1. Handbook
  2. Subjects
  3. Measurement Analytics

Measurement Analytics (MAST90131)

Graduate courseworkPoints: 12.5Online

You’re viewing the 2019 Handbook:
Or view archived Handbooks


Year of offer2019
Subject levelGraduate coursework
Subject codeMAST90131
Term 3 - Online
FeesSubject EFTSL, Level, Discipline & Census Date

Measurement analytics combines measurement science and validity theory with analytics methods. Its main application is to assess human (or sometimes organisational) performance or attributes, using digital big data and analytical techniques. Use of measurement analytics is appropriate when the objective of the analyst is to build reliable and valid assessments of individuals, especially when attributes or levels of performance can only be inferred, not directly observed, and when results have consequences for the individuals concerned.

There are many applications: in education, to any assessment of competence or understanding; in health and human services, to assessments of patient physiological or psychological status; in the professions and vocations for recruitment, to assessment of complex skills, including in areas such as music, sport, and non-cognitive attributes such as attitudes, values and beliefs; and in situations when automated assessments are generated from games, essays, videos or interviews.

In this subject students will develop an understanding of the rationale for using measurement analytics rather than alternative analytics techniques and become familiar with contemporary and emerging applications. This subject provides students with the ability to assess claims to reliability and validity of analytics-based assessments of attributes or performance of individuals, and provides basic understandings and skills in how to maximize validity using complex digital data.

Intended learning outcomes

  • Understand the principles of measurement and learning analytics as well as the rationale for using measurement analytics rather than alternative techniques such as data mining, cluster or regression analysis for assessment purposes.
  • Understand and explore how various data and information can be used to measure complex human attributes and performance.
  • Understand and apply common approaches to conceptualizing human attributes for the purposes of assessment.
  • Apply measurement analytics techniques to digital big-data sets to generate and interpret measures.
  • Understand contemporary applications of measurement analytics to automated, algorithm-based, online adaptive assessment applications, especially those based on machine learning or data mining.

Generic skills

  • Students will be provided with the opportunity to practice and reinforce: • High level written communication skills. • Advanced information and interpretation skills. • Advanced analytic, integration and problem-solving skills • Demonstrate competence in critical and theoretical thinking through report writing and online discussions.

Last updated: 21 September 2019