Scientific Methodologies
| Module title | Scientific Methodologies |
|---|---|
| Module code | ERPM002 |
| Academic year | 2019/0 |
| Credits | 30 |
| Module staff | Nasser Mansour (Convenor) |
| Duration: Term | 1 | 2 | 3 |
|---|---|---|---|
| Duration: Weeks | 10 |
| Number students taking module (anticipated) | 30 |
|---|
Module description
Through this module you will develop a critical understanding of the hypothetico-deductive approach to data collection and analysis. In the formative work you will be required to work collaboratively to develop 3 different research designs. These formative activities will enable you to design two measurement instruments and to produce a poster on a small-scale research enquiry. The one summative assignment will be a portfolio that consists of a 5,000 word assignment and two tasks equivalent to 2,500 words.
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. In this module it is recognized that scientific methodology includes elements that are commonly regarded as characteristics of work in the interpretive paradigm (e.g. creative interrogation and interpretation of data).
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
- Experimental, quasi-experimental, and survey designs and threats to their validity; different sampling strategies, consequences of sampling – limitations, errors, biases. Theory of measurement, 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, repertory grids, observation schedules, 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, 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 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 |
|---|---|---|---|
| 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, 6, 9 -17 | Written and verbal |
| Poster on a small-scale research enquiry - peer and tutor review, oral defence | Equivalent to 1,000 words | 1-17 | 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 |
|---|---|---|---|---|
| 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 |
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 |
|---|---|---|---|
| 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 learning resources - Basic reading
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.
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. (2000) Discovering Statistics using SPSS for Windows. 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.
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 | 31/08/2012 |
