Module ERPM002 for 2021/2
- Overview
- Aims and Learning Outcomes
- Module Content
- Indicative Reading List
- Assessment
Postgraduate Module Descriptor
ERPM002: Scientific Methodologies
This module descriptor refers to the 2021/2 academic year.
Module Aims
This module aims to give participants knowledge of survey, experimental, and quasi-experimental designs, of the nature, collection and analysis of quantitative data in educational research, and of the interrelations of research design and statistical methods. The construction of measuring instruments (e.g. tests, attitude scales, repertory grids, structured observation schedules, etc) and descriptive and inferential statistical analyses are included, together with the use of statistical software packages.
On successfully completing the programme you will be able to: | |
---|---|
Module-Specific Skills | 1. demonstrate knowledge and understanding of survey and experimental design, including different kinds of sampling strategies; 2. analyse existing archive data sets as well as constructing new data sets; 3. design and know how and when to use questionnaires and other structured approaches to questioning; 4. use various methods of data analysis for theory building including hypothesis testing; 5. demonstrate knowledge and understanding of the underlying principles of the methods used to collect and analyse data; 6. draw up codebooks and manage and construct various datasets; 7. exercise critical evaluation and judgment in all aspects of their work in this module including developing an understanding of political arithmetic; 8. demonstrate critical awareness of ethical issues in quantitative research strategies; |
Discipline-Specific Skills | 9. demonstrate understanding of theoretical principles through the application of the above techniques to complex educational research problems; 10. read and understand research papers and reports that have used quantitative data analysis techniques; 11. tell when statistical conclusions may be suspect because of the inappropriate use of a particular form of analysis, including developing an ability to evaluate their own quantitative research critically in order to improve it; |
Personal and Key Skills | 12. demonstrate skills in self-management - in particular the management of time, tasks and evaluation of own learning; 13. demonstrate personal judgement - particularly in respect of ethically sensitive issues; 14. demonstrate the ability to work independently and collaboratively; 15. demonstrate the ability to communicate and present ideas when writing and speaking and to listen effectively and persuade rationally; 16. demonstrate the ability to problem solve - to think logically, laterally, strategically, analyzing and evaluating; and 17. demonstrate the ability to handle data. |
Module Content
Syllabus Plan
Whilst the module’s precise content may vary from year to year, it is envisaged that the syllabus will cover some or all of the following topics:
- Experimental, quasi-experimental, and survey designs and threats to their validity; different sampling strategies, consequences of sampling – limitations, errors, biases, scales of measurement, operationalisation, the codebook.
- Measuring instruments, design, types of scale, questionnaires and other structured approaches to questioning that can be numerically coded and analysed (tests, attitude scales, semantic differentials, , etc); different methods of ensuring measurements are reliable, instrument validation, threats to internal and external validity, criteria for assessing validity, the electronic collection of quantitative data
- Descriptive statistics and exploratory data analysis; concept of a statistic, distributions of statistics, probability and non-probability sampling, statistical significance, analysis of variance; regression and its relationship to multi-level modelling; factor analysis; OLS regression, multiple and logistic regression. Use of software packages (e.g. SPSS). Through evaluation of published research and practical application appreciate the importance of political power and bias, limitations of knowledge claims and warrants from quantitative research and the ethical issues involved in quantitative fieldwork.
Learning and Teaching
This table provides an overview of how your hours of study for this module are allocated:
Scheduled Learning and Teaching Activities | Guided independent study | Placement / study abroad |
---|---|---|
30 | 270 | 0 |
...and this table provides a more detailed breakdown of the hours allocated to various study activities:
Category | Hours of study time | Description |
---|---|---|
Scheduled Learning and Teaching Activities | 30 | 10x3 hour teaching sessions (lectures, workshops and seminars), including on campus teaching and recorded sessions |
Guided Independent Study | 70 | Collaborative group work |
Guided Independent Study | 100 | Reading and assignment preparation |
Guided Independent Study | 100 | Writing summative assignment |
Online Resources
This module has online resources available via ELE (the Exeter Learning Environment).
Other Learning Resources
http://vle.exeter.ac.uk/course/view.php?id=3161
http://vle.exeter.ac.uk/course/view.php?id=3162
How this Module is Assessed
In the tables below, you will see reference to 'ILO's. An ILO is an Intended Learning Outcome - see Aims and Learning Outcomes for details of the ILOs for this module.
Formative Assessment
A formative assessment is designed to give you feedback on your understanding of the module content but it will not count towards your mark for the module.
Form of assessment | Size of the assessment (eg length / duration) | ILOs assessed | Feedback method |
---|---|---|---|
Design two measurement instruments - investigate score reliability and validity, outline sampling strategy for empirical study, draw up codebook and plan for analysis. | Equivalent to 1,500 words | 1, 2, 3, 4, 11, 12, 13, 14 | Written and verbal |
A proposal for a small-scale research enquiry and complete the ethical form. | Equivalent to 1,000 words | 1-17 | Written and verbal |
Summative Assessment
A summative assessment counts towards your mark for the module. The table below tells you what percentage of your mark will come from which type of assessment.
Coursework | Written exams | Practical exams |
---|---|---|
100 | 0 | 0 |
...and this table provides further details on the summative assessments for this module.
Form of assessment | % of credit | Size of the assessment (eg length / duration) | ILOs assessed | Feedback method |
---|---|---|---|---|
Portfolio, including a written assignment | 100 | 7,500 words in total, including a 5,000 word assignment and two other tasks equivalent to 2,500 words | 1-13, 15-17 | Written |
Re-assessment
Re-assessment takes place when the summative assessment has not been completed by the original deadline, and the student has been allowed to refer or defer it to a later date (this only happens following certain criteria and is always subject to exam board approval). For obvious reasons, re-assessments cannot be the same as the original assessment and so these alternatives are set. In cases where the form of assessment is the same, the content will nevertheless be different.
Original form of assessment | Form of re-assessment | ILOs re-assessed | Timescale for re-assessment |
---|---|---|---|
Portfolio, including a written assignment | Portfolio, including a written assignment (7,500 words. As above) | 1-13, 15-17 | 6 weeks from notification of failure or re-entry onto programme |
Indicative Reading List
This reading list is indicative - i.e. it provides an idea of texts that may be useful to you on this module, but it is not considered to be a confirmed or compulsory reading list for this module.
Bernauer, J., & O'Dwyer, L. (2013). Quantitative research for the qualitative researcher. SAGE, London.
Biddle, S. (1995) Quantitative Data Analysis: An Introduction to Multivariate Statistical Techniques. Exeter University, School of Education.
Black, T.R. (1999) Doing quantitative research in the social sciences - an integrated approach to research design, measurement and statistics. London, Sage.
Bryman, A. & Cramer, D. (1997) Quantitative data analysis with SPSS for Windows: a guide for social scientists.London, Routledge
Buckingham, A. & Saunders, P. (2004) The Survey Methods Workbook. Polity
Burton, D. (2000) Research Training for Social Scientists. Sage.
Cohen, L. and Holliday, M. (1996) Practical statistics for students. London, Paul Chapman.
Cohen, L., Manion, L., & Morrison, K. (2017). Research methods in education. Taylor & Francis, England.
Cook, T. and Campbell, D.T. (1979) Quasi experimentation. Chicago, Rand McNally.
Coolidge, F.L. (2000) Statistics. London, Sage.
Cramer, D. (2003) Advanced Quantitative Analysis. OU Press
Field, A. (2017) Discovering Statistics Using IBM SPSS Statistics London, Sage.
Galloway, A. (1997) Questionnaire Design and Analysis. http://www.tardis.ed.ac.uk/~kate/qmcweb/qcont.htm
Oppenheim, A.N. (2000) Questionnaire Design, Interviewing and Attitude Measurement. London, Continuum.
Pallant, J. (2020). SPSS Survival manual: A step by step guide to data analysis using IBM SPSS. Maidenhead, Berkshire, England.
Pears, I. (1996) Statistical Analysis for Educational and Psychological Researchers. London, Falmer Press.
Preece, P.F.W. (1994) Basic Quantitative Data Analysis. Exeter, University School of Education.
Rust, J. and Golombok, S. (1989) Modern Psychometrics. London, Routledge.
StatPac Inc. (2000) Questionnaires, Survey Design, Marketing Research. http://www.statpac.com/surveys/index.htm#toc
Tukey, J.W. (1977) Exploratory Data Analysis. Reading, MA, Addison-Wesley.