A popular definition describes learning analytics as measuring, collecting, analyzing and reporting of data about learners. The main purpose thereof is to understand and support learning processes. Thus, the main research goals of learning analytics remarkably overlap with those of educational assessment and psychometrics. To demonstrate how these goals are pursued (maybe differently) in educational assessment, the present talk will review key concepts of educational assessment including principles of item and test development (e.g., evidence centered design), the validation of test score interpretations (e.g., construct validation), as well as the psychometric modelling of test data to describe learning outcomes and trajectories (e.g., IRT measurement models). These concepts will be illustrated by examples from our own research utilizing product and process data.
Frank Goldhammer is professor for educational and psychological assessment (Technology-Based Assessment and Instruction) at the Goethe University Frankfurt a. M. and the Centre for International Student Assessment (ZIB). He is head of the Centre for Technology Based Assessment (TBA) at the German Institute for International Educational Research (DIPF). His current research activities include technology-based assessment (e.g., validation), the use of process data from cognitive and non-cognitive assessments, modelling response times and experimental control, as well as the assessment of digital skills and motivational context variables.