Durham University
Programme and Module Handbook

Undergraduate Programme and Module Handbook 2005-2006 (archived)


Department: PSYCHOLOGY (APPLIED PSYCHOLOGY) [Queen's Campus, Stockton]


Type Tied Level 3 Credits 20 Availability Available in 2005/06 Module Cap None. Location Queen's Campus Stockton
Tied to C810


  • Modules to the value of 100 credits from Level 2 Applied Psychology (C810) INCLUDING Research Design and Data Analysis (PSYS2091)


  • None.

Excluded Combination of Modules

  • None.


  • This module has three complementary aims: first, students will learn how to use a computer package to analyse qualitative material.
  • second, students will be introduced to additional forms of multivariate data analysis and third, they will learn to combine their various research skills.


  • Introduction to advanced research methods.
  • Major types of method and their advantages and disadvantages.
  • Qualitative; observation, interviews, data analysis.
  • Computer assisted qualitative analysis
  • 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.

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 qualitative and quantitative research.
  • Describe the main methods of quantitative and qualitative 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.
  • Possess competent competent qualitative data analysis skills with n*DIST or similar program.
Key Skills:
  • Students passing this module should be able to demonstrate:
  • Good IT skills in data handling, represention and anlysis.

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
2000 word meta-analysis assignment 50%
3000 word report of an evaluation or other research 50%

Formative Assessment:

Either one qualitative data analysis exercise or one quantitative data analysis exercise.

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