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Programmatic assessment for learning: A programmatically designed assessment for the purpose of learning: AMEE Guide
Dario Torre1, Lambert Schuwirth2
1University of Central Florida College of Medicine, Orlando, FL, USA.
Medical Teacher
|October 5, 2024
Summary
Programmatic assessment for learning (PAL) uses structured data collection to enhance learning. This guide clarifies PAL terminology, learning processes, validity, and future AI integration in assessment.
Area of Science:
- Educational Assessment
- Learning Sciences
Background:
- Programmatic assessment for learning (PAL) is an evolving educational approach.
- It involves the structured collection of assessment data specifically for learning enhancement.
Purpose of the Study:
- To provide recommendations on key aspects of PAL.
- To clarify terminology and outline guiding learning processes.
- To examine validity and future directions, including AI's role.
Main Methods:
- Review of the evolution of programmatic assessment.
- Outline of learning processes (distributed learning, interleaving, overlearning, test-enhanced learning).
- Analysis of validity from a programmatic perspective and future AI opportunities.
Main Results:
- Clarification of PAL terminology and its historical development.
- Identification of key learning processes that inform PAL design.
- Insights into the evolving nature of validity and AI's impact on assessment.
Conclusions:
- PAL offers a structured framework for leveraging assessment data to improve learning.
- Understanding learning processes and validity is crucial for effective PAL implementation.
- Artificial intelligence presents significant opportunities and challenges for the future of assessment.
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