Preferred scoring and feedback methods differ significantly across assignment types, with AI-based scoring rarely preferred and mixed options most chosen for low-stakes assignments¶

Claim · All claims
Evidence · 1 study · associational r1 · q2 · i1 small
Currency · newest study 2026 · not yet checked against its sources · not reviewed by a person

Subclaims¶

q2 i1 A chi-square test showed a significant association between assignment type and preferred scoring/feedback method with a small printed effect size (Cramér's V = 0.16). → Yildirim-Erbasli 2026

Evidence¶

Yildirim-Erbasli 2026¶

Yildirim-Erbasli, S. N., Ilgun Dibek, M., Thomas, M. L., & Lesoway, N. (2026). When Do Undergraduate Students Prefer AI? Insights into AI Scoring and Feedback. Behavioral Sciences, 16(7), 1196. https://doi.org/10.3390/bs16071196

q2 · i1 · associational · r1

Chi-square test across five assignment types (general, low-stakes, high-stakes, creative, appeal-eligible) in the same survey. The association was significant, "χ2(12) = 35.19, p < 0.001", with printed effect size Cramér's V = 0.16 (small, coded i = 1); the article cautions about low expected cell counts.

"The results indicated a significant association between assignment type and preferred scoring/feedback method, χ2(12) = 35.19, p < 0.001, with a small effect size, Cramér's V = 0.16. Given that some expected cell counts were low, results should be interpreted with caution."

Discussion¶

Related Claims¶

• Undergraduate students' preferences for AI feedback characteristics differ significantly from an equal distribution for tone, length, format, and focus, but not for timing — related
• Students' preferences for AI versus human scoring and feedback vary significantly across assessment scenarios, with strong human preference for high-stakes tasks — related
• Frequency of AI use predicts AI feedback preference, while comfort with technology and frequency of human feedback predict relative preference for AI over human grading
• Students perceive AI scoring as accurate for grammar, mechanics, and organization but skeptical of its ability to evaluate diverse styles, complex writing, tone, and emotion
• Post-interaction reflections reveal four preference themes: AI as formative learning aid, preference for human authority, conditional acceptance, and skepticism about educational impact