scope.
• The aids must be able to produce good results.

How do I test the research design?

• Simulate your research process. Are these the right detailed questions or sub questions?
• Do the answers to the detailed questions close the gap in research? Have I defined the correct data?
• Does this data match the objects in the detailed questions? Do I have the right data sources?
• Are there perhaps still better sources than the one I already found? Can the methods be used to evaluate the collected data?
• Has anyone ever described this in an article?
• How do I structure and describe the research design in the text?

Describe the research design in the text as a separate chapter in your dissertation.

To do so, you should answer about 20 questions. Here are the first so-called micro questions:

• What exactly is analyzed? Who or what is the focus of the analysis?
• What is the aim of the analysis? What insight will be gained?
• Which methods can be used for the analysis?
• What are the decision criteria for choosing a method?
• Why am I using a particular method?

Additional micro questions can be found in the 200 Days Dissertation Guide. Answer all these questions and your research design will be ready!

What sources do I need for the research design?

The best papers are those that have dealt with a related question. The methods are described there but are usually not comprehensive so you will also need method books. However, maybe an article is good but quite old. Don’t worry because methods are quite timeless. Papers on other issues are also interesting for the design if they have used certain suitable methods.

Method books are useful when it comes to the description. They are also more general and not just focused on one case.

How can I tell that my research design is "complete"?

The design is complete when the questions in the chapter ‘Research Design’ are answered and your supervisor knows the procedure and considers it useful. Actually this question is only finally answered when you have collected and evaluated all the data. Until then, minor changes in your research design are still necessary.

How do I work with the research design?

Just go for it! That's it! Let's go! Good luck writing your text!

Silvio and the Aristolo Team

PS: Check out the PhD Guide for writing a PhD in 200 days .

• Schools & departments

Design PhD, MPhil

Awards: PhD, MPhil

Study modes: Part-time, Full-time

Funding opportunities

Programme website: Design

PhD by Distance online session

Edinburgh College of Art are hosting a session on the PhD by Distance option on Wednesday 22 May during the Online Learning Open Days.

Register now

Introduction to Postgraduate Research

Join us online on 19 June to learn about applying for and studying a research degree at Edinburgh.

Find out more and register

Research profile

Design research is part of a dynamic and supportive environment within a vibrant community of world-class research. Design research integrates practice and theory within a dynamic and supportive environment. It connects across disciplines and research initiatives to support doctoral study within a vibrant community of world-class research. The range of subjects possible is vast and includes but is not limited to:

• Design anthropology
• Design history and theory
• Methodological development
• Design informatics
• Design for healthcare and wellbeing
• Design management
• Craft studies
• Service design
• Design for change (transition and transformation)
• Cultural and heritage studies
• Sustainability and the circular economy
• Design Cultures
• Design and Digital Media

You will also be supported through our practice specialisms (in theory or practice) in:

• Film and television
• Graphic design
• Illustration
• Performance costume
• Product design
• Screen studies (film and animation)
• Silversmithing

Programme structure

You can undertake the Design MPhil or PhD programme either as a practice-based programme of research, or theory based. And it is possible to change between approaches during your programme of study.

The PhD programme comprises three years of full-time (six years part-time) research under the supervision of an expert in your chosen research topic within Design. If you study by theory then the period of research culminates in a supervised thesis of up to a maximum of 100,000 words. For the practice-based approach your research would culminate in a portfolio of artefacts or artworks which would be accompanied by a thesis of up to a maximum of 50,000 words.

The MPhil programme comprises two years of full-time (four years part-time) research under the supervision of an expert in your chosen research topic within Design. If you study by theory then the period of research culminates in a supervised thesis of up to a maximum of 60,000 words. For the practice-based approach your research would culminate in a portfolio of artefacts or artworks which should be accompanied by a thesis of up to a maximum of 20,000 words.

Regular individual meetings with your supervisor provide guidance and focus for the course of research you are undertaking.

You will be encouraged to attend research methods courses at the beginning of your research studies.

And for every year you are enrolled on programme you will be required to complete an annual progression review.

Training and support

All of our research students benefit from Edinburgh College of Art's interdisciplinary approach, and you will be assigned at least two research supervisors.

Your first/ lead supervisor would normally be based in the same subject area as your degree programme. Your second supervisor may be from another discipline within Edinburgh College of Art or elsewhere within the University of Edinburgh, according to the expertise required. On occasion more than two supervisors will be assigned, particularly where the degree brings together multiple disciplines.

Our research culture is supported by seminars and public lecture programmes and discussion groups.

Tutoring opportunities will be advertised to the postgraduate research community, which you can apply for should you wish to gain some teaching experience during your studies. But you are not normally advised to undertake tutoring work in the first year of your research studies, while your main focus should be on establishing the direction of your research.

You are encouraged to attend courses at the Institute for Academic Development ( IAD ), where all staff and students at the University of Edinburgh are supported through a range of training opportunities, including:

• short courses in compiling literature reviews
• writing in a second language
• preparing for your viva

The Scottish Graduate School for Arts and Humanities ( SGSAH ) offers further opportunities for development. You will also be encouraged to refer to the Vitae research development framework as you grow into a professional researcher.

You will have access to study space (some of which are 24-hour access), studios and workshops at Edinburgh College of Art’s campus, as well as University wide resources. There are several bookable spaces for the development of exhibitions, workshops or seminars. And you will have access to well-equipped multimedia laboratories, photography and exhibition facilities, shared recording space, access to recording equipment available through Bookit the equipment loan booking system.

You will have access to high quality library facilities. Within the University of Edinburgh, there are three libraries; the Main Library, the ECA library and the Art and Architecture Library. The Centre for Research Collections which holds the University of Edinburgh’s historic collections is also located in the Main Library.

The Talbot Rice Gallery is a public art gallery of the University of Edinburgh and part of Edinburgh College of Art, which is committed to exploring what the University of Edinburgh can contribute to contemporary art practice today and into the future. You will also have access to the extraordinary range and quality of exhibitions and events associated with a leading college of art situated within a world-class research-intensive University.

St Cecilia’s Hall which is Scotland’s oldest purpose-built concert hall also houses the Music Museum which holds one of the most important historic musical instrument collections anywhere in the world.

In addition to the University’s facilities you will also be able to access wider resources within the City of Edinburgh. Including but not limited to; National Library of Scotland, Scottish Studies Library and Digital Archives, City of Edinburgh Libraries, Historic Environment Scotland and the National Trust for Scotland.

You will also benefit from the University of Edinburgh’s extensive range of student support facilities provided, including student societies, accommodation, wellbeing and support services.

PhD by Distance option

The PhD by Distance is available to suitably qualified applicants in all the same areas as our on-campus programmes.

The PhD by Distance allows students who do not wish to commit to basing themselves in Edinburgh to study for a PhD in an ECA subject area from their home country or city.

There is no expectation that students studying for an ECA PhD by Distance study mode should visit Edinburgh during their period of study. However, short term visits for particular activities could be considered on a case-by-case basis.

• For further information on the PhD by Distance, please see the ECA website

Entry requirements

These entry requirements are for the 2024/25 academic year and requirements for future academic years may differ. Entry requirements for the 2025/26 academic year will be published on 1 Oct 2024.

Normally a UK 2:1 honours degree or its international equivalent. If you do not meet the academic entry requirements, we may still consider your application on the basis of relevant professional experience.

You must also submit a research proposal; see How to Apply section for guidance.

If your research is practice-based a portfolio should also be submitted; see How to Apply section for guidance.

International qualifications

Check whether your international qualifications meet our general entry requirements:

• Entry requirements by country
• English language requirements

Regardless of your nationality or country of residence, you must demonstrate a level of English language competency at a level that will enable you to succeed in your studies.

English language tests

We accept the following English language qualifications at the grades specified:

• IELTS Academic: total 7.0 with at least 6.0 in each component. We do not accept IELTS One Skill Retake to meet our English language requirements.
• TOEFL-iBT (including Home Edition): total 100 with at least 20 in each component. We do not accept TOEFL MyBest Score to meet our English language requirements.
• C1 Advanced ( CAE ) / C2 Proficiency ( CPE ): total 185 with at least 169 in each component.
• Trinity ISE : ISE III with passes in all four components.
• PTE Academic: total 70 with at least 59 in each component.

Your English language qualification must be no more than three and a half years old from the start date of the programme you are applying to study, unless you are using IELTS , TOEFL, Trinity ISE or PTE , in which case it must be no more than two years old.

Degrees taught and assessed in English

We also accept an undergraduate or postgraduate degree that has been taught and assessed in English in a majority English speaking country, as defined by UK Visas and Immigration:

• UKVI list of majority English speaking countries

We also accept a degree that has been taught and assessed in English from a university on our list of approved universities in non-majority English speaking countries (non-MESC).

• Approved universities in non-MESC

If you are not a national of a majority English speaking country, then your degree must be no more than five years old* at the beginning of your programme of study. (*Revised 05 March 2024 to extend degree validity to five years.)

Find out more about our language requirements:

Fees and costs

Tuition fees, scholarships and funding, featured funding.

• Edinburgh College of Art scholarships

UK government postgraduate loans

If you live in the UK, you may be able to apply for a postgraduate loan from one of the UK’s governments.

The type and amount of financial support you are eligible for will depend on:

• your programme
• the duration of your studies
• your tuition fee status

Programmes studied on a part-time intermittent basis are not eligible.

• UK government and other external funding

Other funding opportunities

Search for scholarships and funding opportunities:

• Search for funding

Further information

• Edinburgh College of Art Postgraduate Research Team
• Phone: +44 (0)131 651 5741
• Contact: [email protected]
• Postgraduate Research Director, Design, Dr Craig Martin
• Contact: [email protected]
• Edinburgh College of Art Postgraduate Office Student and Academic Support Service
• The University of Edinburgh
• Evolution House, 78 West Port
• Central Campus
• Programme: Design
• School: Edinburgh College of Art
• College: Arts, Humanities & Social Sciences

Select your programme and preferred start date to begin your application.

PhD Design by Distance - 6 Years (Part-time)

Phd design by distance - 3 years (full-time), phd design - 3 years (full-time), phd design - 6 years (part-time), mphil design - 2 years (full-time), mphil design - 4 years (part-time), application deadlines.

If you are applying for funding or will require a visa then we strongly recommend you apply as early as possible. All applications must be received by the deadlines listed above.

• How to apply

You must submit two references with your application.

One of your references must be an academic reference and preferably from your most recent studies.

You should submit a research proposal that outlines your project's aims, context, process and product/outcome. Read the application guidance before you apply. If you wish to undertake research that involves practice then a portfolio will also be required, full details are listed in the application guidance document.

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• Developing the Quantitative Research Design
• Qualitative Descriptive Design
• Design and Development Research (DDR) For Instructional Design
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• Action Research Resource
• Case Study Design in an Applied Doctorate

Qualitative Research Designs

Case study design, using case study design in the applied doctoral experience (ade), applicability of case study design to applied problem of practice, case study design references.

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The field of qualitative research there are a number of research designs (also referred to as “traditions” or “genres”), including case study, phenomenology, narrative inquiry, action research, ethnography, grounded theory, as well as a number of critical genres including Feminist theory, indigenous research, critical race theory and cultural studies. The choice of research design is directly tied to and must be aligned with your research problem and purpose. As Bloomberg & Volpe (2019) explain:

Choice of research design is directly tied to research problem and purpose. As the researcher, you actively create the link among problem, purpose, and design through a process of reflecting on problem and purpose, focusing on researchable questions, and considering how to best address these questions. Thinking along these lines affords a research study methodological congruence (p. 38).

Case study is an in-depth exploration from multiple perspectives of a bounded social phenomenon, be this a social system such as a program, event, institution, organization, or community (Stake, 1995, 2005; Yin, 2018). Case study is employed across disciplines, including education, health care, social work, sociology, and organizational studies. The purpose is to generate understanding and deep insights to inform professional practice, policy development, and community or social action (Bloomberg 2018).

Yin (2018) and Stake (1995, 2005), two of the key proponents of case study methodology, use different terms to describe case studies. Yin categorizes case studies as exploratory or descriptive . The former is used to explore those situations in which the intervention being evaluated has no clear single set of outcomes. The latter is used to describe an intervention or phenomenon and the real-life context in which it occurred. Stake identifies case studies as intrinsic or instrumental , and he proposes that a primary distinction in designing case studies is between single and multiple (or collective) case study designs. A single case study may be an instrumental case study (research focuses on an issue or concern in one bounded case) or an intrinsic case study (the focus is on the case itself because the case presents a unique situation). A longitudinal case study design is chosen when the researcher seeks to examine the same single case at two or more different points in time or to capture trends over time. A multiple case study design is used when a researcher seeks to determine the prevalence or frequency of a particular phenomenon. This approach is useful when cases are used for purposes of a cross-case analysis in order to compare, contrast, and synthesize perspectives regarding the same issue. The focus is on the analysis of diverse cases to determine how these confirm the findings within or between cases, or call the findings into question.

Case study affords significant interaction with research participants, providing an in-depth picture of the phenomenon (Bloomberg & Volpe, 2019). Research is extensive, drawing on multiple methods of data collection, and involves multiple data sources. Triangulation is critical in attempting to obtain an in-depth understanding of the phenomenon under study and adds rigor, breadth, and depth to the study and provides corroborative evidence of the data obtained. Analysis of data can be holistic or embedded—that is, dealing with the whole or parts of the case (Yin, 2018). With multiple cases the typical analytic strategy is to provide detailed description of themes within each case (within-case analysis), followed by thematic analysis across cases (cross-case analysis), providing insights regarding how individual cases are comparable along important dimensions. Research culminates in the production of a detailed description of a setting and its participants, accompanied by an analysis of the data for themes or patterns (Stake, 1995, 2005; Yin, 2018). In addition to thick, rich description, the researcher’s interpretations, conclusions, and recommendations contribute to the reader’s overall understanding of the case study.

Analysis of findings should show that the researcher has attended to all the data, should address the most significant aspects of the case, and should demonstrate familiarity with the prevailing thinking and discourse about the topic. The goal of case study design (as with all qualitative designs) is not generalizability but rather transferability —that is, how (if at all) and in what ways understanding and knowledge can be applied in similar contexts and settings. The qualitative researcher attempts to address the issue of transferability by way of thick, rich description that will provide the basis for a case or cases to have relevance and potential application across a broader context.

Qualitative research methods ask the questions of "what" and "how" a phenomenon is understood in a real-life context (Bloomberg & Volpe, 2019). In the education field, qualitative research methods uncover educational experiences and practices because qualitative research allows the researcher to reveal new knowledge and understanding. Moreover, qualitative descriptive case studies describe, analyze and interpret events that explain the reasoning behind specific phenomena (Bloomberg, 2018). As such, case study design can be the foundation for a rigorous study within the Applied Doctoral Experience (ADE).

Case study design is an appropriate research design to consider when conceptualizing and conducting a dissertation research study that is based on an applied problem of practice with inherent real-life educational implications. Case study researchers study current, real-life cases that are in progress so that they can gather accurate information that is current. This fits well with the ADE program, as students are typically exploring a problem of practice. Because of the flexibility of the methods used, a descriptive design provides the researcher with the opportunity to choose data collection methods that are best suited to a practice-based research purpose, and can include individual interviews, focus groups, observation, surveys, and critical incident questionnaires. Methods are triangulated to contribute to the study’s trustworthiness. In selecting the set of data collection methods, it is important that the researcher carefully consider the alignment between research questions and the type of data that is needed to address these. Each data source is one piece of the “puzzle,” that contributes to the researcher’s holistic understanding of a phenomenon. The various strands of data are woven together holistically to promote a deeper understanding of the case and its application to an educationally-based problem of practice.

Research studies within the Applied Doctoral Experience (ADE) will be practical in nature and focus on problems and issues that inform educational practice.  Many of the types of studies that fall within the ADE framework are exploratory, and align with case study design. Case study design fits very well with applied problems related to educational practice, as the following set of examples illustrate:

Elementary Bilingual Education Teachers’ Self-Efficacy in Teaching English Language Learners: A Qualitative Case Study

The problem to be addressed in the proposed study is that some elementary bilingual education teachers’ beliefs about their lack of preparedness to teach the English language may negatively impact the language proficiency skills of Hispanic ELLs (Ernst-Slavit & Wenger, 2016; Fuchs et al., 2018; Hoque, 2016). The purpose of the proposed qualitative descriptive case study was to explore the perspectives and experiences of elementary bilingual education teachers regarding their perceived lack of preparedness to teach the English language and how this may impact the language proficiency of Hispanic ELLs.

Exploring Minority Teachers Experiences Pertaining to their Value in Education: A Single Case Study of Teachers in New York City

The problem is that minority K-12 teachers are underrepresented in the United States, with research indicating that school leaders and teachers in schools that are populated mainly by black students, staffed mostly by white teachers who may be unprepared to deal with biases and stereotypes that are ingrained in schools (Egalite, Kisida, & Winters, 2015; Milligan & Howley, 2015). The purpose of this qualitative exploratory single case study was to develop a clearer understanding of minority teachers’ experiences concerning the under-representation of minority K-12 teachers in urban school districts in the United States since there are so few of them.

Exploring the Impact of an Urban Teacher Residency Program on Teachers’ Cultural Intelligence: A Qualitative Case Study

The problem to be addressed by this case study is that teacher candidates often report being unprepared and ill-equipped to effectively educate culturally diverse students (Skepple, 2015; Beutel, 2018). The purpose of this study was to explore and gain an in-depth understanding of the perceived impact of an urban teacher residency program in urban Iowa on teachers’ cultural competence using the cultural intelligence (CQ) framework (Earley & Ang, 2003).

Qualitative Case Study that Explores Self-Efficacy and Mentorship on Women in Academic Administrative Leadership Roles

The problem was that female school-level administrators might be less likely to experience mentorship, thereby potentially decreasing their self-efficacy (Bing & Smith, 2019; Brown, 2020; Grant, 2021). The purpose of this case study was to determine to what extent female school-level administrators in the United States who had a mentor have a sense of self-efficacy and to examine the relationship between mentorship and self-efficacy.

Suburban Teacher and Administrator Perceptions of Culturally Responsive Teaching to Promote Connectedness in Students of Color: A Qualitative Case Study

The problem to be addressed in this study is the racial discrimination experienced by students of color in suburban schools and the resulting negative school experience (Jara & Bloomsbury, 2020; Jones, 2019; Kohli et al., 2017; Wandix-White, 2020). The purpose of this case study is to explore how culturally responsive practices can counteract systemic racism and discrimination in suburban schools thereby meeting the needs of students of color by creating positive learning experiences. 

As you can see, all of these studies were well suited to qualitative case study design. In each of these studies, the applied research problem and research purpose were clearly grounded in educational practice as well as directly aligned with qualitative case study methodology. In the Applied Doctoral Experience (ADE), you will be focused on addressing or resolving an educationally relevant research problem of practice. As such, your case study, with clear boundaries, will be one that centers on a real-life authentic problem in your field of practice that you believe is in need of resolution or improvement, and that the outcome thereof will be educationally valuable.

Bloomberg, L. D. (2018). Case study method. In B. B. Frey (Ed.), The SAGE Encyclopedia of educational research, measurement, and evaluation (pp. 237–239). SAGE. https://go.openathens.net/redirector/nu.edu?url=https%3A%2F%2Fmethods.sagepub.com%2FReference%2Fthe-sage-encyclopedia-of-educational-research-measurement-and-evaluation%2Fi4294.xml

Bloomberg, L. D. & Volpe, M. (2019). Completing your qualitative dissertation: A road map from beginning to end . (4th Ed.). SAGE.

Stake, R. E. (1995). The art of case study research. SAGE.

Stake, R. E. (2005). Qualitative case studies. In N. K. Denzin and Y. S. Lincoln (Eds.), The SAGE handbook of qualitative research (3rd ed., pp. 443–466). SAGE.

Yin, R. (2018). Case study research and applications: Designs and methods. SAGE.

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Home » Research Design – Types, Methods and Examples

Research Design – Types, Methods and Examples

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Research Design

Definition:

Research design refers to the overall strategy or plan for conducting a research study. It outlines the methods and procedures that will be used to collect and analyze data, as well as the goals and objectives of the study. Research design is important because it guides the entire research process and ensures that the study is conducted in a systematic and rigorous manner.

Types of Research Design

Types of Research Design are as follows:

Descriptive Research Design

This type of research design is used to describe a phenomenon or situation. It involves collecting data through surveys, questionnaires, interviews, and observations. The aim of descriptive research is to provide an accurate and detailed portrayal of a particular group, event, or situation. It can be useful in identifying patterns, trends, and relationships in the data.

Correlational Research Design

Correlational research design is used to determine if there is a relationship between two or more variables. This type of research design involves collecting data from participants and analyzing the relationship between the variables using statistical methods. The aim of correlational research is to identify the strength and direction of the relationship between the variables.

Experimental Research Design

Experimental research design is used to investigate cause-and-effect relationships between variables. This type of research design involves manipulating one variable and measuring the effect on another variable. It usually involves randomly assigning participants to groups and manipulating an independent variable to determine its effect on a dependent variable. The aim of experimental research is to establish causality.

Quasi-experimental Research Design

Quasi-experimental research design is similar to experimental research design, but it lacks one or more of the features of a true experiment. For example, there may not be random assignment to groups or a control group. This type of research design is used when it is not feasible or ethical to conduct a true experiment.

Case Study Research Design

Case study research design is used to investigate a single case or a small number of cases in depth. It involves collecting data through various methods, such as interviews, observations, and document analysis. The aim of case study research is to provide an in-depth understanding of a particular case or situation.

Longitudinal Research Design

Longitudinal research design is used to study changes in a particular phenomenon over time. It involves collecting data at multiple time points and analyzing the changes that occur. The aim of longitudinal research is to provide insights into the development, growth, or decline of a particular phenomenon over time.

Structure of Research Design

The format of a research design typically includes the following sections:

• Introduction : This section provides an overview of the research problem, the research questions, and the importance of the study. It also includes a brief literature review that summarizes previous research on the topic and identifies gaps in the existing knowledge.
• Research Questions or Hypotheses: This section identifies the specific research questions or hypotheses that the study will address. These questions should be clear, specific, and testable.
• Research Methods : This section describes the methods that will be used to collect and analyze data. It includes details about the study design, the sampling strategy, the data collection instruments, and the data analysis techniques.
• Data Collection: This section describes how the data will be collected, including the sample size, data collection procedures, and any ethical considerations.
• Data Analysis: This section describes how the data will be analyzed, including the statistical techniques that will be used to test the research questions or hypotheses.
• Results : This section presents the findings of the study, including descriptive statistics and statistical tests.
• Discussion and Conclusion : This section summarizes the key findings of the study, interprets the results, and discusses the implications of the findings. It also includes recommendations for future research.
• References : This section lists the sources cited in the research design.

Example of Research Design

An Example of Research Design could be:

Research question: Does the use of social media affect the academic performance of high school students?

Research design:

• Research approach : The research approach will be quantitative as it involves collecting numerical data to test the hypothesis.
• Research design : The research design will be a quasi-experimental design, with a pretest-posttest control group design.
• Sample : The sample will be 200 high school students from two schools, with 100 students in the experimental group and 100 students in the control group.
• Data collection : The data will be collected through surveys administered to the students at the beginning and end of the academic year. The surveys will include questions about their social media usage and academic performance.
• Data analysis : The data collected will be analyzed using statistical software. The mean scores of the experimental and control groups will be compared to determine whether there is a significant difference in academic performance between the two groups.
• Limitations : The limitations of the study will be acknowledged, including the fact that social media usage can vary greatly among individuals, and the study only focuses on two schools, which may not be representative of the entire population.
• Ethical considerations: Ethical considerations will be taken into account, such as obtaining informed consent from the participants and ensuring their anonymity and confidentiality.

How to Write Research Design

Writing a research design involves planning and outlining the methodology and approach that will be used to answer a research question or hypothesis. Here are some steps to help you write a research design:

• Define the research question or hypothesis : Before beginning your research design, you should clearly define your research question or hypothesis. This will guide your research design and help you select appropriate methods.
• Select a research design: There are many different research designs to choose from, including experimental, survey, case study, and qualitative designs. Choose a design that best fits your research question and objectives.
• Develop a sampling plan : If your research involves collecting data from a sample, you will need to develop a sampling plan. This should outline how you will select participants and how many participants you will include.
• Define variables: Clearly define the variables you will be measuring or manipulating in your study. This will help ensure that your results are meaningful and relevant to your research question.
• Choose data collection methods : Decide on the data collection methods you will use to gather information. This may include surveys, interviews, observations, experiments, or secondary data sources.
• Create a data analysis plan: Develop a plan for analyzing your data, including the statistical or qualitative techniques you will use.
• Consider ethical concerns : Finally, be sure to consider any ethical concerns related to your research, such as participant confidentiality or potential harm.

When to Write Research Design

Research design should be written before conducting any research study. It is an important planning phase that outlines the research methodology, data collection methods, and data analysis techniques that will be used to investigate a research question or problem. The research design helps to ensure that the research is conducted in a systematic and logical manner, and that the data collected is relevant and reliable.

Ideally, the research design should be developed as early as possible in the research process, before any data is collected. This allows the researcher to carefully consider the research question, identify the most appropriate research methodology, and plan the data collection and analysis procedures in advance. By doing so, the research can be conducted in a more efficient and effective manner, and the results are more likely to be valid and reliable.

Purpose of Research Design

The purpose of research design is to plan and structure a research study in a way that enables the researcher to achieve the desired research goals with accuracy, validity, and reliability. Research design is the blueprint or the framework for conducting a study that outlines the methods, procedures, techniques, and tools for data collection and analysis.

Some of the key purposes of research design include:

• Providing a clear and concise plan of action for the research study.
• Ensuring that the research is conducted ethically and with rigor.
• Maximizing the accuracy and reliability of the research findings.
• Minimizing the possibility of errors, biases, or confounding variables.
• Ensuring that the research is feasible, practical, and cost-effective.
• Determining the appropriate research methodology to answer the research question(s).
• Identifying the sample size, sampling method, and data collection techniques.
• Determining the data analysis method and statistical tests to be used.
• Facilitating the replication of the study by other researchers.
• Enhancing the validity and generalizability of the research findings.

Applications of Research Design

There are numerous applications of research design in various fields, some of which are:

• Social sciences: In fields such as psychology, sociology, and anthropology, research design is used to investigate human behavior and social phenomena. Researchers use various research designs, such as experimental, quasi-experimental, and correlational designs, to study different aspects of social behavior.
• Education : Research design is essential in the field of education to investigate the effectiveness of different teaching methods and learning strategies. Researchers use various designs such as experimental, quasi-experimental, and case study designs to understand how students learn and how to improve teaching practices.
• Health sciences : In the health sciences, research design is used to investigate the causes, prevention, and treatment of diseases. Researchers use various designs, such as randomized controlled trials, cohort studies, and case-control studies, to study different aspects of health and healthcare.
• Business : Research design is used in the field of business to investigate consumer behavior, marketing strategies, and the impact of different business practices. Researchers use various designs, such as survey research, experimental research, and case studies, to study different aspects of the business world.
• Engineering : In the field of engineering, research design is used to investigate the development and implementation of new technologies. Researchers use various designs, such as experimental research and case studies, to study the effectiveness of new technologies and to identify areas for improvement.

Advantages of Research Design

Here are some advantages of research design:

• Systematic and organized approach : A well-designed research plan ensures that the research is conducted in a systematic and organized manner, which makes it easier to manage and analyze the data.
• Clear objectives: The research design helps to clarify the objectives of the study, which makes it easier to identify the variables that need to be measured, and the methods that need to be used to collect and analyze data.
• Minimizes bias: A well-designed research plan minimizes the chances of bias, by ensuring that the data is collected and analyzed objectively, and that the results are not influenced by the researcher’s personal biases or preferences.
• Efficient use of resources: A well-designed research plan helps to ensure that the resources (time, money, and personnel) are used efficiently and effectively, by focusing on the most important variables and methods.
• Replicability: A well-designed research plan makes it easier for other researchers to replicate the study, which enhances the credibility and reliability of the findings.
• Validity: A well-designed research plan helps to ensure that the findings are valid, by ensuring that the methods used to collect and analyze data are appropriate for the research question.
• Generalizability : A well-designed research plan helps to ensure that the findings can be generalized to other populations, settings, or situations, which increases the external validity of the study.

Research Design Vs Research Methodology

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PhD Assistance

What are the steps involved to design phd research methods explain about two primary research method commonly used for the phd program.

• PhD Research Methodology Research Design helps in planning the research design and assist you in collecting and analyzing the needed information for your PhD research
• The main objective of Research Design Methodology is to formulate a research problem that requires precise investigation for developing a working thesis
• PhD Methodology Research Design Help follows a well-organized procedure utilized by scientist to drive your study and get a good outcome.

Introduction

The Research Design and Methodology is the integral part of the study that aims to explain how to drive the research and which data analysis method you will use to research. It is a framework that explains various other research theories, assumptions to give a working framework suitable for your study.

The research method includes information such as,

• A framework of research such as assumptions and theories
• Methods and techniques used to enhance the reliability and validity of the research work
• The theoretical orientation of the research
• Justification for choosing this method
• Consideration and limitation of selected research method

Designing your PhD research methods

Preparing a PhD design is the challenging task that involves various steps,

• Defining basis information Qualitative or quantitative

Experts for framing a PhD Research Design & Methodology is based on the data needed to interpret the result of the research. Qualitative data is descriptive and which can be observed not measured. Quantitative data is information about quantities.

• Determine the subject of the experiment

The approach of data collection varies based on different fields of the study and relies on the required information. So, determining the area of study is required to drive the research method. The objective of data collection is to ensure the information and reliable data for statistical analysis, so it is easy to make data-driven decisions for research.

• I dentify the approach of the research methodology

The two different approaches to follow in research method is a qualitative and quantitative approach. The research approach is a plan and procedure that consist of steps of broad assumptions to methods of data collection. Choosing the right data collection method is an important step that can change the fate of the research you carry out.

• Identify sample design

The sample design is a framework that serves as the basis for the selection of the survey sample and can change many other aspects of the survey. Identification of sample design is a more significant step that provides a basic plan and Methodology for selecting the sample.

• Data collection

It is the process of collecting, analyzing, measuring, accurate research using the standard validated technique. Framing PhD Research Methodology is the process of validating the information on target variables involves two Primary Dissertation Research Methods .

• Analysing and interpretation

It is the process of making sense to collect data using various techniques. Data collection is the systematic analysis of recording the information. Data interpretation involves explaining those patterns and trends.

Qualitative research method

Qualitative type of research method focuses on examining the area of study through external factors. This type of research has various ways to collect data from an individual. The primary dissertation research method used are interview, open-ended questions, focus group.  PhD Research Design Consulting Services helps in gaining insight into people’s thought and beliefs around certain behaviour and system.

The three primary dissertation research method used to collect the data are,

• Case study:

The case study is the only standard approach to study the working environment with the help of multiple sources of data. It provides a detailed study of a specific subject like the person, group, event, organization. These case study commonly use in education, clinical and business research. It is the research method that involved a detailed examination of a particular study.

• Observation:

The observation is a data collection method gathered knowledge of the research phenomenon by observing researched phenomenon—one of the simplest methods that do not require any technical knowledge to get results. Scientific controlled observation requires some technical skills to interpret the data. Observation is the main basis of formulating the hypothesis. The main advantage of this method is researchers do not depend on the information provided by the respondent.

Quantitative research methods

• Primary data collection:

It is the approach of data collected by the researcher. This approach allows the researchers to decide what exact variables operationalized in the study. PhD Research Design and Methodology analyze the data using a statistical technique to assess the natural relationship between the variables.

• Secondary data collection:

This approach differs and involves the statistical analysis of data collected by other researchers. It requires selection of publicly involved data sets for research. Secondary data analysis saves time for researchers to assess the information reliable. However, before start using these data’s researchers must build the research question based on the available data.

Data analysis is the process eventually helps to arrive conclusions by proving the hypothesis. Qualitative Research Methodology Editing Helps to frame the objectives that are supposed to measure, explore the relationships between multiple measures.

• Jonker, J., & Pennink, B. (2010). The essence of research methodology: Guide for master and PhD students in management science. Springer Science & Business Media.
• Steyaert, C. (1997). A qualitative methodology for process studies of entrepreneurship: Creating local knowledge through stories. International Studies of Management & Organization, 27(3), 13-33.
• Suri, H. (2011). Purposeful sampling in qualitative research synthesis. Qualitative research journal, 11(2), 63.
• Rutberg, S., & Bouikidis, C. D. (2018). Focusing on the fundamentals: A simplistic differentiation between qualitative and quantitative research. Nephrology Nursing Journal, 45(2), 209-213.
• Williams, C. (2007). Research methods. Journal of Business & Economics Research (JBER), 5(3).

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Know How to Structure Your PhD Thesis

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In your academic career, few projects are more important than your PhD thesis. Unfortunately, many university professors and advisors assume that their students know how to structure a PhD. Books have literally been written on the subject, but there’s no need to read a book in order to know about PhD thesis paper format and structure. With that said, however, it’s important to understand that your PhD thesis format requirement may not be the same as another student’s. The bottom line is that how to structure a PhD thesis often depends on your university and department guidelines.

But, let’s take a look at a general PhD thesis format. We’ll look at the main sections, and how to connect them to each other. We’ll also examine different hints and tips for each of the sections. As you read through this toolkit, compare it to published PhD theses in your area of study to see how a real-life example looks.

Main Sections of a PhD Thesis

In almost every PhD thesis or dissertation, there are standard sections. Of course, some of these may differ, depending on your university or department requirements, as well as your topic of study, but this will give you a good idea of the basic components of a PhD thesis format.

• Abstract : The abstract is a brief summary that quickly outlines your research, touches on each of the main sections of your thesis, and clearly outlines your contribution to the field by way of your PhD thesis. Even though the abstract is very short, similar to what you’ve seen in published research articles, its impact shouldn’t be underestimated. The abstract is there to answer the most important question to the reviewer. “Why is this important?”
• Introduction : In this section, you help the reviewer understand your entire dissertation, including what your paper is about, why it’s important to the field, a brief description of your methodology, and how your research and the thesis are laid out. Think of your introduction as an expansion of your abstract.
• Literature Review : Within the literature review, you are making a case for your new research by telling the story of the work that’s already been done. You’ll cover a bit about the history of the topic at hand, and how your study fits into the present and future.
• Theory Framework : Here, you explain assumptions related to your study. Here you’re explaining to the review what theoretical concepts you might have used in your research, how it relates to existing knowledge and ideas.
• Methods : This section of a PhD thesis is typically the most detailed and descriptive, depending of course on your research design. Here you’ll discuss the specific techniques you used to get the information you were looking for, in addition to how those methods are relevant and appropriate, as well as how you specifically used each method described.
• Results : Here you present your empirical findings. This section is sometimes also called the “empiracles” chapter. This section is usually pretty straightforward and technical, and full of details. Don’t shortcut this chapter.
• Discussion : This can be a tricky chapter, because it’s where you want to show the reviewer that you know what you’re talking about. You need to speak as a PhD versus a student. The discussion chapter is similar to the empirical/results chapter, but you’re building on those results to push the new information that you learned, prior to making your conclusion.
• Conclusion : Here, you take a step back and reflect on what your original goals and intentions for the research were. You’ll outline them in context of your new findings and expertise.

Tips for your PhD Thesis Format

As you put together your PhD thesis, it’s easy to get a little overwhelmed. Here are some tips that might keep you on track.

• Don’t try to write your PhD as a first-draft. Every great masterwork has typically been edited, and edited, and…edited.
• Work with your thesis supervisor to plan the structure and format of your PhD thesis. Be prepared to rewrite each section, as you work out rough drafts. Don’t get discouraged by this process. It’s typical.
• Make your writing interesting. Academic writing has a reputation of being very dry.
• You don’t have to necessarily work on the chapters and sections outlined above in chronological order. Work on each section as things come up, and while your work on that section is relevant to what you’re doing.
• Don’t rush things. Write a first draft, and leave it for a few days, so you can come back to it with a more critical take. Look at it objectively and carefully grammatical errors, clarity, logic and flow.
• Know what style your references need to be in, and utilize tools out there to organize them in the required format.
• It’s easier to accidentally plagiarize than you think. Make sure you’re referencing appropriately, and check your document for inadvertent plagiarism throughout your writing process.

PhD Thesis Editing Plus

Want some support during your PhD writing process? Our PhD Thesis Editing Plus service includes extensive and detailed editing of your thesis to improve the flow and quality of your writing. Unlimited editing support for guaranteed results. Learn more here , and get started today!

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Introducing Research Designs

• First Online: 10 November 2021

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• Michael Blankenagel 3  

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We define research design as a combination of decisions within a research process. These decisions enable us to make a specific type of argument by answering the research question. It is the implementation plan for the research study that allows reaching the desired (type of) conclusion. Different research designs make it possible to draw different conclusions. These conclusions produce various kinds of intellectual contributions. As all kinds of intellectual contributions are necessary to increase the body of knowledge, no research design is inherently better than another, only more appropriate to answer a specific question.

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Hunziker, S., Blankenagel, M. (2021). Introducing Research Designs. In: Research Design in Business and Management. Springer Gabler, Wiesbaden. https://doi.org/10.1007/978-3-658-34357-6_1

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 Ph.D. in Human Behavior and Design

The research tradition within the Human Behavior and Design major is based on the social sciences, in particular environmental psychology and human factors and ergonomics. The underlying premise is that systematic, empirical research based in the social sciences, when combined with an understanding of design processes, can contribute to the planning, design, and management of environments that enhance individual and organizational effectiveness.

Program Focus

The Ph.D. in Human Behavior and Design at Cornell University is a multidisciplinary program integrating the social sciences and design. Research focuses on environmental settings across a range of scales (from products to buildings to cities), that support safe, healthy and productive behaviors and foster sustainable design and lifestyles.

The program brings together faculty and students with expertise in the fields of interior, industrial and graphic design, architecture, art, design history, historic preservation, design with digital media, building technology, environmental psychology, human factors and ergonomics, economics, and facility planning and management to work on problems related to the interior environment.

The Ph.D. in Human Behavior and Design rests on the following basic premises:

• Development of the knowledge base guiding the planning, design, and management of physical settings requires systematic, empirical research.
• The physical environment affects the realization of human and organizational potential including health, safety, comfort, productivity and satisfaction.
• The users of environments are diverse and have different needs. Individual characteristics such as culture, gender, stage in the life course, family structure, role or task affect environmental needs.
• Organizational culture, goals, and structure help shape building design and use.
• The planning, design, and management of good environments require consideration of all users.
• Understanding organizational and human needs is no less critical than understanding financial, technological and aesthetic factors influencing the planning, design, and management of our physical surroundings.
• Multidimensional spatial experiences are heightened through an understanding of design elements, such as circulation, materials, lighting and acoustics.
• Theory provides a foundation that both informs and is informed by research and practice.

The program draws its strength from faculty knowledge and research in the following four areas:

• Environmental Psychology
• Facility Planning and Management
• Human Factors and Ergonomics

Ph.D. Requirements

Ph.D. in Human Behavior and Design curriculum requirements  and the graduate student handbook .

People who embrace thinking across disciplinary boundaries and who have a passion for teaching and scholarship are encouraged to apply. The strength of this unique new program is the integration of scientific and creative expertise within the same department. Applicants' prior disciplines might include (but are not limited to): social science, design, or engineering.

For more information, please contact the Graduate Field Assistant at [email protected] .

Applications are due November 1st . Applications are accepted for Fall Admission only.  

In addition to the online application via the Graduate School website , the following required documents must be submitted online:

• Academic Statement of Purpose (within 500 words)
• Personal Statement (limit 500 words)
• Three letters of recommendation
• Official transcripts
• Writing sample
• Curriculum vitae
• GRE general test (The desired combined score should be greater than or equal to 310—for the new scoring system effective November 2011—or, a combined score of 1200 for the old scoring system.)
• TOEFL - test for International students (DEA overall minimum: 105, plus Graduate School minimums must be met for each section: writing: 20; listening: 15; reading: 20; speaking: 22)
• OR IELTS - The Graduate School requires an overall band score of a 7.0 or higher on the IELTS

For additional information on how to apply, please visit Graduate School Admissions.

The intent of the Ph.D. in Human Behavior and Design program is that all admitted students will be fully funded with tuition, fees, and a stipend for a period of four academic (9 months) years contingent upon satisfactory progress toward the degree.

Prospective Ph.D. Student Application Requirement FAQ

Contact the Director of Graduate Studies (DGS) at  [email protected] .

First, you should read papers written by faculty with whom you might like to work to see if your interests align. Carefully review the websites and online materials provided by the program. In your application, describe your experience related to research, statistics, design, etc. Demonstrate your research experience. Describe you interests – possible dissertation research directions. Indicate your goals following the PhD. Request letters of recommendation from people who can speak to your research aptitude, commitment, preparedness, work ethic.

Yes, the Graduate School can help with this, but you must still adhere to our requirements and deadlines. 

No, we only have one admission cycle, applications are due in November for PhD; students start in the Fall semester of the following year.

All application materials are submitted online via the Graduate School’s application system (available on the web at: http://www.gradschool.cornell.edu/admissions/applying/apply-now ). 

No, a portfolio is not required for the Ph.D. degree.

No, but scholarly writing sample submissions are preferred (ex: Master’s Thesis; Peer Review Journal Article; Senior Honors Project).

One writing sample is sufficient.

HCD provides four years of funding to Ph.D. students in HBD, as long as students’ progress and performance is satisfactory. This funding could take the form of teaching assistantships, research assistantships, fellowships, or some combination and is typically for the nine-month academic year.

No, it is not necessary to have an MS or MA before beginning the PhD.  The strongest applicants are those who have a foundation in research (e.g., have completed a research thesis (undergrad or graduate), have participated in a lab as a research assistant, have perhaps taken a social science research methods class).

For the PhD in Human Behavior and Design, a background in both design and research is preferred, but students may come from a variety of disciplines.

Yes, HOWEVER, if substantial progress has not been made on their Master’s, then it’s a long shot. Applicants should be told the following two things: 1. Their Ph.D. work will take 4 years to complete, and 2. Lack of substantial progress on their Master’s Thesis will be viewed as a liability.

Yes. Note that GRE scores must be less than five years old. See the language proficiency requirement here . 

No. Academic letters of recommendation are valuable and somewhat preferable; however recommendations should be from people who can best assess the qualities, characteristics, and capabilities of the applicant. 

Cornell’s institutional test code for ETS is 2098. DEA’s department code is 4499.

D+EA recommends a combined verbal/quantitative GRE score of 310 (new scoring system effective November 2011) or a combined score of 1200 (old scoring) but this is not an absolute cutoff. Candidates with strong applications, but scores below this level, may be considered. You may submit scores to D+EA more than once if you re-take the test. Your scores may not be older than 5 years. Please plan to take the GRE in time to submit your scores by the application due date. 

No, the GR’s can't be waived.

Yes, GREs can be retaken, but scores must be submitted by the application deadline. 

We strongly encourage you to take the GRE and TOEFL/IELTS tests early enough in advance that your scores will be received by our application due date. We may allow some latitude, however. If your official scores have not arrived by the due date, but your unofficial scores have, we may hold your application if approved by the DGS. Your scores are automatically reported to Cornell by the testing service (ETS) as soon as they are ready, and the Graduate Field Assistant will automatically add them to your packet.

Please see the graduate school's website .

D+EA recommends a GPA of 3.0 (minimum), but this is not an absolute cutoff.

The online application requires you to upload an unofficial copy of each official transcript from each college or university previously attended. To prepare your transcripts, follow the steps below:

Admitted students who accept the admission offer are required to submit an official  transcript prior to matriculation.  For more information visit:  https://gradschool.cornell.edu/admissions/prepare/transcripts/

It is advised that you periodically check your application on line to see if your application is complete, especially if you are waiting for letters of recommendation to be uploaded. D+EA’s Graduate Field Assistant may, as a courtesy, send you a reminder if you have missing information when the committee begins to review applications. If you have questions, please contact D+EA’s Graduate Field Assistant at [email protected] .

Yes, we allow deferments up to one year, but this must be decided when responding to the department’s offer.  To request a deferral, by the "reply by" date (typically April 15) an applicant must first accept the offer of admission and then request (and provide a reason for) the deferral.  Applicants cannot defer admission after declining our offer; instead the applicant must re-apply.

Yes, but this is on a case-by-case basis, and the D+EA Graduate Faculty will make decisions as to what is allowed or not allowed. Typically, you will need to provide a syllabus for your prior course(s).

 If you would like to schedule a visit, you should first make an appointment with D+EA’s DGS. If you would like to meet with other D+EA Faculty, you could also schedule meetings with them while you are on campus. Many students also enjoy taking a walking tour of campus while they are here: http://www.cornell.edu/visiting/ithaca/walking_tours.cfm .    Other useful links include the campus map  and the Visit Ithaca web site: http://www.visitithaca.com/

Ph.D. Program FAQ

Our Ph.D. students often find jobs in academia but some choose to pursue jobs in industry (e.g. Apple, Google) or as design researchers/environmental psychologists within large architecture firms.

Yes, The Graduate School regularly collects and shares information on graduate student experiences and outcomes to support prospective applicants in their decision-making process. For more information please see their metrics and outcomes data .

No, D+EA does not offer online classes for the Ph.D. program.

Yes, the Ph.D. program is STEM certified.

The first two years are dedicated primarily to course work (in your major field and two minor fields).  At the end of year 2, PhD students complete qualifying exams (“A Exam”).  Arrangements for you’re A-Exam are made with your dissertation committee. A dissertation is required.  Years 3 and 4 focus primarily on research and the completion of the dissertation.  The “B Exam” is the dissertation defense. 

Four years.

Yes, PhD students are expected to be on campus for the 4-year PhD degree. For more information please see: https://living.cornell.edu/live/wheretolive/housingoptions/index.cfm  

This depends on what sort of funding is awarded to the doctoral student. In most cases, Ph.D. students will be asked to function as a teaching assistant for at least part of their time in D+EA.

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• CAREER COLUMN
• 31 January 2020

Design your own doctoral project

• Jesko Becker 0

Jesko Becker is a doctoral candidate at the University of Freiburg in Germany.

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Browsing for funded PhD positions on the Internet and beyond can be time-consuming and exhausting; the constellation of topic, supervisors and location must fit together to suit the individual candidate. Creating my own project from scratch allowed me to choose a topic, supervisor and location separately. But it is certainly not a path for everyone: self-doubt, setbacks and the risk of not getting enough support for your plans are inevitable. This undertaking also requires strong autonomy, determination and perseverance to overcome the initial obstacles alone.

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doi: https://doi.org/10.1038/d41586-020-00268-1

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PhD in Transition Design

Fundamental change at every level of society is needed to address the issues confronting us in the 21st century. From climate change, loss of biodiversity, and depletion of natural resources, to systems of oppression, inequality, and inequity, Transition Design tackles these kinds of complex, wicked problems.

About our PhD Program

The PhD in Transition Design is for people committed to making a positive change in the world. Our unique program develops future design leaders with the capacity to envision and realize purposeful change across a range of complex systems—from food, water, materials and products, to policy, culture, economy, cities, and social movements. Transition Design acknowledges that we are living in transitional times, takes as its central premise the need for societal transition (systems-level change) to more just, equitable, and sustainable futures, and argues that design and designers have a key role to play in these transitions. This kind of design is connected to long horizons of time, pluriversal perspectives, compelling visions of desired futures, and must be based upon new knowledge and skill sets. Research in Transition Design, while grounded in systems thinking, can also be undertaken from the perspective of many areas of interest—circular economies, commoning, decoloniality, sociotechnical transitions, public policy, stakeholder participation, and futuring, to name a few.

Complex challenges must be addressed through ecologies of interventions that draw on multiple design specialisms, alongside expertise from other disciplines. In this way, Transition Design is a transdisciplinary field that unites researchers from within and beyond Design. This involves service designers, social designers, communication designers, product designers, environments designers, and design historians, working alongside ecologists, anthropologists, philosophers, economists, and political scientists.

Our PhD researchers develop their own research interests within the broad framework of Transition Design. We practice a collective, rather than competitive approach to creating a strong cohort. Program faculty and researchers alike operate as one supportive community with the shared goal of producing transformational work that matters. Throughout the program, you will maintain fluid interactions between theory and practice, through critical engagements with texts, images, media, objects, and experiences. The program is designed to encourage a supportive, critical research culture in which students, their peers, and advisory committees work closely together to shape new knowledge. As a PhD Researcher at CMU, your research will directly shape the development of this dynamic and emerging field.

The School of Design at Carnegie Mellon is a top-ranked Design School, situated at the heart of a world-leading research university, with a thriving undergraduate, graduate and doctoral student community. Upon completing the PhD, graduates are equipped to drive design-led systems-change through academic posts in leading universities and take on influential roles in nonprofit organizations, business, and government. Recent graduate destinations have included the University of Technology Sydney, New York University, Microsoft, University of Michigan, and Northeastern University.

Read more about Transition Design .

Program Structure

The program has two key stages: the first is taught (year 1); the second comprises a self-defined project developed in consultation with an advisory committee (years 2–4). Where schedules permit, our students can take electives from across Carnegie Mellon's rich and diverse curricular offering.

The core curriculum is as follows:

Advancing your understanding of how research from diverse disciplinary domains can inform new kinds of research and practice. Through this 15-week course, you will explore the intersections of theory, practice and praxis, to develop a holistic understanding of research as a reflexive theoretical and practical process. Coursework includes the design of praxis methods to shape your own research. Topics include: research of design, research for design, research by design, and design praxis.

"Teaching Design" focuses on planning, conducting, reviewing, and revising learning experiences in academic and professional contexts. Students will study learning theories and instructional design approaches, probing their value to design education. Students will investigate traditional and emergent approaches to instruction through readings and discussions situated in the realm of cognitive studies, neuroscience, learning science, instructional design, and educational pedagogy. Students will discuss challenges that are common to design, which they will use to brainstorm ways of effectively addressing obstacles that they are likely to encounter when teaching. Students will apply their discoveries to the design of learning objectives, outcomes, instructional activities, performance measures, formative assessments, and summative evaluations, to create innovative and effective teaching and learning experiences based on a context they define. The course will culminate in the design of concrete teaching plans that may take the form of syllabi, project briefs, class exercises, assessment tools, and evaluation metrics.

An “ecoliterate” mindset is the starting point for Transition Design. Indeed, to be ecoliterate is to understand the principles through which natural systems flourish and to apply these principles to society, so that we too may flourish without compromising or destroying the natural systems on which we depend. Spanning 7-weeks, this seminar class focuses on key themes of ecoliteracy to help us navigate our social, ecological, and existential crises. Topics include: place and bioregions, Goethean science, living systems and Gaia, relationality and context, radical holism, and everyday life and infrastructure

This seminar exposes students to the emergent issues in the research and practice of Design through weekly discussions with individual faculty members. Faculty primarily resident to the School of Design present their research and interests to students in 50 minute sessions; two faculty presenting one day each week. The course aims to provide masters students (and some PhD students) first-hand exposure to faculty, their research, and interests. It's also a nice way for faculty to begin meeting grad students.

Driving design-led, systems-level change towards socially and ecologically sustainable, convivial and equitable place-based lifestyles. Through this 15-week course, you will explore multilevel problems to establish mutually beneficial relationships between people, the natural environment and the designed world; repositioning designers as agents of sustainable change. Topics include: living systems & complex problems, mindsets & postures, theories of change, visions, and transition designing.

Introducing future-focused design practices with practical training in futuring and foresight methods. Through this 15-week course, you will be introduced to a broad array of future-focused design practices, coupled with practical training in futuring and foresight techniques and methods. Coursework includes the development of a "Time Machine"—an immersive, future-focussed scenario for storytelling and research activation. Topics include: world modeling, futuring & foresight, emerging design practices, criticality & speculation, design pedagogy, and sustainable futures.

Defining a 3-year research project with your advisory committee, geared toward activating sustainable change. Through this 7-week course, you will frame new research contexts, define questions, plan methodological approaches, design open research structures that adapt and change, and speculate upon research outcomes and their impacts. Coursework includes writing a PhD proposal. Topics include: framing research problems, building an argument, planning your project, keeping research open, and writing a research proposal.

Developing a 2-year period of deep, reflective and self-directed research. Across this sequence of courses—spanning 4 semesters—you work closely with your advisory committee to build upon your research proposal and literature review. During this phase, you will deepen your literature review, undertake field research, develop your practice and begin pulling together your research into a coherent body of work.

Deepening your connection with the craft of writing via a cross-section of academic, journalistic and creative styles. Through this 15-week course this practical hands-on course helps you develop your style, structure and confidence in design writing. Writing is framed as a creative process where ideas are explored, discovered and expressed. Coursework includes planning a literature review. Topics include: conference papers & journal articles, design criticism, podcasts & digital publishing, and transformational design curricula.

Creating the critical space for divergent research themes to coalesce into a clear and conclusive body of research. You will assemble your dissertation in advance of the defense in May of the final semester. Dissertations can be entirely written (60–80K words), or a body of written and practical work (40–60K words, by negotiation). Your final body of work must demonstrate an original contribution to knowledge which expands understanding of transition design.

In addition to the above courses, students and faculty meet every few weeks for Critical Readings in Transition Design—a forum for in-depth discussion and critique of key texts, concepts and tools relating to transition design, and design-led systems-change more broadly.

Click here to view our PhD in Transition Design Planner, illustrating how these courses map across the 4 years of the program.

Current Researchers & Faculty

Phd researchers.

Adam Cowart

Tricia Douglas

Kyla Fullenwider

Luis Garcia

Esther Kang

William Martin

Saurin Nanavanti

Alexander Polzin

Madeline Sides

Russell Singer

Margaret M Urban

Matthew Wizinsky

Faculty advisors.

Toward the end of the first year, you are supported in assembling a 2-4 member advisory committee. This mentoring group comprises diverse expertise from faculty from the School of Design , from other schools across CMU, and advisors external to CMU where appropriate.

Requirements & Costs

Entry requirements.

Qualifications Applicants should meet the following requirements:

• A Bachelor's degree from an accredited institution with a strong record of academic achievement.
• A Master's degree from an accredited institution with a strong record of academic achievement. In some circumstances, we will consider applicants without a Master's degree, where there is evidence of equivalent community-engagement, leadership, research, writing, or other related experience.
• Candidates for the PhD teaching fellowship will ordinarily have a Master's degree in Design, and at least two years of professional and/or teaching experience. In select cases, 5+ years of professional design experience, demonstrated by portfolio, may be considered if the applicant's Master's degree is in a related or complementary field.

Language Requirements All applicants whose native language is not English are required to submit a TOEFL (Test of English as a Foreign Language), the IELTS (International English Language Testing System), or the online Duolingo English Test score. All applicants must submit their highest test score by the application deadline.

• Our minimum TOEFL total score is 102, with minimum subscores of 25. In addition to single test date TOEFL iBT scores, the School of Design also accepts MyBest scores for TOEFL iBT.
• Our minimum IELTS score is 7.5
• Our minimum Duolingo score is 128 total. Subscore minimums: Literacy: 125, Conversation: 120, Comprehension: 135, Production: 105

Scores below these minimums will not be considered for admission. Note : There are additional requirements for teaching fellowship candidates, in regards to written and verbal English language capacities by Pennsylvania State Legislation. All non-native English speakers are required to pass an International Teaching Assistant Test administered by CMU.

There are two funding routes through the program: professional track and teaching fellowships.

Professional track candidates find their own sources of funding. This route is for people who wish to continue their employment whilst also undertaking PhD research, and keep the flexibility to study in a low-residency mode once the first year of coursework is complete.

Teaching fellowships cover tuition, individual health insurance, and provide an annual stipend of $22,500 ($11,250 per semester). Teaching fellows co-teach one course per semester, from semesters 2–7. All teaching fellows must be in residence at CMU for the duration of the program.

Applicants who are accepted into the program, but do not receive an offer of a teaching fellowship, are required to pay the following fees, totalling approximately $69,975 over 4-years:

• Year 1: $45,700 (2024-2025)
• Year 2: $6,490 (2025-2026)
• Year 3: $6,625 (2026-2027)
• Year 4: $6,760 (2027-2028)

University fees (annual estimate)

• Activity Fee: $238
• Transportation Fee: $256
• Technology Fee: $460

Note : Professional track candidates are responsible for their own individual health insurance at approximately $3,000 per year.

Application

Information on how to apply and what you'll need to include with your application can be found HERE .

Further Information

Please feel free to email us with any questions. You can also check out our FAQs page . As this is a relatively new program, insufficient data exists to provide helpful transparency statistics. This will be shared as it becomes available.

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Entrance Year Sep 2024

Programme Code 73601

Within The Hong Kong Polytechnic University, the School of Design offers positions for applicants who wish to obtain doctoral degrees in design. Operating within a leading design school in Asia, the PhD programme aims to advance knowledge by producing high-quality research. Situated in Hong Kong, the School brings together Asian and Western knowledge to inform scholarly, technical and critical enquiry. As a centre for both design research and design education, the School of Design welcomes diverse approaches within each of these themes, with various methodologies, practices and theoretical positions, through hypothetico-deductive, interpretive, constructive and artistic research. The PhD programme draws together global scholars to generate, exchange and discuss knowledge and ideas on contemporary questions within the pursuit of advanced academic work.

2. Research Themes

Research at the School of Design is grounded in an understanding of design as a social activity that: [a] involves collaboration and sharing among diverse people, [b] is embedded in societies and cultures, [c] gives expression to ideals and values of society, [d] critically explores and interrogates issues in society and [d] goes beyond the design professions.

Moreover, the School research has gravitated towards exploring these social dimensions of design within three distinct realms:

a) Social Design (設計社會學):

collaborative design with communities to improve their lives through participatory, theoretical and critical approaches

b) Design Economy (設計經濟學):

collaborative design that enhances the role of design in innovation and value creation in the private sector

c) Design Making (設計製造學):

user-centred design investigations with communities and practices of making, such as the “maker movement,” with technological, organizational as well as sociological facets.

This work happens in the School’s research centres and  research labs :

Each theme is based on the established experience and expertise of the School of Design and its researchers. Each embraces an essential facet of relevant contemporary design research approach.

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Media arts and sciences PhD redesigns community through research in human-computer Interaction

Photo courtesy of Alejandra Rodriguez Vega

Editor’s note:  This story is part of a series of profiles of  notable spring 2024 graduates .

Alejandra Rodriguez Vega, who is receiving her PhD from the media arts and sciences program in the School of Arts, Media and Engineering, focuses on designing with communities based on collaborative design approaches and user-centered design.

Rodriguez Vega has contributed valuable research to the local arts and academic communities during her graduate (MS and PhD) studies. Projects like “The Dream Collective” utilize crowdsourcing as a way to collect data about the experience of the modern classroom and how it can be re-designed to enhance the learning experience. She has also worked with Citizen Science to help design Pollinator Gardens for the local Mirabella at ASU community.  

Rodriguez Vega credits Associate Professor Stacey K.,  in the School of Arts, Media and Engineering, and her as a source of inspiration for introducing her to the research area of human- computer interaction early in her graduate studies. Having the opportunity to help work behind the scenes for the 2019 Tangible Embedded and Embodied Interaction conference that took place at ASU’s Tempe campus inclined her to further pursue graduate studies with a PhD in media arts and sciences.

“I wanted to be a part of this and continue collaborating with these brilliant minds who are not only very technically gifted but also incredibly creative,” she said.

While Rodriguez Vega attributes acceptance into the PhD program to hard work and luck, her dedication to contributing her valuable perspective to the research fields stood out to faculty.

During her studies in the MS media arts and sciences program, she collaborated with the SANDS (Social and Digital Systems Group) research lab. This led to her finishing her MS with a publication that was published at the 2019  Designing Interactive Systems conference. This experience prepared her for the world of dissertation and defense that is typical within the realms of PhD studies.

“The paper focused on a workshop that we did with the community scientists, revolving around interaction with drones,” Rodriguez Vega said. “That was really the starting point of doing hands-on research, seeing the publication process, as well as presenting my research to my fellow peers, faculty and researchers from all over the world. And I was lucky enough that I had that experience during my first summer of my masters, so preparing to go into my PhD, I had a pretty good idea of at least how the first few years were going to be.”

Rodriguez Vega entered graduate studies with a background in communication and interest in the interactions that take place between humans and computer systems. She was able to explore these interactions in various ways, from co-developing an online creativity tool, “The Dream Collective,” and creating a friendly user interface, to holding in-person workshops with participants where users’ needs and aspirations for future technologies were brought to life through low-fidelity prototypes. 

“I specifically decided to focus on what is called ‘collaborative design.’ This is an area of research that talks with all stakeholders and gives them the opportunity to iterate on any part of the design process and voice their concerns, desires and likes or dislikes,” she said. “The focus is really trying to understand user needs and expectations of designs and then working with engineers, designers and researchers to see how these changes can be brought to life. My research specifically focuses on integrating speculative methodologies into collaborative design so that participants are not limited by technological knowledge or feasibility when ideating and voicing their concerns, as well as, through online collaborative ideation tools, being able to collaborate with stakeholders at a larger scale.”

Most recently, Rodriguez Vega has worked on a project focused on collaborative design with the Center for the Future , an ASU-Starbucks partnership. 

Rodriguez Vega has received multiple scholarships and awards through her studies, such as the Graduate Completion Fellowship (2023–24), Graduate College Travel Award (2022), Creative Constellation Grant (2021), University Graduate Fellowship (2020), Outstanding Graduating Student (2019) and Katherine K. Herberger Scholarship (2018).

Question: What’s something you learned while at ASU — in the classroom or otherwise — that surprised you or changed your perspective?

Answer: My original background was in the humanities, so I was really scared of all these coding classes and thought they were going to be math heavy. I quickly learned otherwise, and I especially thank the faculty at AME, as they help you understand the logic behind coding and how it can be applied to art and creative outlets. I don’t think that that was something that I have ever encountered before or even thought possible, so that was very interesting to learn and tackle.

Q: Why did you choose ASU?

A: It was actually the weather. I don’t think a lot of people would say that, but I do like the heat for one thing. On a more serious note, the biggest thing was I didn’t find any other universities or programs that had a similar program like media arts and sciences — where it’s not completely engineering and it’s not completely art — it’s a mixture of both as well as design. This was extremely attractive to me, because I don’t have a background in engineering and didn't have the pressure of going into it thinking ‘Oh no, I need to know how to code!’ This really helped me get in the door having a bit of an understanding in engineering, design and art. Now, with my experience through research, I can communicate with engineers and programmers along with designers to produce meaningful and user-friendly interactions.

Q: Which professor taught you the most important lesson while at ASU?

A: My PhD chair, Stacey K. Her extensive background in human computer interaction has been extremely eye-opening. It has also made me realize my passion so that was extremely helpful while doing my PhD. She has taught me to be a better writer and a better researcher and how to approach people, handle workshops, and how to analyze data. She has been essential throughout my PhD journey.

I also have to mention Professor Kimberlee Swisher, I was her teacher’s assistant for quite a bit and although I never took a class with her since she teaches undergrad, she really inspired me to be a better educator and mentor and understand how to relate to people better when tackling problems. Really, all the faculty and staff within AME deserve recognition as they are great in helping you find a solution. If you have a crazy idea or a random question, even if it’s really out there, they’ll ask for more details and help find a solution. This would not have been doable without such a supportive department.

Q: What’s the best piece of advice you’d give to those still in school?

A: My best advice would be to ask a lot of questions. A lot of times you hear faculty say go to office hours or if you have any questions, come up and ask me, I’ll be here and not a lot of people take that opportunity. What I’ve learned is that the amount of knowledge that everyone has is beyond what you expect and if you really want to make the most out of your time here, whether it’s undergraduate or graduate studies,  start a conversation with faculty and staff, because they really do want to help you. Not only can this help you make connections, but it also helps you figure out what you want to do for a career.

Q: What was your favorite spot on campus, whether for studying, meeting friends or just thinking about life? 

A: It was probably the graduate student lounge in Matthews Center (on the Tempe campus). I was able to meet my fellow grad students, and just being able to talk with them and hang out really helped with making friends but also understanding their approach to their own research and writing. I think one of the things that really separates graduate studies from undergraduate studies is that everyone is doing their own research, writing their own papers, so this can become lonely sometimes. Having the Matthews Center created a space where I could talk with other students and understand the struggles they're going through and how they tackled challenging times.

Q: What are your plans after graduation?

A: I am hoping to go into user experience research in industry. User experience research allows us to collaborate, ideate and design alongside stakeholders such as users, designers, engineers and programmers to see what works, what doesn’t work, and what can be improved in a current technology, service or experience and even speculate on the future. 

Q: If someone gave you $40 million to solve one problem on our planet, what would you tackle?

A: I don’t think $40 million would be enough to tackle a specific problem on our planet. However, I do think a way to start tackling a lot of problems would be by educating people, so one of the things I think we could heavily invest in would be in education. I think now more than ever, teachers and middle school teachers lack funding and support. This money could be used to give teachers and students a better starting point to further educate them and have them be aware of problems and ways to solve the problems. Not just getting information out about things like global warming but actually giving them the time and resources to solve the problems through collaborative work. Education can be a great starting point or a foundation to actually solve problems.

More Sun Devil community

Media arts and sciences grad: ‘I am capable of doing what I previously thought was unthinkable’

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Voices Blog

Sciences, Mathematics and Biotechnology

Steeped in Clinical Trial Design Know-How

Certificate graduate vivian dao-tong parlays skills to advance into clinical trial manager role.

For Vivian Dao-Tong, the importance of clinical research and its positive effects on health are personal.

One of her family members participated in a clinical trial for diabetes research and Vivian was taken aback at how much care and attention they received from the trial staff during each monthly visit. “The research team was very knowledgeable and resourceful. They spent a lot of time explaining to us what diabetes was and how to modify lifestyle habits to help improve quality of life,” Vivian explains.

“When the clinical trial was over and the drug went to market, it was neat to see how my family member’s participation in the clinical trial played a huge role in helping other patients have access to a new therapy to help manage their diabetes.”

This experience stuck with her. It’s what led her to earn a B.S. in biological sciences (with a minor in psychology) from Sacramento State and then to continue her education in the field with an M.S. in pharmaceutical sciences from Touro University.

In the field, Vivian has held clinical research coordinator and clinical research associate roles at various biotech companies in the Bay Area. It was during these experiences when Vivian realized that in order to succeed and help others improve their quality of life, she would need the technical know-how to effectively oversee a clinical trial from start to finish.

“The Bay Area is home to a lot of biotech companies and unfortunately not all companies will teach their employees on how to lead and manage a clinical trial,” Vivian explains.

“It was important for me to find a program that would prepare me to be knowledgeable in FDA and ICH Good Clinical Practices regulations and understand best practices on how to start, maintain and close out a clinical trial.”

So Vivian turned to some coworkers for advice, many of whom had excelled in their careers after completing our Certificate Program in Clinical Research Conduct and Management . With those recommendations in mind, Vivian knew that our certificate would be the perfect path toward career success .

“I was also drawn to UC Berkeley Extension’s reputation of upholding rigorous academic standards that would prepare me for my career in clinical trials.”

In August 2019, Vivian took her first step in investing in her future: Enrolling in the Introduction to Clinical Research: Clinical Trial Phases and Design course .

It was important for me to find a program that would prepare me to be knowledgeable in FDA and ICH Good Clinical Practices regulations and understand best practices on how to start, maintain and close out a clinical trial. I was also drawn to UC Berkeley Extension’s reputation of upholding rigorous academic standards that would prepare me for my career in clinical trials.

You took all of the classes online. Tell me about your experience going through the certificate.

I really enjoyed meeting other students and instructors virtually . The teachers really cared for their students and shared their industry experiences with us.

Assignments were applicable to day-to-day operations in the field. I remember we had an assignment where we had to write out what to prepare prior to conducting a monitoring visit .

I really enjoyed the flexibility of taking online classes because I was also working full time as a clinical trials specialist at Exelixis .

The curriculum was very logical. The first course was very high-level and challenging, but as I navigated through the program, it started to get easier. I enjoyed learning about the different life cycles of a clinical trial—such as startup, maintenance , close-out , post-market—different phases of a clinical trial and inspection readiness.

I really enjoyed the flexibility of taking online classes because I was also working full time as a clinical trials specialist at Exelixis.

Since completing the certificate, you’ve moved up from a clinical trials specialist to a clinical trials manager.

Yes, I am working at Alector , a biotechnology company in South San Francisco that focuses on neurodegenerative and immuno-neurology therapies.

Some of my day-to-day responsibilities include:

Ensuring sponsor oversight by managing contract research organizations (CROs) and study vendors

Overseeing regional site management activities

Performing data listing reconciliations and protocol-deviation reviews.

Managing CTA and budget negotiations

Leading study document reviews with cross-functional team members

Overseeing Trial Master File (TMF) as part of inspection readiness

Identifying risks and performing mitigation

Working on clinical-development operations, process, initiatives and improvement

That’s quite a lot of responsibilities! Are you incorporating lessons learned from the certificate to your work?

Absolutely! There was one company that I worked for that was a pre-IPO biotech company. At the time, the company wanted to start a clinical trial but did not know how or what guidelines to follow. I was able to explain what processes must be in place before starting a clinical trial —such as site feasibility, site qualification, site selection, et cetera—and worked very closely with the project manager to set realistic timelines.

This program provided me with a lot of knowledge and gave me the tools to be resourceful so that I can help lead my team to manage a clinical trial successfully.

What does earning this certificate mean to you personally and professionally?

With the constant changes in the world, there are so many new and undiscovered illnesses out there. Being able to research these emerging illnesses and investing the time, effort and money to run these clinical trials is very rewarding. Not everyone can say that they can put a drug out on the market , and for me it is an ultimate career goal to be a part of a team that is able to do this.

What advice would you give to a student who is starting the certificate?

Stay organized and stay disciplined ! Don't be afraid to ask questions if you do not understand the material at first.

Stay up to date with courses and trends in Clinical Research Conduct and Management

Deepen your skills, clinical research conduct and management, related posts.

Sticking to Her Roots

Making a Difference in the Lab

February 20 Online Event: Careers in Biotech

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• MyU : For Students, Faculty, and Staff

Professor Mona Minkara

Professor Mona Minkara Department of Bioengineering Northeastern University Abstract

Building the COMBINE Lab: Breaking Barriers as a Blind Chemist

In this talk, Mona Minkara, an assistant professor of Bioengineering at Northeastern University, shares the story behind building the Minkara Computational Modeling for BioInterface Engineering (COMBINE) Laboratory. As a blind chemist, Mona faced challenges and overcame internalized ableism to see her blindness as an asset in the lab’s work. She emphasizes the importance of combining diverse perspectives in science to solve new problems and advocates for disability inclusion in STEM. Her story challenges us to reflect on our biases and recognize the importance of creating inclusive spaces and striving for equitable opportunities for all. 

Throughout her academic journey, Mona navigated the complexities of securing the necessary accommodations for her education and selecting a graduate school that offered the support she needed. Her mentors played a significant role in helping her overcome internalized ableism and see her blindness as an unseen advantage. This perspective has been a driving force in her work. Mona’s story asks us to reflect on how we can work together to break down barriers, and acknowledges there are still barriers to break – we still need to make the results of scientific research and its literature accessible to all people.

Mona Minkara

Dr. Minkara’s research uses a variety of methods from computational chemistry that she has employed throughout her academic career. While pursuing her BA in Chemistry at Wellesley College, Dr. Minkara worked with Dr. Mala Radhankrishnan, where she used computational methods to explore the binding of drugs to HIV-1 Reverse Transcriptase. After completing her BA in 2009, Dr. Minkara spent a year conducting research at Wellesley under a Howard Hughes Medical Institute Research Grant. In 2010, she began her graduate studies at the University of Florida supported by a National Science Foundation Graduate Research Fellowship. Under her co- advisors, Dr. Kenneth M. Merz Jr. and Dr. Erik Deumens, she focused on using molecular dynamics simulations to design a new inhibitor for Helicobacter pylori urease, an enzyme that helps bacteria survive in the stomach, and in 2015, she received her PhD in Chemistry. She then joined Dr. J. Ilja Siepmann’s lab as a post-doc at the University of Minnesota Twin Cities Chemical Theory Center. In this role, Dr. Minkara used Monte Carlo simulations to explore the interfacial properties of surfactants, the surface tension of water, and the miscibility gap of supercritical fluids.

Hosted by Professor Alexander Umanzor

331 Smith Hall Zoom Link

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Bringing an investigator’s eye to complex social challenges

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Anna Russo likes puzzles. They require patience, organization, and a view of the big picture. She brings an investigator’s eye to big institutional and societal challenges whose solutions can have wide-ranging, long-term impacts.

Russo’s path to MIT began with questions. She didn’t have the whole picture yet. “I had no idea what I wanted to do with my life,” says Russo, who is completing her PhD in economics in 2024. “I was good at math and science and thought I wanted to be a doctor.”

While completing her undergraduate studies at Yale University, where she double majored in economics and applied math, Russo discovered a passion for problem-solving, where she could apply an analytical lens to answering the kinds of thorny questions whose solutions could improve policy. “Empirical research is fun and exciting,” Russo says.

After Yale, Russo considered what to do next. She worked as a full-time research assistant with MIT economist Amy Finkelstein . Russo’s work with Finkelstein led her toward identifying, studying, and developing answers to complex questions. 

“My research combines ideas from two fields of economic inquiry — public finance and industrial organization — and applies them to questions about the design of environmental and health care policy,” Russo says. “I like the way economists think analytically about social problems.”

Narrowing her focus

Studying with and being advised by renowned economists as both an undergraduate and a doctoral student helped Russo narrow her research focus, fitting more pieces into the puzzle. “What drew me to MIT was its investment in its graduate students,” Russo says.

Economic research meant digging into policy questions, identifying market failures, and proposing solutions. Doctoral study allowed Russo to assemble data to rigorously follow each line of inquiry.

“Doctoral study means you get to write about something you’re really interested in,” Russo notes. This led her to study policy responses to climate change adaptation and mitigation. 

“In my first year, I worked on a project exploring the notion that floodplain regulation design doesn’t do a good job of incentivizing the right level of development in flood-prone areas,” she says. “How can economists help governments convince people to act in society’s best interest?”

It’s important to understand institutional details, Russo adds, which can help investigators identify and implement solutions. 

“Feedback, advice, and support from faculty were crucial as I grew as a researcher at MIT,” she says. Beyond her two main MIT advisors, Finkelstein and economist Nikhil Agarwal — educators she describes as “phenomenal, dedicated advisors and mentors” — Russo interacted regularly with faculty across the department. 

Russo later discovered another challenge she hoped to solve: inefficiencies in conservation and carbon offset programs. She set her sights on the United States Department of Agriculture’s Conservation Reserve Program because she believes it and programs like it can be improved. 

The CRP is a land conservation plan administered by USDA’s Farm Service Agency. In exchange for a yearly rental payment, farmers enrolled in the program agree to remove environmentally sensitive land from agricultural production and plant species that will improve environmental health and quality.

“I think we can tweak the program’s design to improve cost-effectiveness,” Russo says. “There’s a trove of data available.” The data include information like auction participants’ bids in response to well-specified auction rules, which Russo links to satellite data measuring land use outcomes. Understanding how landowners bid in CRP auctions can help identify and improve the program’s function. 

“We may be able to improve targeting and achieve more cost-effective conservation by adjusting the CRP’s scoring system,” Russo argues. Opportunities may exist to scale the incremental changes under study for other conservation programs and carbon offset markets more generally.  

Economics, Russo believes, can help us conceptualize problems and recommend effective alternative solutions.

The next puzzle

Russo wants to find her next challenge while continuing her research. She plans to continue her work as a junior fellow at the Harvard Society of Fellows, after which she’ll join the Harvard Department of Economics as an assistant professor. Russo also plans to continue helping other budding economists since she believes in the importance of supporting other students.   

Russo’s advisors are some of her biggest supporters. 

Finklestein emphasizes Russo’s curiosity, enthusiasm, and energy as key drivers in her success. “Her genuine curiosity and interest in getting to the bottom of a problem with the data — with an econometric analysis, with a modeling issue — is the best antidote for [the stress that can be associated with research],” Finklestein says. “It's a key ingredient in her ability to produce important and credible work.”

“She's also incredibly generous with her time and advice,” Finklestein continues, “whether it's helping an undergraduate research assistant with her senior thesis, or helping an advisor such as myself navigate a data access process she's previously been through.”

“Instead of an advisor-advisee relationship, working with her on a thesis felt more like a collaboration between equals,” Agarwal adds. “[She] has the maturity and smarts to produce pathbreaking research.

“Doctoral study is an opportunity for students to find their paths collaboratively,” Russo says. “If I can help someone else solve a small piece of their puzzle, that’s a huge positive. Research is a series of many, many small steps forward.” 

Identifying important causes for further investigation and study will always be important to Russo. “I also want to dig into some other market that’s not working well and figure out how to make it better,” she says. “Right now I’m really excited about understanding California wildfire mitigation.” 

Puzzles are made to be solved, after all.

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The IU School of Medicine Department of Obstetrics and Gynecology is proud to offer the Clinical Research and Academic Success in Obstetrics and Gynecology course . The course will take place in Stowe, Vermont, at the Topnotch Resort, from Aug. 26–29, 2024.   Vermont was selected because it welcomes, affirms, and respects reproductive rights. We look forward to seeing you in Vermont!   Questions should be directed to the course director, Dr. Jeffery Peipert, MD, PhD, Clarence E. Ehrlich Professor and Department of Obstetrics and Gynecology Chair at IU School of Medicine.  

Who the program is for

What learners will gain.

• List the key attributes of an appropriate research question 
• Describe the advantages and disadvantages of longitudinal cohort studies, case-control studies and randomized clinical trials 
• Use the basic functions of a statistical software package 
• Understand the basic principles of article publication and manuscript review processes 
• Critically read research papers by understanding the main sources of bias and confounding  
• List the attributes of a good mentor and the key principles of a successful mentor-mentee relationship 
• Describe the process for promotion from Assistant to Full Professor and the “currency” of academic faculty for career advancement 

Submit an application

To apply, please email  Dr. Peipert  the following:

• A brief statement (one page or less) indicating your reason for applying
• Potential clinical research interests
• A letter of commitment for funding from chair or division director.

Participants and their departments will be responsible for travel, accommodations and tuition ($4,000).

Applications are due by May 15, 2024.

Email your application now

Course faculty

Kavita Nanda, MD, MHS

Director of Medical Research at FHI360

Kavita Nanda, MD, MS, is an internationally recognized expert in contraception. She is the director of medical research at FHI360, where she has worked as an obstetrician gynecologist, epidemiologist and scientist for almost 25 years.

For the past 18 years, she has worked as a temporary advisor to WHO, working to update the WHO Medical Eligibility Criteria and Selected Practice Recommendations for Contraceptive Use. She is also a member of the CDC guidelines development group for contraception.

Nanda received her medical degree from Albany Medical College, completed her residency at Thomas Jefferson University, and did a Women’s Health Research Fellowship and Master of Health Sciences (Clinical Research) at Duke University.

Christina M. Scifres, MD

Associate Professor of Obstetrics & Gynecology

Christina Scifres, MD, is a maternal-fetal medicine specialist at Indiana University School of Medicine. She joined the Department of Obstetrics and Gynecology faculty as an associate professor in 2018 and was named the maternal-fetal medicine division director in 2020.

Her clinical and research interests include gestational diabetes, ovarian cysts, and improving outcomes in pregnancies complicated by diabetes and obesity. She was a co-investigator for an NIH-funded randomized clinical trial comparing two screening strategies for gestational diabetes.

Scifres graduated from the University of Oklahoma College of Medicine and completed residency and a fellowship at Washington University School of Medicine.

Read Bio Christina M. Scifres, MD

Jeffrey F. Peipert, MD, PhD

Chair, Department of Obstetrics & Gynecology

Jeffrey F. Peipert, MD, PhD, is the Clarence E. Ehrlich Professor and chair of the Department of Obstetrics and Gynecology at Indiana University School of Medicine. He is board-certified in obstetrics and gynecology and has a doctorate in epidemiology.

He has conducted numerous studies including: NICHD-funded randomized trial of a computer-based intervention to encourage dual method contraceptive use to prevent unplanned pregnancy and STIs; randomized trial of therapy for pelvic inflammatory disease (PEACH Study). He was also the principal investigator of a large prospective study, the Contraceptive CHOICE Project, which recruited 9,256 women and successfully followed them for two to three years for contraceptive effectiveness, satisfaction, and continuation rates.

Read Bio Jeffrey F. Peipert, MD, PhD

Higher Resolution Brain Mapping Tech Wins Big at Research Expo

• Katherine Connor - [email protected]

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University of California San Diego electrical and computer engineering PhD student Andrew Bourhis won the top prize at the 42nd annual Jacobs School of Engineering Research Expo for his work to integrate thin film transistors into easier-to-use flexible electrode arrays, which could enable much more precise mapping of human brain activity. He was selected from among more than 160 graduate students from all six Jacobs School of Engineering departments who participated in Research Expo this year. 

Research Expo is unique in that graduate students are judged not just on the technical merits of their research, but also on their ability to effectively communicate its impact to a non-technical audience.  More than 110 judges participated this year; most judges are industry professionals, many of whom are also alumni or members of the Jacobs School’s Corporate Affiliates Program. 

In addition to the $1,500 grand prize, which is called the Lea Rudee Outstanding Poster Award, judges vote on a series of other awards that celebrate research projects from across the Jacobs School. Judges vote to select one student presenter in each of the Jacobs School’s six academic departments to receive a $750 Best Poster Award. All attendees vote to select a $500 People’s Choice Award recipient. And new this year was a Transdisciplinary Collaboration Award with a $1,000 prize. All recipients are detailed below. 

The annual event for alumni, industry partners and faculty to connect, collaborate and meet top-tier graduate students, Research Expo provides students an opportunity to practice communicating the broader significance of their work to a wide audience.

“It is essential as a successful engineer to understand and appreciate the larger context of your work,” said Albert P. Pisano, Dean of the Jacobs School of Engineering and Special Advisor to the Chancellor. “It’s one thing to be able to say ‘I made this widget,’ but it’s another to be understanding of how that improves the lives of people across the country and around the world. And that’s the primary function of engineering – we relieve needs by providing the necessary materials, systems and devices.”

Improving flexible neural interfaces

One of the goals for Bourhis’ flexible neural interfaces with built-in transistors is to provide much more granular detail on the real-time activity of a subject’s brain during surgery, restorative or therapeutic long term brain computer interface (BCI) implants. For surgery, this could enable more precise mapping of the source of epileptic activity and could also guide the removal of pathological tissue through a process called functional mapping. For therapeutic BCI, the technology could also be used to stimulate very specific regions of the brain to prevent an epileptic seizure. For restorative BCI, it could detect movement intention to allow amputees to control a prosthetic limb. 

Typical clinical electrode arrays used today must pass wires through the scalp to connect to bulky bedside instrumentation. Having transistors built into the electrode arrays reduces the need for these bulky external wires, which keep patients tethered to a hospital bed, often uncomfortable and prone to developing infection. Reducing the number of wires that connect these electrode arrays to electronics would also enable order-of-magnitude increases in the number of sensors researchers could record from, which would allow for vast improvements in the spatial resolution of the sensor arrays themselves. 

“The goal of my research is to develop thin film technologies to improve the spatiotemporal resolution of neural interfaces,” said Bourhis, a sixth year PhD student working in the lab of Electrical and Computer Engineering Professor Shadi Dayeh and co-advised by Professor Ian Galton. “The brain has nearly 100 billion neurons, and recording from even a few hundred of them can enable patients to control robotic arms to feed themselves, or play online chess using only their thoughts. We’re trying to build a technology that can one day scale up to millions of electrodes and simultaneously scale down each electrode to the size of individual neurons. But in order to do that you really need to integrate transistors into the flexible arrays, and at the same time, you need to make sure the technology is safe and can survive being implanted for years without degrading.”

While it is already possible to create nanometer-sized transistors in silicon, the brittle nature of that material makes it mostly incompatible with use on the brain, and often requires bulky encapsulation to protect against biofluid. To create a natively flexible and long-term stable interface, Bourhis and researchers in his lab were inspired by the flexible high-definition display field to develop transistors made out of IGZO (indium gallium zinc oxide) as a semiconductor material instead of silicon. IGZO has excellent electrical characteristics and can be processed at lower temperatures, meaning it can be built off of flexible plastic substrates. 

"I've been so fortunate to work with such talented colleagues who all work tirelessly for the betterment of society,” said Bourhis. “It's my dream that this research will one day help transform the lives of people currently living with incurable diseases or disabilities."

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Explaining the Why, not just the What

Being able to explain this larger context to people who are not technical experts is becoming an increasingly important skill. The new Transdisciplinary Collaboration Award was designed to help hone that skill. The brainchild of Jacobs School alumnus and longstanding Research Expo judge Sam Knight, the award is designed to encourage pairs of students – one engineering graduate student poster presenter and one non-engineering student – to work together to craft an oral presentation and poster that clearly explain the impact and significance of the work to a non-technical audience. The student pairs met several times in the weeks leading up to Research Expo to iterate on poster design and practice the oral presentation. 

“ Communicating effectively with customers in their language and context is a unique skill that not all engineers can do well, and the skills of ‘communicators’ bridge that gap,” said Knight, who donated the funds to support this $1,000 award. “I spent much of my career in that role, understanding technology and customers and translating between the two. The opportunity to collaborate with communicators outside your field, someone who can help translate great engineering ideas into the language of a diverse audience, will serve any engineer well in their future careers.”

2024 Research Expo Award Winners:

Bioengineering—Shu and K.C. Chien Best Poster

Mapping the Local Functional Consequences of Ablation for Atrial Fibrillation

Student: Noah Mehringer

Advisor: Elliot McVeigh

Computer Science and Engineering Best Poster

SemVecNet: Online Vector Map Generation through Sensor-Configuration-Agnostic Semantic Mapping

Students: Narayanan Elavathur Ranganatha, Shashank Venkatramani, Jing-Yan Liao

Advisor: Henrik Christensen

Electrical and Computer Engineering Best Poster

Monolithic Integration of High-Resolution Display Technology in Thin-Film Neural Interfaces

Student: Andrew Bourhis

Advisor: Shadi Dayeh, Ian Galton

Mechanical and Aerospace Engineering—Katie Osterday Best Poster

Stratified Wakes Past an Inclined 6:1 prolate spheroid: Dynamics and TKE Budget

Student: Sanidhya Jain

Advisor: Sutanu Sarkar

NanoEngineering Best Poster

Bowls Aren’t Just for Cereal: Nanobowl Drug Delivery For Lung Cancer Treatment

Student: Torus Washington II

Advisor: Ratnesh Lal

Structural Engineering Best Poster

Soil-Structure Interaction (SSI) Model of UC San Diego Shake Table

Student: Andres Rodriguez

Advisor: Jose Restrepo

People’s Choice Award

Scalable and Modular Distributed Avionics System: Evaluation of a Modular Distributed Data Acquisition System for Liquid Cryogenic Bi-Propellant Rockets

Student: Darrell Chua

Advisor: Karcher Morris

Transdisciplinary Collaboration Award

FishSense Lite: A Citizen Science Approach for Global Fish Population Data

Student: Kyle Hu; Collaborator:  Kayla Bacon

Advisor: Ryan Kastner

A full list of student presenters and poster titles is available here. 

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