Module PSYS3111: ADVANCED RESEARCH METHODS FOR APPLIED PSYCHOLOGY

Department: Psychology (Applied Psychology) [Queen's Campus, Stockton]

PSYS3111: ADVANCED RESEARCH METHODS FOR APPLIED PSYCHOLOGY

Prerequisites

• 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: 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

• 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

• 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

• 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

Summative Assessment

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