Maria Goldshtein
Author directory2026
Does an Automated Source Integration Score Respond to Revision? Extending Evidence of Construct Validity with a Feedback Experiment
Andrew Potter | Yu Tian | Kaitlin Van Houghton | Manmeet Singh | Renu Balyan | Maria Goldshtein | Laura K. Allen | Danielle S. McNamara
Proceedings of the Artificial Intelligence in Measurement and Education Conference (AIME-Con): Works in Progress
Andrew Potter | Yu Tian | Kaitlin Van Houghton | Manmeet Singh | Renu Balyan | Maria Goldshtein | Laura K. Allen | Danielle S. McNamara
Proceedings of the Artificial Intelligence in Measurement and Education Conference (AIME-Con): Works in Progress
This study examined whether an automated source integration measure responds to revision. In a randomized experiment, undergraduates drafted and revised a source-based essay. Source integration scores increased across drafts, although gains did not differ significantly between students who received source integration feedback and those who did not. Findings support use of the measure for formative evaluation and feedback.