Scientific Methodologies
| Module title | Scientific Methodologies |
|---|---|
| Module code | ERPM002 |
| Academic year | 2023/4 |
| Credits | 30 |
| Module staff |
| Duration: Term | 1 | 2 | 3 |
|---|---|---|---|
| Duration: Weeks | 10 |
| Number students taking module (anticipated) | 30 |
|---|
Module description
The module is designed to enable those students who decide to use a scientific methodology to do so with confidence, and to enable all students (whatever the approach they choose to take in their own research) to read, in an informed and critical way, papers that use a scientific methodology. Through this module you will develop a critical understanding of the hypothetico-deductive approach to data collection and analysis.
Module aims - intentions of the module
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.
Intended Learning Outcomes (ILOs)
ILO: Module-specific skills
On successfully completing the module you will be able to...
- 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;
ILO: Discipline-specific skills
On successfully completing the module you will be able to...
- 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;
ILO: Personal and key skills
On successfully completing the module you will be able to...
- 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.
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, and multiple. 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 activities and teaching methods (given in hours of study time)
| Scheduled Learning and Teaching Activities | Guided independent study | Placement / study abroad |
|---|---|---|
| 30 | 270 | 0 |
Details of learning activities and teaching methods
| 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 |
Formative assessment
| Form of assessment | Size of the assessment (eg length / duration) | ILOs assessed | Feedback method |
|---|---|---|---|
| A proposal for a small-scale research enquiry including the design of two measurement instruments, a strategy to investigate reliability and validity and an outline sampling strategy for empirical study. | 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 (% of credit)
| Coursework | Written exams | Practical exams |
|---|---|---|
| 100 | 0 | 0 |
Details of summative assessment
| Form of assessment | % of credit | Size of the assessment (eg length / duration) | ILOs assessed | Feedback method |
|---|---|---|---|---|
| Written assignment | 100 | a 5,000 word assignment. | 1-17 | Written |
Details of re-assessment (where required by referral or deferral)
| Original form of assessment | Form of re-assessment | ILOs re-assessed | Timescale for re-assessment |
|---|---|---|---|
| Written assignment | As above | 1-17 | 6 weeks from notification of failure or re-entry onto programme |
Indicative learning resources - Basic reading
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.
Indicative learning resources - Other resources
http://vle.exeter.ac.uk/course/view.php?id=3161
http://vle.exeter.ac.uk/course/view.php?id=3162
| Credit value | 30 |
|---|---|
| Module ECTS | 15 |
| Module pre-requisites | None |
| Module co-requisites | None |
| NQF level (module) | 7 |
| Available as distance learning? | Yes |
| Origin date | 31/08/2011 |
| Last revision date | 07/06/2022 |
