Studying at York
Quantitative Research Skills 2 - EDU00071I
- Department: Education
- Credit value: 20 credits
- Credit level: I
- Academic year of delivery: 2023-24
- See module specification for other years: 2024-25
Module summary
This module will introduce students to advanced research methods, building on learning from level 4 and preparing students for the final year dissertation. Students will design, participate in, and analyse data from research projects utilising more 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 2 2023-24 |
Module aims
This module will introduce students to advanced research methods, building on learning from level 4 and preparing students for the final year dissertation. Students will design, participate in, and analyse data from research projects utilising more advanced research 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:
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Describe the characteristics of scientifically rigorous and ethical research
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Evaluate the design of commonly-used research instruments and procedures in psychology in education, including questionnaires and experiments
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Discuss a range of research designs, strategies and quantitative techniques (e.g., univariate and introductory multivariate statistics)
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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:
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Manage a range of data and critically evaluate the reliability and validity of these in informing and supporting academic argumentation.
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Understand how to prepare data for analysis.
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Analyse datasets using appropriate statistical tests.
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Report the results of quantitative data analysis in an appropriate format.
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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:
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Principles of good measurement (e.g., Cronbach alpha, reliability, types of measurement).
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Tests of differences between multiple groups (one-way and two-way ANOVA).
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Simple and multiple linear regression.
Indicative assessment
| Task | % of module mark |
|---|---|
| Online Exam -less than 24hrs (Centrally scheduled) | 100 |
Special assessment rules
None
Indicative reassessment
| Task | % of module mark |
|---|---|
| Online Exam -less than 24hrs (Centrally scheduled) | 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.