design dissertation

How to write the perfect design dissertation

Tutors and students from top design colleges share their advice.

Studying design is about crafting a great design portfolio that will wow potential employers, right? Well, yes. But don't discount the importance of astute creative thinking, and expressing yourself eloquently through the written word. In short, your design dissertation matters.

"I don't believe that design students should be focused entirely on portfolio work," argues Myrna MacLeod , programme leader for Graphic Design at Edinburgh Napier University. "They should also be able to demonstrate an interest in the contexts that underpin their work, and the histories and connections that have informed our practice."

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"Think of a dissertation as an opportunity, not a burden," urges Craig Burston , Graphic and Media Design course leader at London College of Communication (LCC). "It gives us visually-minded people an opportunity to demonstrate that we too can construct arguments and distil complex notions." 

As Burston points out, this is not just an academic exercise: the power of persuasion is often key to success as a commercial designer. "Clients seek clarity, and project concepts or proposals need to be put into context," he says.

Read on to discover some top tips from leading tutors and their students for nailing your design dissertation…

01. Treat it like a design brief

"A great dissertation should be a designed artefact, and portfolio-worthy in its own right," says Burston. And like a design brief, it should be about solving a problem: "Make sure it has clearly stated aims, strong focus, and doesn't lack opinion or rhetoric," he adds.

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"The value of a designed dissertation as a portfolio piece is that it's a holistic view of the individual," agrees Sarah James , senior lecturer in Visual Communication at Arts University Bournemouth (AUB). 

"It shows, type, editorial, research and aesthetic skill, as well as the personal interests and convictions of the individual."

James identifies AUB student Maarit Koobas , who investigated responsive type in both her dissertation and final project, as a particularly strong example of this. "Her design version was one of the most authentic, restrained and elegantly expressive I have ever received," she enthuses.

Koobas conducted a huge amount of initial research into both the contexts in which responsive type can be seen – such as advertising, product design, science and material cultures – and the theories behind its analysis, including semiotics, philosophy and politics. "Creating and analysing ideas, before they end up in your portfolio, is what design is all about," argues Koobas.

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02. Write about your passion

"To develop essay questions, AUB students are asked to consider what they love, hate or are puzzled by in their practice – essentially, what moves them," says James. 

"A poor dissertation is inauthentically chosen for ease as opposed to interest," she adds. "It rambles and blusters, using complex language to mask insufficient research." 

"You can tell a mile off when the writer isn't interested," agrees Burston. "How can you expect the reader to care about it if you don't? Write about something that reflects your interests, focus and direction. I've read fascinating dissertations on topics as diverse as patterns in nature, and Brutalist car parks. Make me interested in what interests you."

For Edinburgh Napier graduate Fiona Winchester , this topic turned out to be typography in graphic novels. "I love reading them, but I think people still don't take them seriously as an art form, which is a shame," she says. For her dissertation, she conducted qualitative interviews using modified pages with and without imagery (shown above). 

Her advice is simple: "Narrow down your idea to be as precise as possible. The smaller your question, the easier it is to research and try to answer it."

If you're struggling to get the ball rolling on the actual writing process, Winchester advocates starting with whichever bit you have ideas for. "If you're stuck, it's so much easier to write in whatever order it comes to you, and then edit it into a dissertation, than to try write straight through from beginning to end," she insists.

03. Don't be afraid to talk to people

"I always think my students get the most out of the new streams of knowledge they find from talking to people," says McLeod. "It breaks down barriers and allows them to find answers to problems. Hopefully they will adopt that approach when designing for people also."

In some cases, this can involve interviewing your design heroes. "Students are very surprised when they send a question to Stefan Sagmeister , Milton Glaser or Michael Wolff and they reply with the most precious nugget of knowledge," smiles McLeod. 

But remember: it's your dissertation, so don't get lazy and expect your interview subject to do all the heavy lifting.

In other cases, it could be as simple as asking friends or family to help proofread. "It is quite daunting writing such a large body of text," admits Kaori Toh , a recent graduate from Central Saint Martins, whose dissertation explored the politics of design and technology.

"I often felt I'd get lost in all that text and research," she confesses. "Therefore, I would often send my drafts to a couple of friends to have them look through, and keep my writing cohesive."

04. Reflect on your design practice 

Most of all, dissertations are an opportunity to reflect on, and develop, your creative process as a designer. "Ultimately, it's your job to make your work relevant and credible, and the dissertation helps you learn how to do this," adds Burston. 

Of course, writing doesn't always come easily to visually minded people – and Burston highlights the fact that dyslexia is not uncommon amongst designers. 

"You're not on your own – in our profession, quite the opposite in fact – so do seek academic support, and just enjoy thinking and writing about 'stuff' that informs your practice," is his advice.

One of Burston's stand-out students from this year, Tom Baber , welcomed support from the university to help with his dyslexia. Baber's dissertation focused on type design, and particularly the extent to which the longwinded design process is worth the effort, compared to using an existing typeface.

"I saw it as an opportunity to approach other type designers and see what they thought. Turns out I'm not the first to ask the question," he smiles. "Writing my dissertation helped me change from a 'maker' mentality to a 'designer' mentality, and be more critical of my ideas."

Related articles:

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• Cookies & Privacy
• GETTING STARTED
• Introduction
• FUNDAMENTALS

Getting to the main article

Choosing your route

Setting research questions/ hypotheses

Assessment point

Building the theoretical case

Setting your research strategy

Data collection

Data analysis

Research design

The quantitative research design that you set in your dissertation should reflect the type of research questions/hypotheses that you have set. When we talk about quantitative research designs, we are typically referring to research following either a descriptive , experimental , quasi-experimental and relationship-based research design, which we will return to shortly. However, there are also specific goals that you may want to achieve within these research designs. You may want to: (Goal A) explore whether there is a relationship between different variables; (Goal B) predict a score or a membership of a group; or (Goal C) find out the differences between groups you are interested in or treatment conditions that you want to investigate:

GOAL A Exploring the relationship between variables

Are you trying to determine if there is a relationship between two or more variables, and what this relationship is? This kind of design is used to answer questions such as: Is there a relationship between height and basketball performance? Are males more likely to be smokers than females? Does you level of anxiety reduce your exam ability?

GOAL B Predicting a score or a membership of a group

Are you trying to examine whether one variable's value (i.e., the dependent or outcome variable) can be predicted based on another's (i.e., the independent variable). These designs answer questions such as: Can I predict 10km run time based on an individual's aerobic capacity? Can I predict exam anxiety based on knowing the number of hours spent revising? Can I predict whether someone is classified as computer literate based on their performance in different computer tasks? Can I predict an individual's preferred transport (car/motorcycle) based on their response to a risk questionnaire?

GOAL C Testing for differences between groups or treatment conditions

Are you trying to test for differences between groups (e.g., exam performance of males and females) or treatment conditions (e.g., employee turnover among employees (a) given a bonus and (b) not given a bonus)? This type of design aims to answer questions such as: What is the difference in jump height between males and females? Can an exercise-training programme lead to a reduction in blood sugar levels? Do stressed males and females respond differently to different stress-reduction therapies? In each of these cases, we have different groups that we are comparing (e.g., males versus females), and we may also have different treatments (e.g., the example of multiple stress-reduction therapies).

Goals A and B reflect the use of relationship-based research questions/hypotheses, whilst goal C reflects the use of comparative research questions/hypotheses. Just remember that in addition to relating and comparing (i.e., relationship-based and comparative research questions/hypotheses), quantitative research can also be used to describe the phenomena we are interested in (i.e., descriptive research questions). These three basic approaches (i.e., describing , relating and comparing ) can be seen in the following example:

Let's imagine we are interested in examining Facebook usage amongst university students in the United States .

We could describe factors relating to the make-up of these Facebook users, quantifying how many (or what proportion) of these university students were male or female, or what their average age was. We could describe factors relating to their behaviour, such as how frequently they used Facebook each week or the reasons why they joined Facebook in the first place (e.g., to connect with friends, to store all their photos in one place, etc.).

We could compare some of these factors (i.e., those factors that we had just described). For example, we could compare how frequently the students used Facebook each week, looking for differences between male and female students.

We could relate one or more of these factors (e.g., age) to other factors we had examined (e.g., how frequently students used Facebook each week) to find out if there were any associations or relationships between them. For example, we could relate age to how frequently the students used Facebook each week. This could help us discover if there was an association or relationship between these variables (i.e., age and weekly Facebook usage), and if so, tell us something about this association or relationship (e.g., its strength, direction, and/or statistical significance).

These three approaches to examining the constructs you are interested in (i.e., describing , comparing and relating ) are addressed by setting descriptive research questions, and/or comparative or relationship-based research questions/hypotheses. By this stage, you should be very clear about the type of research questions/hypotheses you are addressing, but if you are unsure, refer back to the Research Questions & Hypotheses section of the Fundamentals part of Lærd Dissertation now.

If you are exploring the relationship between variables (i.e., Goal A ), you are likely to be following a relationship-based research design (i.e., a type of non-experimental research design). However, if you are predicting the score or a membership of a group (i.e., Goal B ) or testing for differences between groups or treatment conditions (i.e., Goal C ), you are likely to be following either an experimental or quasi-experimental research design. Unless you already understand the differences between experimental, quasi-experimental and relationship-based research designs, you should read about these different research designs in the Research Designs section of the Fundamentals part of Lærd Dissertation now. You need to do this for two main reasons:

You will have to state which type of research design you are using in your dissertation when writing up the Research Design section of your Chapter Three: Research Strategy .

The research design that you use has a significant influence on your choice of research methods , the research quality of your findings, and even aspects of research ethics that you will have to think about.

Once you are familiar with the four types of research design (i.e., descriptive, experimental, quasi-experimental and relationship-based), you need to think about the route that you are adopting, and the approach within that route in order to set the research design in your dissertation:

• ROUTE A: Duplication
• ROUTE B: Generalisation
• ROUTE C: Extension

Route A: Duplication

If you are taking on Route A: Duplication , you would typically not be expected to make any changes to the research design used in the main journal article when setting the research design for your dissertation. After all, the purpose of the dissertation is duplication , where you are, in effect, re-testing the study in the main journal article to see if the same (or similar) findings are found. An important aspect of such re-testing is typically the use of the same research strategy applied in the main journal article. As such, if an experimental research design was used in the main journal article, with 3 groups (e.g., two treatment groups and one control group), your dissertation would also use an experimental design with the same group characteristics (i.e., 3 groups, with two treatment groups and one control group). The research design you used would also have the same goals as those in the main journal article (e.g., the goal of relating two constructs, perhaps study time and exam performance, in order to answer a relationship-based research question/hypothesis).

However, there are some instances where, from a practical standpoint, you may find that it is not possible to use the same research design, perhaps because an experimental research design was used, but you are unable to randomly selected people from the population you can get access to, forcing you to use a quasi-experimenta l research design. But the goal will be to use the same research design in your dissertation as the one applied in the main journal article. Again, you can learn about the differences between experimental and quasi-experimental designs in the Research Designs section of the Fundamentals part of Lærd Dissertation.

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 .

Psst… there’s more (for free)

This post is part of our dissertation mini-course, which covers everything you need to get started with your dissertation, thesis or research project. 

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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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SCI-Arc Breadcrumbs News

• March 26, 2024

Undergraduate Thesis 2024 Engages the Cultural Moment with Visionary Design

In acknowledgement of the extraordinary work done by the 2024 Undergraduate Thesis class, SCI-Arc is proud to announce its 2024 UG Thesis Weekend April 19–20, as this year’s graduating thesis students present and share their accomplishments with the world. “Thesis is a process of critical and curious engagement with the world,” shares Undergraduate Thesis Coordinator Maxi Spina, “an extraordinary time to take risks, to research intensively, and to consider a world outside oneself. Ideas, philosophies, and debates become mediums alongside materials, processes, and systems, as architecture becomes a practice of propositions." Each year, Undergraduate Thesis at SCI-Arc prepares fifth-year B.Arch students to articulate, propose, and defend their ideas and positions on architecture as well as engage with professionals as peers and colleagues. In their final semester of design studio, students in SCI-Arc’s Undergraduate Thesis class complete the production of a year-long thesis project, which addresses a position in relation to contemporary architectural discourse and presents a highly developed building design project. Topics students inquired into through their thesis projects this year represent a vibrant cross section of the cultural moment—from the design of affordable housing to large public venues that provide equitable access to culture, sports, and athletics, to the architecture of the circular economy. This year’s thesis class uniquely highlights the discipline’s efforts to deepen its agency and entanglement with contemporary issues. April 19-20, SCI-Arc’s fifth-year B.Arch students will present their thesis projects during an immersive, in-person Undergraduate Thesis Weekend, a public platform during which over 80 jurors, critics, and architecture professionals from around the globe converge to discuss, debate, and dispute emerging questions in architecture. SCI-Arc’s 2024 Undergraduate Thesis Weekend will be held at SCI-Arc’s Arts District campus, so the public and visiting guests alike can experience the boundary-pushing work of this year’s remarkable Undergraduate Thesis class. Keep an eye on the Undergraduate Thesis 2024 event page for updates on how to access review schedule for the entire weekend, participating juror list, student thesis projects, and more.

Efficient Decentralized Learning Methods for Deep Neural Networks

Decentralized learning is the key to training deep neural networks (DNNs) over large distributed datasets generated at different devices and locations, without the need for a central server. They enable next-generation applications that require DNNs to interact and learn from their environment continuously. The practical implementation of decentralized algorithms brings about its unique set of challenges. In particular, these algorithms should be (a) compatible with time-varying graph structures, (b) compute and communication efficient, and (c) resilient to heterogeneous data distributions. The objective of this thesis is to enable efficient decentralized learning in deep neural networks addressing the abovementioned challenges. Towards this, firstly a communication-efficient decentralized algorithm (Sparse-Push) that supports directed and time-varying graphs with error-compensated communication compression is proposed. Second, a low-precision decentralized training that aims to reduce memory requirements and computational complexity is proposed. Here, we design ”Range-EvoNorm” as the normalization activation layer which is better suited for low-precision decentralized training. Finally, addressing the problem of data heterogeneity, three impactful advancements namely Neighborhood Gradient Mean (NGM), Global Update Tracking (GUT), and Cross-feature Contrastive Loss (CCL) are proposed. NGM utilizes extra communication rounds to obtain cross-agent gradient information whereas GUT tracks global update information with no communication overhead, improving the performance on heterogeneous data. CCL explores an orthogonal direction of using a data-free knowledge distillation approach to handle heterogeneous data in decentralized setups. All the algorithms are evaluated on computer vision tasks using standard image-classification datasets. We conclude this dissertation by presenting a summary of the proposed decentralized methods and their trade-offs for heterogeneous data distributions. Overall, the methods proposed in this thesis address the critical limitations of training deep neural networks in a decentralized setup and advance the state-of-the-art in this domain.

Degree Type

• Doctor of Philosophy
• Electrical and Computer Engineering

Campus location

• West Lafayette

Advisor/Supervisor/Committee Chair

Additional committee member 2, additional committee member 3, additional committee member 4, usage metrics.

• Deep learning
• Neural networks

Hope Bass MFA Thesis Exhibition

Integrated visual arts graduate student hope bass to share work exploring ceramics and ‘the curiosities of the imagination’ in mfa exhibition at iowa state.

AMES, Iowa — Iowa State University integrated visual arts graduate student Hope Bass will share ceramics, mixed-media artwork, installations and sculptures in her master of fine art thesis exhibition.

“Metamorphosis of Hope: A Ceramic Journey through Imagination and Wonder” will be on display April 17–26 in Gallery 181, located on the first floor of the College of Design building on the west side of the Iowa State Campus.

Exhibition viewing hours are 8 a.m.–5 p.m. weekdays. Admission is free. A reception will be from 5–8 p.m. Friday, April 19.

Bass’ master’s thesis explores the relationship between the wonders of ceramic exploration and the curiosities of the imagination, she said. Most of her artworks are inspired by the fantastical creatures living within the grotesques she saw while studying in Italy in summer 2022, which paralleled her thoughts and “reinforced the connections between my creative endeavors and the boundless realms of the imagination,” she said.

About the artist

Bass, from Ardmore, Oklahoma, received her bachelor of fine arts in studio art with an emphasis in sculpture and a minor in art history from the University of Central Oklahoma in 2021. She has been a graduate teaching assistant for art history and ceramics courses throughout her studies at Iowa State.

As a graduate student in the integrated visual arts program, her artwork has been exhibited in Octagonal: The All Media Show (2024) at the Octagon Center for the Arts in Ames, the Iowa State Fair Fine Art Exhibition (2022, 2023) in Des Moines and the Studies in Creativity (2021, 2022, 2023), Nostalgia (2022) and Home (2023) exhibitions at the Memorial Union Art Gallery.

Bass will graduate with her MFA in integrated visual arts from Iowa State in May.

Hope Bass, Graduate Student, Integrated Visual Arts, [email protected] Heather Sauer, Director of Strategic Communications, College of Design, [email protected]

• Art and Visual Culture
• Current Students

Intensification of evaporation of uranium hexafluoride

• Chemical Engineering Science and Chemical Cybernetics
• Published: 14 August 2013
• Volume 47 , pages 499–504, ( 2013 )

Cite this article

• A. M. Belyntsev 1 ,
• G. S. Sergeev 2 ,
• O. B. Gromov 2 ,
• A. A. Bychkov 1 ,
• A. V. Ivanov 2 ,
• S. I. Kamordin 3 ,
• P. I. Mikheev 4 ,
• V. I. Nikonov 2 ,
• I. V. Petrov 1 ,
• V. A. Seredenko 2 ,
• S. P. Starovoitov 1 ,
• S. A. Fomin 1 ,
• V. G. Frolov 1 &
• V. F. Kholin 2  

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The theoretical mechanism of the sublimation of uranium hexafluoride are considered. The most contribution to the rate of evaporation of UF 6 is introduced by the conductive mode of heat exchange. Various modes of the intensification of the evaporation of uranium hexafluoride during the nitrogen supply in pulse mode to the product mass are investigated. The nitrogen supply results in the turbulization of gas flow within a vessel (Re = 2500–4000) and significantly increases the rate of evaporation of uranium hexafluoride with the substantial decrease in a weight of the nonevaporable residue of 5.6–1.0 kg. The complex application of the pulse nitrogen supply in combination with heating the bottom of the vessel is the most effective method for evaporating uranium hexafluoride. The rate of evaporation of UF6 increases by a factor of almost four in comparison with the design mode. The developed methods are applied in industry and provide the stable operation of Saturn reactors during the conversion of uranium hexafluoride into its dioxide.

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Obtaining Hydrogen Fluoride During the Interaction of Uranium Hexafluioride with Hydrogen and Oxygen in a Combustion Regime. Experiment

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Engineering Works, Elektrostal’, Moscow oblast, Russia

A. M. Belyntsev, A. A. Bychkov, I. V. Petrov, S. P. Starovoitov, S. A. Fomin & V. G. Frolov

Leading Research Institute of Chemical Technology, Moscow, Russia

G. S. Sergeev, O. B. Gromov, A. V. Ivanov, V. I. Nikonov, V. A. Seredenko & V. F. Kholin

Bochvar All-Russia Research Institute of Inorganic Materials, Moscow, Russia

S. I. Kamordin

Bauman Moscow State Technical University, Moscow, Russia

P. I. Mikheev

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Original Russian Text © A.M. Belyntsev, G.S. Sergeev, O.B. Gromov, A.A. Bychkov, A.V. Ivanov, S.I. Kamordin, P.I. Mikheev, V.I. Nikonov, I.V. Petrov, V.A. Seredenko, S.P. Starovoitov, S.A. Fomin, V.G. Frolov, V.F. Kholin, 2011, published in Khimicheskaya Tekhnologiya, 2011, Vol. 12, No. 11, pp. 675–681.

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Belyntsev, A.M., Sergeev, G.S., Gromov, O.B. et al. Intensification of evaporation of uranium hexafluoride. Theor Found Chem Eng 47 , 499–504 (2013). https://doi.org/10.1134/S0040579513040040

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Received : 25 January 2011

Published : 14 August 2013

Issue Date : July 2013

DOI : https://doi.org/10.1134/S0040579513040040

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Contact S.24: Photography BFA Thesis Exhibition

April 5, 2024

Colvard Student Union Art Gallery

On display April 5th through April 19th, 2024 in the Colvard Student Union Art Gallery,  Contact S.24  features recent photography work by Mississippi State University graduating senior Nathan Jones of Louisville, Kentucky.

Under the direction of the Department of Art's Photography Concentration Coordinator, Professor Marita Gootee, Jones created a portfolio of photography exploring the effects of anxiety. According to Jones, "My work seeks to illuminate the interplay of internal feeling and external surroundings, offering viewers a glimpse into the profound depths of the anxious mind."

A public reception with refreshments will be held  Friday, April 5 from 5:00 p.m. – 6:00 p.m.  in the Colvard Student Union Art Gallery, located on the second floor of the MSU Colvard Student Union. Regular gallery hours are 8:00 a.m. to 5:00 p.m. daily.

For more information on this exhibition or any gallery programs, contact the Department of Art at 662-325-2970, or email Lori Neuenfeldt, gallery director at  [email protected] .

Click to Visit Nathan Jones' Portfolio Website

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