Handbook of Learning Analytics

Chapter 2

A Practitioner's Guide to Measurement in Learning Analytics: Decisions, Opportunities, and Challenges

Geraldine Gray & Yoav Bergner


What is our data measuring, why are we measuring it, and what can we infer from our measurements? These are key questions for models of learning, and the focus of this chapter. This chapter discusses the role of measurement in transitioning from predictive models of learning to models from which meaningful explanations about learning can be inferred. We consider how to associate latent constructs of learning with observable data from a variety of data sources relevant to learning contexts, illustrated with examples from recent LAK proceedings. We also review common sources of errors that arise with a variety of data collection instruments, and highlight the challenges and opportunities for progressing valid and reliable measurement of both learning itself and factors related to the learning process.

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