Overview

This unit provides students with an understanding of the fundamentals of psychological measurement. Students will gain familiarity with the general process of developing psychological scales, including a variety of measurement methods and administration formats. The unit will also address topics in basic psychometric theory, including reliability, validity, and norms. Students will be given the opportunity to develop professionally relevant skills and experience in the selection, construction and evaluation of psychological tests and measures.

Requisites

Prerequisites
STA20006 Analysis of Variance and Regression
PSY20006 Cognition and Human Performance

Rules

STA20006 - Analysis of Variance and Regression

AND

PSY20006 - Cognition and Human Performance

Teaching periods
Location
Start and end dates
Last self-enrolment date
Census date
Last withdraw without fail date
Results released date
Semester 1
Location
Hawthorn
Start and end dates
02-March-2026
31-May-2026
Last self-enrolment date
15-March-2026
Census date
31-March-2026
Last withdraw without fail date
21-April-2026
Results released date
07-July-2026
Teaching Period 1
Location
Online
Start and end dates
09-March-2026
07-June-2026
Last self-enrolment date
22-March-2026
Census date
07-April-2026
Last withdraw without fail date
28-April-2026
Results released date
30-June-2026
Teaching Period 2
Location
Online
Start and end dates
06-July-2026
04-October-2026
Last self-enrolment date
19-July-2026
Census date
04-August-2026
Last withdraw without fail date
25-August-2026
Results released date
27-October-2026

Learning outcomes

Students who successfully complete this unit will be able to:

  • Describe the characteristics of a good psychological measure and explain how to evaluate the usefulness and appropriateness of a specific instrument for a specific application
  • Outline the steps involved in the development of psychological measures, and design your own program for the development and validation of a new measure
  • Calculate, report and interpret key statistics relevant to scale development and evaluation
  • Describe a range of different measurement formats and methods, explaining the pros and cons of each
  • Develop skills in effective Generative AI prompt creation and how to effectively incorporate AI generated output into an assessment task

Teaching methods

Hawthorn

Activity Type Activity Total Hours Number of Weeks Hours Per Week
On-campus Lecture 12 12 weeks 1
On-campus Class 24 12 weeks 2
Specified Activities Various 24 12 weeks 2
Unspecified Activities Various 90 12 weeks 7.5
Total Hours: 150 Total Hours (per week): 12.5

All Applicable Locations

Activity Type Activity Total Hours Number of Weeks Hours Per Week
Live Online Class 13 13 week 1
Online Directed Online Learning and Independent Learning 137 13 week 10.54
Total Hours: 150 Total Hours (per week): 11.54

Assessment

Type Task Weighting ULO's
Report 1 Individual  40%  1,2,5 
Report 2 Individual  50%  1,2,3,4 
Online Tests Individual  10%  1,2,3,4 

Content

  • Theories and methods for psychological measurement
  • Fundamentals of test construction
  • Methods for evaluating the properties and quality of tests
  • Administration and scoring of tests
  • Cultural appropriateness and sensitivity
  • Professional and ethical issues in psychological measurement and research
  • Graduate Attribute – Communication Skills: Communicating using different media
  • Graduate Attribute – Digital Literacies: Information literacy
  • Graduate Attribute – Digital Literacies: Technical literacy

Study resources

Reading materials

A list of reading materials and/or required textbooks will be available in the Unit Outline on Canvas.