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Quantitative Research Skills 3 - EDU00058H

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  • Department: Education
  • Credit value: 20 credits
  • Credit level: H
  • Academic year of delivery: 2024-25
    • See module specification for other years: 2023-24

Module summary

This module will develop students' understanding of quantitative research methods and analysis, building on learning from level 4 and 5. Students will be introduced to the design of and analysis of data from quantitative research projects utilising advanced methods. The module will also prepare students to read more complex reports of educational and psychological research with critical analysis, understanding and insight, so they are able to assess the strengths and weaknesses of such research.

Module will run

Occurrence Teaching period
A Semester 1 2024-25

Module aims

This module will develop students' understanding of quantitative research methods and analysis, building on learning from level 4 and 5. Students will be introduced to the design of and analysis of data from quantitative research projects utilising advanced methods. The module will also prepare students to read more complex reports of educational and psychological research with critical analysis, understanding and insight, so they are able to assess the strengths and weaknesses of such research.

Module learning outcomes

By the end of this module students will be able to:

  • Describe the characteristics of scientifically rigorous and ethical research

  • Evaluate the design of commonly-used research instruments in psychology in education, including questionnaires, and experiments

  • Discuss a range of research designs, strategies and quantitative techniques (e.g., univariate and introductory multivariate statistics)

  • Use a range of analysis techniques to work with different types of data through and computer-based practical lab sessions.

Academic and graduate skills

Students will have learned how to:

  • Manage a range of data and critically evaluate the reliability and validity of these in informing and supporting academic argumentation.

  • Understand how to prepare data for analysis.

  • 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.

Module content

The following is indicative of the different topics that will be covered:

  • Open Science

  • Factor Analysis (e.g., EFA and CFA).

  • Logistic Regression

  • ANCOVA

  • Introduction to Meta-Analysis

  • Introduction to Structural Equation Modelling and Multi-Level Modelling

Indicative assessment

Task % of module mark
Essay/coursework 100

Special assessment rules

None

Indicative reassessment

Task % of module mark
Essay/coursework 100

Module feedback

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.

Indicative reading

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.


The information on this page is indicative of the module that is currently on offer. The University constantly explores ways to enhance and improve its degree programmes and therefore reserves the right to make variations to the content and method of delivery of modules, and to discontinue modules, if such action is reasonably considered to be necessary. In some instances it may be appropriate for the University to notify and consult with affected students about module changes in accordance with the University's policy on the Approval of Modifications to Existing Taught Programmes of Study.