Analysing and integrating new sources of data reliably in innovative assessments

This chapter explores whether robust analytic techniques are available to generate defensible inferences from complex data generated by digital assessments, including process data. Digital technologies hold great promise for helping to bring about changes in educational measurement and assessment, but one challenge to be faced is how to accumulate different sources of evidence in defensible ways to make inferences when constructs and observations include inherent complexity. This chapter discusses some potential solutions for making measurement inferences at scale using complex data, notably hybrid measurement models that incorporate one measurement model within another. The chapter conceptually draws on an example of a complex task in a technology-rich environment from the OECD Platform for Innovative Learning Assessments (PILA) to highlight this analytical approach.