Beyond Outcomes: Assessing the Process of Problem Solving Using Process Education
TL;DR
It is argued that process-oriented assessment offers a constructive response to generative AI by shifting attention from detecting tool use to evaluating the quality of student reasoning, and supports growth-oriented feedback that helps learners improve their learning skills and future performances.
Abstract
The link between a finished course assignment and the learning required to produce it is increasingly uncertain. In the era of generative artificial intelligence, polished coursework can be created in moments without demonstrating the reasoning, judgment, or productive struggle traditionally associated with learning. Product-focused grading may therefore be evaluating the AI tool used to produce it, not the learner’s actual performance. This article presents Process Education’s assessment framework for assessing four links in the problem solving performance chain: definition, strategy, implementation, and validation. Rather than focusing solely on the final product, the framework makes the learner’s process more visible and assessable. Practical tools include a seven-dimension process rubric, the Strengths-Improvements-Insights (SII) feedback method, coaching prompts designed to elicit process evidence, and illustrative student examples. During the related AALHE conference session, participants analyzed individual samples, identified broken process links, and drafted formative feedback intended to strengthen future performance. The article argues that process-oriented assessment offers a constructive response to generative AI by shifting attention from detecting tool use to evaluating the quality of student reasoning. It also supports growth-oriented feedback that helps learners improve their learning skills and future performances, strengthen self-assessment, and develop insights transferable across contexts.