Team code comprehension dropped in lec09 when Implementation-phase AI usage peaked, and recovered in lec10 following instructor intervention¶

Claim · All claims
Evidence · 1 study · design r2 · q2
Currency · newest study 2026 · not yet checked against its sources · not reviewed by a person

Subclaims¶

q2 i? For teams other than Team 25C, code comprehension levels dropped in lec09 while their Implementation-phase AI usage became very high, and comprehension showed a measurable recovery in lec10 after instructor support. → Hidetake Tanaka 2026

Evidence¶

Hidetake Tanaka 2026¶

Hidetake Tanaka, Hiroshi Igaki, Kazumasa Shimari, Kiyoshi Honda, and Naoki Fukuyasu. (2026). Practical Implementation Report on Introducing Spec-Driven Development Using AI Agents in Software Development PBL. https://arxiv.org/abs/2608.30572 doi:10.48550/arxiv.2608.30572

q2 · i? · design · r2

Observation from comparing AI usage trends (Figure 4) with team comprehension trends (Figure 6b); the authors present the lec09 drop and lec10 recovery as a potential example of instructor intervention impact, not a tested effect.

"A potential ex ample of this im- pact was observed in lec09, where AI usage peaked and compreh ension scores dropped; however, following instructor support, compre- hension showed a mea- surable recovery in lec10."

Discussion¶

Related Claims¶

• In SDPBL with SDD introduced, AI usage varies greatly by team and phase, with all teams using AI in Implementation and Debugging but large team differences in Investigation and Planning — related
• Students who implemented code without AI (usage level 0) maintained consistently high code comprehension, while level-3 AI users showed very little comprehension in the Mid period — related
• Across the student body as a whole, no clear statistical trend was confirmed between AI usage levels and code comprehension — related
• Self-reported LLM usage collapses at the first team milestone and recovers only partially on later coding-heavy team tasks — related