This is an archived handbook for a previous year. The current undergraduate and postgraduate handbooks can be viewed using the links above.

Undergraduate Handbook 2010-2011 (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	Level	Credits	Availability	Module Cap	Location
Tied	3	20	Available in 2010/2011	None.	Queen's Campus Stockton

Tied To

C810: Applied Psychology

Pre-requisites

100 credits from Level 2 Applied Psychology (C810) INCLUDING Research Design and Data Analysis (PSYS2091)

Corequisites

None

Excluded Combinations

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: Rasch analysis, 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

Detailed knowledge of advanced research methods in psychology including current theory, evidence, and practice
In-depth knowledge of advanced research methods in applied psychology, including meta analysis

Subject-specific Skills

Ability to review critically and consolidate understanding of a coherent body of psychological knowledge and apply it appropriately:
- competent data analysis skills with the base programmes of SPSS
- competent data analysis skills with at least one of AMOS, LISREL, EQS, RUMM or Winsteps

Key Skills

Good written communication skills
Good IT skills in word processing, data manipulation, and data presentation
Ability to work independently in scholarship and research within broad guidelines

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	Attendance Monitored
Lectures	22	1 per week	1 hour	22
Practicals	22	1 per week	1 hour	22	Yes
Preparation and Reading				156
Total				200

Summative Assessment

Component	Component Weighting	Element	Length/Duration	Element Weighting	Resit Opportunity
Reports	100%	3000 word meta-analysis assignment		50%
Reports	100%	3000 word report of other research method.		50%

Formative Assessment

One quantitative data analysis exercise, from network analysis or structural equation modelling

Students who do not attend monitored activities shown under Teaching Methods and Learning Hours, or who fail to complete the summative or formative assessment(s) specified above, may be subject to the Academic Progress procedures defined in the University's General Regulation V, and may be required to leave the University.