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TRUVACE RECORD VERSION
record: TRV-2026-0811
version: 1
kind: certified
reason: Certified into the record
timestamp: 2026-08-17T06:23:32.418679Z
status: published
lens: p_space
sector: education
headline: Personalizing Assignments in the AI Era: The Role of Engaged Pedagogy
dek: Generative artificial intelligence (Gen AI) has taken the academic world by storm. This G.I.F.T.S. paper argues that personalizing academic assignments may curb students’ tendency to copy and paste content from Gen AI outputs. I demonstrate how I personalized a written assignment in one of my courses. A total of 81 paper grades were analyzed, and no significant difference was found between stud...
gain_title: (none)
problem_title: Personalizing the assignment did not produce a significant improvement in student paper grades.
trace_subject: (none)
gain_reading: (none)
gain_evidence: (none)
problem_reading: Personalizing the assignment did not produce a significant improvement in student paper grades.
problem_evidence: A total of 81 paper grades were analyzed, and no significant difference was found between stud...
quick_read: A faculty author describes personalizing a written assignment to reduce students copying and pasting from generative AI outputs, then analyzes 81 paper grades from the course to assess impact.

The reported finding of no significant difference in grades matters for academic integrity efforts because it suggests personalization alone may not improve performance, leaving open whether it actually reduced AI copying, how students engaged, and whether results would hold beyond this single-course sample.
limitation: Study reports no significant difference based on 81 paper grades from a single course, limiting generalizability and leaving whether copying behavior actually changed unresolved.
tag: Evidence-backed problem
key_points: Author personalized a written assignment to address Gen AI copying in a course. | Analysis included 81 paper grades comparing personalized assignment outcomes. | No significant difference was found between student groups on paper grades.
rundown: The paper is framed as a G.I.F.T.S. contribution describing how the author personalized a written assignment in one course to address Gen AI copying.

The evaluation is based on 81 paper grades, with the reported result that no significant difference was found between student groups, suggesting personalization did not change grade outcomes in this setting.
sources:
- peer_reviewed | Roger Williams University - Digital Commons (Roger Williams University) | https://docs.rwu.edu/nyscaproceedings/vol2025/iss1/7 | 2026-09-01
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79fbe31cf7608b7fdfd6176fa2aef9d00469a7183079fcbc7fa6ab37e59e8d58

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