Abstract Programmatic assessment for learning (PAL) involves programmatically structured collection of assessment data for the purpose of learning. In this guide, we examine and provide recommendations on several aspects: First, we review the evolution that has led to the development of programmatic assessment, providing clarification of some of its terminology. Second, we outline the learning processes that guide the design of PAL, including distributed learning, interleaving, overlearning, and test-enhanced learning. Third, we review the evolving nature of validity and provide insights into validity from a program perspective. Finally, we examine opportunities, challenges, and future directions of assessment in the context of artificial intelligence.

Programmatic assessment for learning: A programmatically designed assessment for the purpose of learning: AMEE Guide No. 174

Dario Torre
Membro del Collaboration Group
;
2025-01-01

Abstract

Abstract Programmatic assessment for learning (PAL) involves programmatically structured collection of assessment data for the purpose of learning. In this guide, we examine and provide recommendations on several aspects: First, we review the evolution that has led to the development of programmatic assessment, providing clarification of some of its terminology. Second, we outline the learning processes that guide the design of PAL, including distributed learning, interleaving, overlearning, and test-enhanced learning. Third, we review the evolving nature of validity and provide insights into validity from a program perspective. Finally, we examine opportunities, challenges, and future directions of assessment in the context of artificial intelligence.
2025
47
6
918
933
10.1080/0142159X.2024.2409936
Dario Torre; Lambert Schuwirth
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/2318/2126990
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