The module is only available to students taking the Q-Step Major degree (BSc Statistical Social Research) or any of the Q-Step Minor degrees (any programme that includes 'with Quantitative Research'
OverviewThis module will involve students undertaking quantitative research in a placement setting, while simultaneously reflecting on the process of undertaking real-life quantitative research (through a log), culminating in an assessed reflection on their placement. Aside from the support of the Q-Step Placements Officer and an academic placements advisor, students would also receive lectures covering:
- Turning an organisations ideas into a viable research project (noting that the Q-Step team will already have worked with placement organisations to do this);
- Good practice in undertaking quantitative research projects (e.g. data security, data management, replicability);
- Ethics in applied quantitative research (certainty/uncertainty, power, and 'usefulness');
- Reflecting on research practice (linked to the assessments below).
Matching students to placements
While the Kent Q-Step Centre will arrange a number of potential placements for students on this module, it is the student's responsibility to negotiate a suitable placement – placements depend on finding a successful match between a student's abilities/interests and the placement hosts' needs, and this cannot be guaranteed in advance. However, the Q-Step Centre's Placements Officer (in collaboration with the Q-Step Academic Placement Lead and (where appropriate) the Schools' Placements Officer) will provide considerable support for students in finding a placement, including:
o Providing a range of possible placement opportunities for students that have been negotiated with employers across the private, public and voluntary sectors;
o Helping match students to these placement opportunities;
o Helping students find their own placement opportunity, if they cannot find a successful match in the existing placement opportunities.
The Placements Officer will also provide the further support.
This module appears in:
200 hour placement and 10 hours contact time.
Method of assessment
100% coursework (portfolio 50%, presentation 25% and an essay 25%)
Cook, T., & Campbell, D. (1979) Quasi-experimentation: Design and analysis issues for field settings. Rand McNally College Publications
Robson, C and McCartan, K (2016), Real-World Research, 4th edition. Wiley.
Scott Long, J (2009), The Workflow of Data Analysis Using Stata. Stata Press.
Stevens, A (2011), 'Telling Policy Stories: An Ethnographic Study of the Use of Evidence in Policy-making in the UK'. Journal of Social Policy, 40:237-255. DOI: 10.1017/S0047279410000723
Critically understand the difference between quantitative research in theory and quantitative research in practice.
Critically understand the pressures on quantitative analysts in real-life-settings, such as producing quick results, data protection, pressures for certainty and/or simplicity,
or to produce 'useful' results.
Conduct advanced quantitative analyses in an applied setting;
Report (verbally and in writing) on quantitative analyses, to both technical and non-technical audiences.
Demonstrate an ability to reflect on their own position as a quantitative analyst in an applied setting.