Our department is one of the two strongest UK centres for quantitative analysis of educational data (RAE 2008).
Two of the externally funded Research Centres in the department (Centres for Educational Assessment and Skills Knowledge and Organisational Performance), as well as five of the research groups, primarily employ quantitative methods, offering fertile ground for the continuing development of the department’s profile in this broad area of methodology.
The large body of researchers actively using and applying quantitative methods are members of research groups which reflect their varying areas of substantive research interest.
The Quantitative Methods (QM) Hub is not a research group, it is a cross-cutting grouping intended to bring together colleagues with an interest/experience in using QM or in developing such expertise. The QM hub intends to:
- Co-ordinate the provision of high quality Department staff in their use and application of QM in their own research;
- Advise colleagues on, and where appropriate support, large grant bids by the Department;
- Liaise with other departments within the Social Sciences Division and with the Doctoral Training in the Social Sciences (DTCSS) Methods Hub.
The QM Hub is a forum to support all staff in developing their QM expertise, whatever their initial level of engagement or facility.
A particular area of focus has been to increase awareness among staff of the potential of Secondary Data Analysis (SDA) as a research resource. SDA offers the potential for high quality research and publications without the need for large research grants or research teams necessary for collecting primary data.
A core reference if you are considering SDA is:
- Smith, E. (2008). Using secondary data in educational and social research. Maidenhead: OU Press. Appendix 1 of the book has numerous links and summaries of sources of secondary data and it can be accessed by staff with authorised access.
Core training for MSc and DPhil students
The QM hub provides high quality QM training for MSc and DPhil students within the department. QM are introduced through input to the two Foundations of Educational Research modules (FER1/FER2) and culminate in two full modules Introduction to Quantitative Methods and Intermediate Quantitative methods. These modules are convened by Professor Lars-Erik Malmberg drawing on QM expertise across the department. The introduction course covers basic statistical literacy, including theoretical ideas put to practice through application of parametric and non-parametric tests to real-world educational data. The intermediate course introduces multivariate statistics ranging from analysis of variance for experimental designs to regression techniques for survey data. Ideas and techniques are introduced in lectures, followed by workshops which focus on understanding of concepts, hands-on analysis using SPSS and Excel, interpretation and documentation of findings. Master classes and workshops on advanced topics (confirmatory factor analysis, multilevel modelling) are available for all students and staff and are arranged in Trinity Term.
Staff in the department contribute to Advanced Methods training co-ordinated through the Doctoral Training in the Social Sciences (DTSS) Methods hub. Professor Lars Malmberg provides a course on Structural Equation Modelling. Details of the DTSS methods hub can be found here.
Many MSc and DPhil students actively engage with QM in their dissertations, supported by their supervisors. We do offer drop-in advice surgeries for students, although resources are limited and referral should be made in conjunction with the dissertation supervisor.
Weblearn is the repository for our course and module content and support. However there are public access resources that may also be of value, such as the ReStore website: www.restore.ac.uk/srme
What is the SRME website?
- The website was developed through an ESRC National Centre for Research Methods (NCRM) grant awarded to Professor Strand to support researchers in learning to use a class of statistical procedures called regression analyses. The web resource is designed for users to work through at their own pace.
Who is it for?
- The resource site is not aimed at statisticians or those with high levels of experience in quantitative data analysis. This site is primarily designed for researchers in the social sciences who may have limited experience in quantitative research methods but wish to expand their expertise without drowning in a sea of abstract examples and formulae.
What is distinctive about the resource?
- It roots regression analysis firmly within the context of ‘real’ research using throughout examples drawn from the Longitudinal Study of Young People in England (LSYPE). Though the examples focus on educational data, we anticipate the site will be useful to social scientists from a variety of backgrounds.
- It implements all analyses using the Statistical Package for the Social Sciences (SPSS), by far the most popular statistical package used by social scientists today. Throughout it shows you step by step how you can put into practice what you learn about regression analyses.
- Finally it employs a range of multi-media tools such as video demonstrations, interactive quizzes with feedback, an online glossary and plenty of worked examples and exercises to create a flexible learning tool.
The QM Hub has had an active and sustained seminar programme for more than five years, hosting over 20 presentations each academic year.
The programme builds on a tradition of addressing substantive educational research questions using quantitative methods, as well as presenting a particular quantitative method which can serve as inspiration for educational research (and more widely for research in the social sciences). Presentations are given by both academics and higher degree students within friendly lunch-time seminars that are open to all. The programme is convened by Professors Steve Strand and Lars-Erik Malmberg, and Dr Ariel Lindorff.
Presentations take place in the department on Mondays in Seminar Room A from 12.45pm-2pm. If you do not have access to the department, please call at Reception when you arrive and you will be directed to the room.
All upcoming our upcoming events are listed on the Events page.
9 October 2023
Dr James Hall, University of Southampton
16 October 2023
Dr Olga Cara, University College London
23 October 2023
Dr Joonghyun Kwak, University of Oxford
30 October 2023
Benjamin Hart, University of Oxford
6 November 2023
Jason Bradbury, Ofsted and Nadir Zanini, Ofqual
13 November 2023
Johannes Schulz, University of Oxford