- Department: Education
- Credit value: 20 credits
- Credit level: C
- Academic year of delivery: 2023-24
- See module specification for other years: 2024-25
The aim of this module is to provide the foundations for students’ study of more complex designs later in the degree. Students will be introduced to quantitative research methods skills commensurate with the study of psychology in education. This will include an introduction to quantitative research methods alongside a range of descriptive and inferential statistics. The module plays an important part in developing students' critical and analytical skills that can be applied to learning in other modules.
Occurrence | Teaching period |
---|---|
A | Semester 2 2023-24 |
The aim of this module is to provide the foundations for students’ study of more complex designs later in the degree. Students will be introduced to quantitative research methods skills commensurate with the study of psychology in education. This will include an introduction to quantitative research methods alongside a range of descriptive and inferential statistics. The module plays an important part in developing students' critical and analytical skills that can be applied to learning in other modules.
By the end of this module students will be able to:
Describe a range of quantitative research designs appropriate for the study of psychology in education.
Describe and use a range of descriptive statistical techniques, including calculating means and standard deviations using appropriate statistical analysis software.
Explain the principles of Null-Hypothesis significance testing and the process of choosing an appropriate statistical test.
Describe and use a range of bivariate statistical tests (e.g., chi-square and t-tests) using appropriate statistical analysis software.
Academic and graduate skills
Students will have learned how to:
Design and implement common instruments and methods for data collection in psychology of education through interactive workshops, practical sessions and computer-based lab sessions.
Analyse datasets using appropriate statistical tests.
Report the results of quantitative data analysis in an appropriate format.
Use the Virtual Learning Environment (VLE) website, appropriate statistical software, and the Internet effectively.
The following is indicative of the different topics that will be covered:
Introduction to quantitative methods.
Descriptive statistics (measures of central tendency and measures of dispersion).
Introduction to Null-Hypothesis significance testing and central limit theorem
Confidence intervals, the sampling error.
Chi-square tests.
Simple tests of differences: t-tests and their non-parametric equivalents.
Correlations: Pearson’s and Spearman’s.
Task | % of module mark |
---|---|
Essay/coursework | 50 |
Online Exam -less than 24hrs (Centrally scheduled) | 50 |
None
Task | % of module mark |
---|---|
Essay/coursework | 50 |
Online Exam -less than 24hrs (Centrally scheduled) | 50 |
Individual written feedback reports, with follow-up tutor meeting, if necessary. The feedback is returned to students in line with university policy. Please check the Guide to Assessment, Standards, Marking and Feedback for more information.
Coolican, H. (2017). Research methods and statistics in psychology. Psychology Press.
Field, A. (2018). Discovering statistics using IBM SPSS statistics (5th Ed.). Sage.
Harrison, V., Kemp, R., Brace, N., & Snelgar, R. (2020). SPSS for Psychologists. Bloomsbury Publishing.
Pallant, J. (2020). SPSS survival manual: A step by step guide to data analysis using IBM SPSS. Routledge.