PlaceME@SMI is a placement scheme funded by the Sheffield Q-Step Centre which is part of the Sheffield Methods Institute at The University of Sheffield.
We are giving undergraduate students a chance to work on exciting projects involving analysis of quantitative data, with our external partners such as commercial businesses and government organisations or internally with our leading researchers.
Our placements are advertised here on our website, with new placements going live when details are received.
What you need to know
The 2019 placements will be advertised in March but you can see examples of last year's placements here.
Some of our partners
PlaceME@SMI case studies
Ed @ Dubit
During my first couple of weeks the job mostly consisted of familiarising myself with the data and the methods. This involved navigating my way through the filing systems and discovering the content of the data and how to interact with it. Many of the projects Dubit works on, begin with the same foundations of data. This is the Trends Tracker, a large collection of data compiled in a 130-page report on each country or discipline. The raw data is considerably large and provides insights into children’s tastes and trends. This could be what toys are currently popular, how much time children are spending on devices or the difference between what apps girls and boys are using.
A regular occurrence in the office is draft meetings where a few members of the team get together and create ideas about how to win contracts, bring in more business or to make changes to the current products. In my first few days I was involved in a project to try and win a contract from a major book firm. The contract wanted to explore children’s relationship with books and what drives book trends. Luckily the weather was hot so it took place outside in the park! The research team has morning meetings every day to gather thoughts and to keep track of everyone’s progress and this is where the team bonding happens. Everyone at Dubit is friendly and bubbly so it’s easy to fit in. The team is only small and half of them were interns but it didn’t take long to feel like part of the team.
During the third and fourth weeks I had become familiar with the format of the data and how the majority of research projects work. I had become quite efficient at data checking and was quite easily going through 100 slides of data a day. Data checking is the majority of the job at this point but it gets easy and quicker the more you do it.
During the fourth week I had been assigned two research projects that I would be in charge of. This meant conducting primary research and combining this with secondary data to produce investigative reports. These projects were; Research into the Children’s VR Market and An App Research report: examining the purchase journey of parents and children.
The first project, looking into the VR market began with some fun research, which involved testing out both the high-end and the low-end VR hardware. Working with another intern we tested out the HTC Vive, the Oculus Rift and the Google Cardboard. The research included testing the newest line of games and talking to the VR team and getting their insights into where there is potential for the VR market. The VR report was starting to take shape, at this point it was in the form of a written report rather than the end product; a blog post. I was producing graphs and tables to show the size and growth of the VR market this initial research was time consuming, as there are so many sources of information for the VR market.
The work still largely consisted of data checking. The team was preparing trend reports for a range of different countries including; Brazil, UK, US, Spain, Mexico and more. These reports are around 200 slides long and once the data is inputted, there needs to be thorough checks to make sure everything is precise. During my last week we were finalising the reports for Spain and Mexico. The VR project was well on its way and nearly ready for hand in. There were two separate documents that had been created through this research project. A presentation with the basic information about the Virtual Reality market and a blog post. The blog post is around 1000 words long and will be published on Meduim. The blog needed multiple tweaks to ensure that it was written in the right format and that all the details were correct. The final report gave a brief overview of the VR market, what things were up and coming and potential for investments.
During the fifth week I was given the opportunity to run the online focus group. I had to contact a resource firm that specialised in hiring respondents. I oversaw the financial side of hiring the respondents. After I had prepared the script based on secondary research into the app market I was prepared for the focus group. After work in the final week I ran the focus group. It gave me a great insight into the firm’s research methods but also the findings of the group gave me a new insight into the app market from a parent’s perspective.
My experience of Dubit has been great from start to finish. The team were all great and easy to get on with. There were also two other interns who were there at the same time and we were are given multiple project together. The ability to communicate well with everyone was essential and in the end, I have made some great friends who I will remain in contact with. The highlight of my experience was my last Friday team meeting. Everyone in the team was there and all in a great mood. Beers were brought out and it was a great way to finish my amazing internship.
|Rachel @ WPREU||
Within my placement at the University of Sheffield's Widening Participation Research and Evaluation Unit (WPREU), I am tasked with analysing data about the 2017 undergraduate cohort. Specifically, I aim to explore and identify the proportion of students with various characteristics, at an institutional, faculty and departmental level.
My placement provides an opportunity for me to gain real-world knowledge and experience regarding widening participation to higher education. For example, I will gain knowledge about the proportion of students from disadvantaged areas, the proportion of Black Minority Ethnic (BME) students, and the proportion of undergraduates who study whilst simultaneously supporting dependants.
This project is my first opportunity to analyse a large-scale, real-world data set in SPSS. I anticipate that the skills and experience I develop over the course of the placement will be highly useful across my career path. The opportunity to utilise industry software with the analysis of real-world data will hopefully prepare me for similar projects on a professional basis. Furthermore, the placement will complement my academic work within the Sheffield Methods Institute, where I learnt about the philosophical underpinnings of research, and how to conduct rigorous research. I will be able to put what I have learnt within an academic setting into practice.
I am looking forward to having the opportunity to work with social and educational data, as it may guide the direction of my career. I will be able to get a real sense of the research industry, and see if I thrive in this particular environment, or whether I should rethink my current career path. Overall, due to my upbringing, the issues of widening participation and ensuring that access to higher education is fair and equal are very close to my heart. I am looking forward to the dual opportunity to hone my employability skills, whilst simultaneously learning more about and working within a cause I am passionate about.
At this current stage in the placement, I have used SPSS to analyse the dataset at an institutional level, exploring a wide variety of widening participation indicators. My next task will be undertaking analysis at a faculty and departmental level.
I feel like I have got to grips with the basics of SPSS, and analysing descriptive statistics, providing me with the building blocks necessary in order to use the software in my future career. This new experience has made me feel more confident in conducting research and analysing data. Such skills will be crucial when undertaking my dissertation.
I have also written reports which summarise and explain my results. I have had to try to make the information accessible, interesting and visually appealing. It is hard to find the balance between providing sufficient detail, without making the volume of data overwhelming or make the report look cluttered and overloaded. Although this report is quite different to my academic work, the skills gained will be highly useful to me across my degree, as being able to present results in an interesting and accessible way for the general reader is often a requirement for assessed work.
One benefit of placements is that they allow people to test the waters before fully committing themselves to a certain career or role. I have heard from other placement students that completing this placement has guided them in regards to their graduate aspirations. Undertaking the placement has cemented my plan to work as a Social Researcher, as I now know that I enjoy doing this on a day to day basis.
Spending my summer preparing for my future career has been much more productive, and enjoyable than simply having a regular summer job, such as in retail. Not only is it more impressive and relevant for my Curriculum Vitae, but it is much more interesting and engaging.
As my placement comes to a close, I have begun to reflect upon my experiences at WPREU. One of the biggest things I will take away from the experience is increased speed and efficiency. Trial and error of what worked took a lot of time while I familiarised myself with the process. For example, at first I heavily relied on the Mouse commands in SPSS. But now, I am much more comfortable utilising syntax, which is a much faster and more effective method. I feel that if I was set a similar task now with the knowledge and experience that I have gained, I would be capable of completing the assignment in around half the time it has taken me. Increased familiarity and efficiency will be incredibly useful when I undertake my dissertation and within my upcoming career.
One aspect of the placement that I appreciate is the opportunity to present and explain my findings at a dedicated workshop session. This will give me the opportunity to gain crucial feedback which I can implement during future research. Additionally, I will be able to increase the visibility of my work and provide interested individuals with further information. It will also help boost my presentation and communication skills, which are key in many jobs.
Something that I have learnt over the course of my placement is how much further there is to go in terms of making university accessible to all. Before my placement, I knew that certain types of people are more likely to go on to Higher Education, whereas others are underrepresented. However, seeing the figures first-hand really helped me understand. I was always passionate about widening participation to university, but completing this placement has made me a lot more aware of the nature of the issue. I will definitely be more mindful of issues surrounding widening participation as a result of completing this placement.
|Megan @ Shelter||
Since starting my summer placement at Shelter, I have been made to feel very welcome and like a valuable part of the team. My role at Shelter is to provide evidence and information that the digital advice team can use as a starting point for creating content on the website that helps people to find solutions to housing problems. I have also been given a lot of independence to use the knowledge that I have gained through my degree when offering insight into the people who need Shelter’s services.
Earlier this week, I had the opportunity to visit the head office in London, and to meet people who work in different areas in the organisation. I was able to learn how different roles within the organisation fit together as well as how people could help me to reach the aim of my placement. For example, I met with policy researchers to learn about their approach and how I might apply their methods or resources to my advice research. They also helped to show me how I can apply the knowledge that I already have, and how the skills that I have gained doing a quantitative degree are used in a working environment.
I have been introduced to other software and programmes during my placement so far that build on skills I already have learned, or introduce something that is completely new to me. At Shelter, many people use Google Analytics to look at trends on the website, and so I have been able to learn how to use this programme and how it can support my existing abilities. One new area I have explored is web content design, using a programme called Squiz which lets you edit and publish webpages. Having the chance to try new things like this has made the placement at Shelter exciting and useful, since I am gaining skills beyond what I will learn through my degree.
Over 5 million people visit Shelter’s housing advice website each year, and the digital advice team in Sheffield produce and manage these pages that deal with issues from homelessness, eviction, bad conditions and benefits. My focus within this team has been on researching the private rented sector of housing in England and finding out what kind of problems people experience to make sure that the advice given is always as helpful as possible.
I have mainly worked with YouGov data, which is different to a lot of the data I have worked with before because the survey has been conducted specifically for Shelter to research this area. I could draw on a lot of demographic characteristics and find out more about people’s feelings and attitudes, rather than just their situation which is all that I would be able to find in publicly available government data.
Since I’m trying to find out who experiences certain issues in the private rented sector, I have used a series of logistic regressions to find out who is more likely to be affected by certain problems. I have found consistently that people with disabilities or illnesses that limit their daily lives and people with dependent children are more likely to experience problems, for example being harassed by a landlord. I have also looked at the differences in certain issues on a local level, and made a series of interactive maps to demonstrate which areas have a higher proportion of private landlord evictions.
While doing this, I’ve had the opportunity to participate in the advice team’s work in several other ways. Firstly, I took part in discussions and plans for including infographics on the website, and I have found that thinking about infographics from another perspective has improved the way I approach data visualisation. I was also invited to join the ‘crit’ where the people who write the advice pages share what they have written and the rest of the team offers their suggestions to improve the work. Being a part of this exercise made me feel like a valued part of the team and was a really interesting experience. While I’m not a writer, I got to offer my thoughts as someone who doesn’t know a lot about housing - like the reader, and it made me think more about how to adapt my work to whoever needed to use it.
Now that I’m at the end of my placement at Shelter, I feel like I have been able to help provide the digital advice team towards with evidence of what kind of problems people experience so that they can tailor their work to what people need and ensure they are delivering the right advice and information to the right people. This has been really rewarding because the information that they give is so helpful to millions of people in situations of bad housing, and I have been able to help ensure that this reaches as many of the people who need it as possible.
I gave a presentation of my findings to people from the digital advice team as well as people from other areas, like the helpline and web chat advisers. When I showed my findings, they offered their own experiences and we were able to discuss what were the reasons behind some of the results. For example, several advisers commented that a lot of people that they support with these issues are from London. I was able to offer an explanation, saying that my results suggested that people were more likely to have these experiences in London because of factors like the younger average age and the fact that more people struggle to afford rent there. I felt that everyone seemed genuinely interested in my research so I appreciated the opportunity to share what I had found.
By having a lot of independence to complete this project in the way that I think is best, I have learned a lot about the way that I work best and how to use the skills I have gained at the SMI in practice. Throughout my placement, I’ve also needed to convey my findings to people who are not familiar with the same methods and jargon that I might use when describing my work at the SMI, so I’ve had the opportunity to build on my communication skills.
As well as having learned a lot and being proud of the work that I’ve produced, I’ve really enjoyed my time at Shelter. Everyone that I’ve worked with has been extremely kind and welcoming – from regular tea and coffee rounds in the digital advice team, to lots of friendly faces across the whole office. Overall, this placement has been such a positive experience and I’m really happy to have had the opportunity to do it.
Olivia @ WPREU
This summer I worked on two research projects for the WPREU team at the University of Sheffield. I worked for them last year, working on the ‘Further Exploration of the Attainment Gaps at the University of Sheffield’ report. I was therefore already used to the office environment and the team at WPREU. I enjoyed returning for another summer placement.
I wanted to expand my experience of research projects by undertaking both qualitative and quantitative research projects. I am working on a qualitative project on the experiences of mature students, which will involve a series of interviews in the last few weeks of my placement. I have never undertaken this type of research before so I am excited to gain some new experience. I am currently waiting for the ethics application approval to move forward with this project.
I am also working on a quantitative project, looking at the attainment data for medicine and dentistry students. I have not looked at their attainment before, so I have to get used to different attainment data and marking systems. However, since I have completed my final year of my degree, I can utilise my extended knowledge of data analysis and the different techniques and methods for SPSS that I learnt whilst completing my dissertation. Furthermore, their attainment patterns are very different to the rest of the institution so I have had to do more academic research to understand the existing literature on the study of medical and dental student attainment. I am looking forward to completing my two projects and presenting them at the WPREU SMI project presentations in September.
The placement is providing me with some useful insights into the world of work. I have had the freedom to design the projects that I want to work on and decide which methods I will use.
As shown in the graph below, I wanted to give the reader all the information by giving them a full histogram of the attainment, but I also wanted to give a general overview, so I used the Normal line. By offering further information of the mean, standard deviation and number of cases, I allowed the reader to decide how much information they wanted to take from the visualisation of the data.
During my final weeks I did my presentation for the reports I completed during my placement. The report I talked about were the quantitative reports studying student attainment, using data from the Medicine and Dentistry departments.
As I have already done a presentation for my placement at WPREU last year, and repeated this presentation for the university-wide WPREU forum in May, I was more confident for this presentation. Myself and three other interns presented, to an audience of around thirty stakeholders in the university. Among them were attendees from the staff at the medical and dentistry departments, so my presentation was of particular interest to them.
I designed my presentation to be a brief summary of my analysis and final report. I wanted to give people an overview of my work, and report the key findings without making the presentation too long. I knew if it was too long or included too much jargon or figures that I may not hold people’s attention. The presentation went well, I felt I presented my research concisely and it was received well. It sparked an interesting debate among the audience members about the importance of analysis of attainment in separate departments within the university.
There was also a lot of support for analysing the medical and dentistry departments separately from the rest of the institution because there is a very different social and academic culture within these departments. It seems that there will be demand for similar research in the next few years, to assess the situation. I have found this placement really interesting, and it has been great to see my research projects so well-received by stakeholders in the university.
Ben @ WPREU
In the first two weeks of placement with WPREU I have already found it incredibly useful, intriguing and enjoyable. I have been tasked with replicating, comparing and then furthering a research project conducted in 2015 into the attainment gap between white and BME (Black and Minority Ethnic) students.
This has involved me working with new colleagues to collate a suitable dataset covering 2016 to 2018 and then exploring this to produce an updated report. The team is a small group of seven who all work closely in both in space with all members being in the same office, but also in communication with thoughts and queries constantly being shared. Through this group I have been helped to settle into this working environment through not only work related support but also occasional team activities such as going for lunch.
A key appeal of this placement was the usefulness it will have in the development of my skills analysing data due to use real life datasets that I can directly relate to unlike in any research project conducted for university courses. The feeling that I may have an impact on implementing positive changes was another reason and something else I will look at, whether an encouraging effect was had the last time this report was produced. The exploration of this new data has required, and therefore given me the opportunity to, improve my skills using SPSS which before now I had only used sparsely and for very basic analysis. So far I have managed to combine this with my higher level of understanding of R studio to produce both tables and graphs visualising the trends or patterns shown by the data.
After completing my replication of the previous project I expect to look for findings of my own through further analysis and also to work with other members of the department to construct regression models in an attempt to explain the differences in attainment scores between particular demographics especially focusing on the problem of the BME attainment gap.
With my progression through this placement I become more pleased with my choice due to feeling more relaxed, confident and engaged in the project. This time has allowed me to successfully complete my replication of the process followed three years ago and therefore make comparisons and view any changes that have taken place. The main conclusion that can be drawn when observing the data as a whole is the persistence of the BME (Black and Minority Ethnic) attainment gap which, despite fluctuating in size over the recent years was recorded as White students on average achieving 10.2% more 1sts or 2:1s in 2018.
Due to the problem being as noticeable as previously the same steps were taken to rule out other variables from being the causal factor that provided this variation in grades. The areas tested were prior attainment, socioeconomic background and then a between faculty comparison. After plotting these results, it was apparent that these could not be identified as the root effectors in the attainment gap due to the continuing lower percentages for BME students throughout, not the crossover that would have been needed.
In an attempt to progress this research, I decided to test a different measure of socioeconomic status’ effect on the grades of varying ethnicities. For this I used the Indices of Multiple Deprivation (IMD) which rank 33,000 areas in England from most to least deprived. Despite once again finding that the gap remained an interesting discovery was made that the mean IMD score and % of 1st or 2:1 grades follow a similar pattern when subset by ethnicity.
The progression of this research will be to move onto regressions which will hopefully give a more detailed view of the degree of impact that certain variables have on grades rather than just inspecting graphs and percentages.
This placement has been useful for what it has taught me in a variety of ways. At the core of the project I have learnt how to construct a report which will be used in the real world, unlike anything I have done before, but furthermore I have learnt about the huge efforts that go on behind the scenes at the University of Sheffield. Working with WPREU has shown that significant actions are attempting to not only help students from a range of backgrounds attend the University but also once they arrive take steps to improve their experience. My practical skills have been developed through this process as well with both SPSS and R Studio being needed for the analysis and visualisations respectively. The practice and problem solving has furthered my ability on these programmes which will undoubtedly be of great use for University work.
The main purpose of my study was to investigate whether the same conclusion would be drawn as in the report that had been conducted three years previous and after finalising my research it was clear that there were no changes of note, the BME attainment gap was still an issue. After conducting the same procedure of controlling for alternative variables the gap remained providing the same message that it could not be explained by prior attainment or socioeconomic factors. Comparisons between the five faculties also did not show any signs of the gap not being a problem, despite there being varying levels of its extremity. Further research needs to be planned which will test a wider range of variables to find the route of the problem however these may be more difficult to collect mass data as they have ambiguous interpretations such as personal target grades, hours spent on revision or ambition based on personal job prospects.
New data was processed that showed the gap remained in courses where the top grade was a pass with honours. The final days of the placement are being spent preparing a presentation of my findings which will then be shown to staff members from various departments around the University and hopefully result in some actions being taken to address the issue.
|Rosie @ South Yorkshire Police||
In my first week of interning with South Yorkshire Police I felt a mixture of emotions, including nervousness but also excitement to begin an experience in a role that I had never worked in before, or even closely encountered in other jobs previously.
I began the week being shown around South Yorkshire Police HQ, where I would be spending the next six weeks analysing and visualising data, using RStudio to provide an alternative insight to the data collection. My line manager showed me where each department was placed and briefly described to me what their role is within the organisation. I was then briefed on all health and safety requirements and we discussed the objectives of the internship in the short term and long term for both myself, and the organisation. My first couple of days consisted of me having short meetings with most of the individuals working in the Business Change and Innovation department where I was working, to get to know them as individuals as well as understand what their role is within the organisation. This was really interesting as someone new coming into the organisation, particularly learning about how important every role is to changing the business to be more efficient, as well as being shown what types of software is used, and what types of data are being handled.
I spent the next week developing a presentation that I would present to both the team I was working for, and others who were interested. RStudio is a software that is new to South Yorkshire Police, and with the skills I have developed from university handling data in RStudio, they were really interested to know both what I can do in the software and also what the potential possibilities are in using RStudio alongside or in replacement of other alternative software. Within the presentation I used a PowerPoint slide presentation and demoed RStudio to show examples of how to use code, as well as showing what data visuals are able to be produced, and answered any questions the audience had. Following on from the presentation, once the team knew the range of skills I had they were able to give me different tasks to complete, including visualising complex data, regression models and other calculations.
Overall, in 3 words my first 2 weeks were insightful, exciting and engaging, I was able to practice a range of skills including analysis, using RStudio and my presentation skills – I look forward to continuing my internship over the next few weeks!
Entering the next two weeks of my 6-week placement at South Yorkshire Police marked the midpoint of the internship. In this period, I have predominantly spent time performing pieces of analysis in RStudio that my colleagues asked me to complete, including analysis that have helped as part of projects they are working on.
Over this time, I have also been required to use Excel, a program I was already slightly familiar with but the extent of my usage of the software before the internship was not much more than using it to download datasets online and converting them to CSV files. The past 2 weeks at South Yorkshire Police has required me to develop my knowledge of Excel, including performing calculations and using filters to observe values in the datasets, which are particularly large compared to any data I have previously handled. Using large and current datasets has given me a huge insight into the power of data analysis, and I know these skills will be useful for future work at university and beyond, as Excel and RStudio are two programs that work well together to perform analysis.
The latter half of these two weeks I have spent preparing for a second presentation, that this time, will be based on the work I have been completing for the organisation, including analysis and visuals that I will present at some point in the final two weeks. As this presentation is for senior members of staff, who aren’t necessarily familiar with the datasets themselves, or the statistical jargon used, it was important in the planning of the presentation to understand ‘what does this mean for SYP?’ when analysing the data and drawing conclusions, and not just stating the statistics as they’re provided in R. This means thinking about future trends and requirements that SYP can prepare for, and providing new information that hasn’t already been uncovered.
The photo above is an image of my workstation, where I have been working and will continue to work for the upcoming weeks, where I have been performing analysis, and preparing for presentations. Unfortunately, I am unable to show any of my work, as this is confidential information – but I can assure you it is interesting!
As my final 2 weeks at South Yorkshire Police have come to a close, I reflect on all of the experiences I have had and how much I have learnt in this truly interesting and insightful experience.
Not only have I practiced and developed my data analysis skills hugely every day for the past 6 weeks, I have also learnt what it’s like to work for such a large organisation and learnt how integral the organisation is to South Yorkshire, and how every individual’s job plays an important role in the functioning of the organisation. As well as this I have got to know so many interesting and friendly people, who welcomed me into the office and have supported me throughout my entire experience here, which I am extremely grateful for.
In the last 2 weeks of my internship, I have showcased my second presentation regarding the pieces of analysis I have performed over the past few weeks at SYP. This presentation was for multiple members of staff within my department, including the Director of the department, as well as one of the Assistant Chief Constables. It was a real honour to know that such senior members of staff were interested in the work I was doing. Upon performing the presentation, I could really see how my presentation and analysis skills had developed from previously, which was great to notice.
I also got the chance to visit Atlas Court, and listen to some live 999 and 101 calls, as well as observe someone working in dispatch. This was truly one of the most eye opening experiences of my life, hearing real people’s voices and understanding where all of the data I was using came from and gave the data so much context and meaning.
Overall I can say that working for South Yorkshire Police has been a tremendous experience for me, in terms of developing my understanding of the importance Police Force and developing my own personal skills that will aid me at University and beyond. I can’t thank the SMI and SYP enough for allowing me to be able to have this opportunity.
|Niall @ YouGov||
During my work placement at YouGov I did many interesting things that relate directly to the skills I have developed on my degree. The first week mainly involved getting used to all the various programmes that YouGov uses. This varied from Microsoft Excel to SPSS to the in house software that they have for producing questionnaires called Gryphon. There was also a programme used for coding open ended questions called Ascribe. All these programmes were relatively new to me when I first joined but after 6 weeks of using them daily I became much more confident using them all.
Over the course of the next couple of weeks I was entrusted to do different jobs within the YouGov Political and Social team. These jobs were for different clients who used YouGov’s services and included Channel 5, Lord Ashcroft, Centre for Social Justice and The Times newspaper – with each client having a variety of tasks I had to complete.
One of these tasks was coding using the programme Ascribe. This involved coding responses for a question Lord Ashcroft ran called ‘Why has your opinion of the Conservative Party become less favourable?’ There were nearly 2000 answers which needed sorting into different categories ready for use.
One of the other clients on worked on was Channel 5. They wanted questions about Grenfell tower and whether people viewed the Government’s response to the disaster as good enough. For this client’s questions had to be checked to see if they were good enough and to be put onto YouGov’s Daily Poll. After they had been run through the Daily Poll and the results given back to Channel 5 used the data in a press release, that they sent to for YouGov to check over. I did this by making sure all the statistics were the same ones I gave them and they weren’t presented in a misleading way.
I used SPSS to analyse all the data and weight all the responses by five different measures. This programme was used for the Daily Polling so that each respondent could be weighted properly. These will include all the client questions that have been asked for and arranged, as well as some internal questions that various members of the PR team or the political team wanted to run.
My SMI placement at YouGov was a very interesting experience and I would recommend it to anyone interested in Politics or data or both.
|Olivia @ WPREU||
During my studies, both through the SMI and the Department of Poltitics, I have undertaken various data analysis research projects. I have found working with both quantitative and qualitative data extremely interesting and I hope to further my experience working with data next year with my Dissertation in Political Analysis. This summer I was able to work on a research project for WPREU at the University of Sheffield, analysing student attainment data and furthering the work done previously in the department on the Ethnicity Attainment Gap within the University.
One aspect of the placement that I found particularly interesting was that the project was building on previous research. After reading the other reports, I could then decide which areas of research I wanted to focus on and analyse in more detail. Having the freedom to choose the focus of my research was initially challenging, as the dataset was large and difficult to get to grips with. However, it made the placement more interesting, as the other SMI placement student and I could focus on what interested us the most.
The first few weeks of the six-week placement were challenging for a few reasons. Not only was it by far the largest dataset I had ever worked with, with 16077 cases and dozens of variables, but I had only used the software (IBM SPSS) once before. Learning to use SPSS again was difficult, but we received plenty of help on how to use the software and also how to write syntax for it.
Overall, the WPREU placement was challenging but very interesting. I have developed my SPSS skills and learnt how to use syntax. It was eye-opening to work on a real data analysis project and see how important research is for making changes to the University.
You can read more about Olivia's research at WPREU.
|Rhiannon @ WPREU||
Walking into the placement with WPREU, the ethnicity attainment gap in UK universities was an issue that I really knew nothing about. I had heard bits here and there about some people arguing that it existed, others arguing that it was simply a matter of socioeconomic and other traits in the students’ backgrounds only making it look like an ethnicity based issue; a matter of misinterpreted correlation. In all honesty, it really wasn’t a subject that I had really thought about all that much before - after learning more about it however, it became something which I am interested in researching in the future of my academic career.
Some of the most commonly heard arguments against the presence of an ethnicity based attainment gap are that Black and minority ethnic (BME) students simply come in with lower entry grades or differing entry qualification types and their lower attainment rates of a 2:1 / 1:1 when leaving university are simply a reflection of that, or that they largely come from lower socioeconomic backgrounds and are therefore being affected by their background of relative deprivation; nothing to do with their ethnicity as an isolated factor. Other variables used to explain away the gap include age, gender and subjects studied.
As important as this previous work on the project was, there were still arguments from ethnicity attainment gap deniers left over which had not been addressed; as such, myself and another student working on the project chose to look at gender, mature status, Polar3 (a measure of higher education participation rates in the students’ social background) and IMD ranks (a measure of socioeconomic deprivation), with myself investigating the latter two.
Some of the findings of the project have also reinforced the notion that the way in which the ethnicity attainment gap is studied needs to be addressed within itself; namely, the fact that students of different BME subcategories attained a 2:1 / 1:1 at differing rates from eachother and as such cannot be looked at as one homogenous group. This finding is as of yet unexplained although I do hope that it will be factored into more effective research designs, including the upcoming regression analysis work, for BME students’ issues to be addressed faster and more effectively.
You can read more about Rhiannon's research at WPREU.
|Morris @ Linney||
My work placement at Linney has been a very positive experience. I was welcomed into a driven and immensely friendly ‘Insight’ team as if I was a fellow colleague. They allowed me the first week or so to settle in, meet and greet, and learn a few new skills to help me over the remainder of the internship.
Things I’ve learned about Linney:
Most of the business activity I was exposed to requires a personal relationship between an account manager and a client (without these relationships, Linney would presumably be out of work).
FIRST MAJOR TASK
McDonald’s are the parent company of McCafe, a relatively new coffee chain, and Linney are a close client of McDonald’s. I was given a sample of over 4000 participants who, amongst other questions, were asked what they thought of various coffee brands (McCafe included). I was assigned with the task of translating the data into something meaningful for McCafe. I wrote a report to explain any important discoveries.
One particular finding that I believed was worth reporting on was part of a linear regression model I created in Rstudio. The above estimate for the ‘Age’ coefficient suggests that the older a participant was, the more negative they were about McCafe.
WHAT I’VE LEARNT
|Alex @ Dubit||
Working at Dubit was the first time I had ever worked on a longitudinal survey. This opportunity rarely pops up for data analysts due to limited funding and time. However, through the SMI PlaceME scheme, I was able to do so. I worked within the research department of Dubit, mainly focusing on Dubit Trends, which is their longitudinal survey which collects data biannually. This focused on how children consume media, potential implications, worries for parents, and how new technology is changing how children interact with media. They collected data from across the globe, catering to the needs of their clients. I mostly helped to visualise their exhaustive data, which was used to help companies understand their markets and ultimately focus their products and services into a more fine-tuned version. It was also used to provide a pilot run for new products to gauge interest and decide whether to further invest.
During my time at Dubit, I also worked on a deep dive project. Within the survey are many areas which are questioned. I focused on one particular set of questions and used their many waves of data through multiple countries in order to find correlations and disparities. I found how different countries have different rates of adoption of new technology, and how between countries, demographics can alter the reception of media massively. For example, when it comes to adopting new technology, central Europe cares very little about technology (the early majority) compared to the UK (early adopters) and even more so the Americans (innovators). This project was used to provide supplementary quantitative analysis to other projects and help reinforce Dubit’s findings.
My experience with Dubit, a private company, was very different compared to university research. Academic research has mostly been one where I took the lead in all aspects, with direction from supervisors. Private research heavily relies on teamwork to meet tight deadlines, where coordination is the key to success. This is the first time I have ever been treated this way in a work place. Adam, my supervisor, was present during the beginning in order to guide me and answer questions, but also placed trust in me once I had got to grips with the work required of me. It was the first time I had been held accountable in a work office environment, and contributed to the output of a company. This was a perfect learning curve to ready me for a world beyond university.
Information for employers
We are open to collaborations with academic and external to the University partners for the PlaceME@SMI programme. If your are a University research project, community organisation or a business and you have an idea for a collaborative research project (between at least one person in your organisation and our student) and it would involve generation and analysis of quantitative data - you are welcome to join the programme. Please email Dr. Aneta Piekut to express your interest.