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Research Methods for Psychology in Education - EDU00018I

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  • Department: Education
  • Module co-ordinator: Dr. Lisa Kim
  • Credit value: 30 credits
  • Credit level: I
  • Academic year of delivery: 2022-23
    • See module specification for other years: 2021-22

Module will run

Occurrence Teaching period
A Autumn Term 2022-23 to Summer Term 2022-23

Module aims

To prepare students to read 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; to prepare students to consider the contexts and ethics of research in education and psychology.

To develop knowledge and skills that are essential in a range of careers in education, psychology and in the social sciences more widely, including forming research questions, literature searching and reviewing, and quantitative and qualitative research design.

To familiarise students with a full range of quantitative and qualitative analysis techniques in preparation to carry out independent research on topics in psychology in education.

Module learning outcomes

Subject content

  • Develop increased familiarity with a range of research designs, strategies and techniques, including both quantitative and qualitative methods (e.g., univariate and introductory multivariate statistics; qualitative approaches)
  • Develop increased proficiency at designing and implementing commonly-used research instruments in psychology of education, including questionnaires, interview schedules and observation schedules
  • Gain practical experience of designing and implementing common instruments for data collection in psychology of education through interactive workshops, practical sessions and computer-based lab sessions.
  • Be able to evaluate the appropriateness of techniques for different research topics, critically describe strengths and limitations of different data collection methods, and know how to gather and analyse data using each of these methods.
  • Gain practical experience of a range of analysis techniques for dealing with data through practical sessions and computer-based lab sessions, and increasing familiarity with statistics software
  • Gain a clear understanding of the characteristics of scientifically rigorous and ethical research


Academic and graduate skills

  • Critically evaluate academic arguments as presented in research reports using a range of methods and data analysis techniques
  • Manage a range of sources and critically evaluate the reliability and validity of these in informing and supporting academic argumentation
  • Understand how to prepare data for analysis
  • Ability to carry out quantitative and qualitative analysis of simple datasets
  • Use the VLE and Internet effectively

Assessment

Task Length % of module mark
Online Exam -less than 24hrs (Centrally scheduled)
Open exam : 3-hour online exam		 3 hours 40
Online Exam -less than 24hrs (Centrally scheduled)
Open exam : 4-hour online exam		 4 hours 60

Special assessment rules

None

Additional assessment information

The two exams are both online exams. The reassessment exams are also online exams.

Reassessment

Task Length % of module mark
Online Exam -less than 24hrs (Centrally scheduled)
Open exam : 3-hour online exam		 3 hours 40
Online Exam -less than 24hrs (Centrally scheduled)
Open exam : 4-hour online exam		 4 hours 60

Module feedback

Individual mark summaries with follow-up tutor discussion 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

Aron, A., Aron, E., & Coups, E. (2010). Statistics for the behavioural and social sciences: A brief course (5th ed.). New Jersey: Prentice Hall.

Coolican, H. (2009). Research methods and statistics in psychology. London: Hodder.

Field, A. (2017). Discovering Statistics Using IBM SPSS Statistics (5th ed.). London: SAGE.

Mertens, D. (2010). Research and evaluation in education and psychology: Integrating diversity with quantitative, qualitative, and mixed methods. Thousand Oaks, CA: Sage.

Pallant, J. (2010). SPSS survival manual: A step by step guide to data analysis using the SPSS program (4th ed.). Berkshire, UK: McGraw Hill.


The information on this page is indicative of the module that is currently on offer. The University is constantly exploring 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 by the University. Where appropriate, the University will notify and consult with affected students in advance about any changes that are required in line with the University's policy on the Approval of Modifications to Existing Taught Programmes of Study.