Undergraduate Programme and Module Handbook 2008-2009 (archived)
Module PSYS3111: ADVANCED RESEARCH METHODS FOR APPLIED PSYCHOLOGY
Department: Psychology (Applied Psychology) [Queen's Campus, Stockton]
PSYS3111: ADVANCED RESEARCH METHODS FOR APPLIED PSYCHOLOGY
| Type | Tied | Level | 3 | Credits | 20 | Availability | Available in 2008/09 | Module Cap | None. | Location | Queen's Campus Stockton |
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| Tied to | C810 |
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Prerequisites
- Modules to the value of 100 credits from Level 2 Applied Psychology (C810) INCLUDING Research Design and Data Analysis (PSYS2091)
Corequisites
- None
Excluded Combination of Modules
- None
Aims
- This module has three complementary aims:
- first, students will learn how to synthesize research results using meta-analysis
- second, students will be introduced to additional forms of multivariate data analysis
- third, they will learn to combine their various research skills
Content
- Introduction to advanced research methods
- Major types of quantitative method and their advantages and disadvantages
- Quantitative; meta-analysis, factor analysis and confirmatory factor analysis
- Two other methods from: Cluster analysis, structural equation modelling, multi-dimensional scaling, network analysis or logistic regression
- The module will also cover related conceptual and historical issues in psychology
Learning Outcomes
Subject-specific Knowledge:
- Upon satisfactory completion of this module students should be aware of some of the various advanced methods that can be used in psychological research and have an understanding of the problems associated with them
- The ability to understand and conduct a simple meta analysis
Subject-specific Skills:
- Students passing this module should be able to:
- Understand the advantages and disadvantages of quantitative research
- Describe the main methods of quantitative research
- Possess competent data analysis skills with the base programmes of SPSS
- Possess competent ompetent data analysis skills with at least one of AMOS, LISREL or EQS
Key Skills:
- Students passing this module should be able to demonstrate:
- Good IT skills in data handling, represention and analysis
Modes of Teaching, Learning and Assessment and how these contribute to the learning outcomes of the module
- Knowledge and understanding of advanced research methods and statistics, and the ability to select appropriuate methods in addressing a specific question are developed through the weekly lectures. Skills in applying this knowledge using advance computing packages is acquired during the weekly computing practicals
- This knowledge will be assessed in the summative assessments in which students must demonstrate practical skills in reporting and conducting a meta-analytic study and a critical evaluation of another piece of research
- These abilities are also assessed via the formative report for which feedback is provided
- Good IT and data handling skills are required for the formative and summative work in this module. Feedback is provided regarding the adequacy of these skills where necessary
Teaching Methods and Learning Hours
| Activity | Number | Frequency | Duration | Total/Hours | |
|---|---|---|---|---|---|
| Lectures | 22 | 1 per week | 1 hour | 22 | |
| Practicals | 22 | 1 per week | 1 hour | 22 | ■ |
| Preparation and Reading | 156 | ||||
| Total | 200 |
Summative Assessment
| Component: Reports | Component Weighting: 100% | ||
|---|---|---|---|
| Element | Length / duration | Element Weighting | Resit Opportunity |
| 3000 word meta-analysis assignment | 50% | ||
| 3000 word report of other research method. | 50% | ||
Formative Assessment:
One quantitative data analysis exercise, from network analysis or structural equation modelling.
■ Attendance at all activities marked with this symbol will be monitored. Students who fail to attend these activities, or to complete the summative or formative assessment specified above, will be subject to the procedures defined in the University's General Regulation V, and may be required to leave the University