Undergraduate students' preferences for AI feedback characteristics differ significantly from an equal distribution for tone, length, format, and focus, but not for timing¶

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

Subclaims¶

q2 i? Chi-square goodness-of-fit tests showed significant deviations from equal distribution for feedback tone, length, format, and focus, while timing preferences did not differ significantly from chance. → 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 · i? · associational · r1

Chi-square goodness-of-fit tests in the survey study of 93 undergraduates tested whether preferences for AI feedback characteristics differed from an equal distribution. Four dimensions were significant, e.g., "feedback format (χ2(3) = 30.40, p < 0.001)", while timing was not (p = 0.087).

"The results were significant for feedback tone (χ2(3) = 15.86, p = 0.001), feedback length (χ2(3) = 11.65, p = 0.009), feedback format (χ2(3) = 30.40, p < 0.001), and feedback focus (χ2(3) = 18.27, p < 0.001). However, for feedback timing, the chi-square test was not significant, χ2(3) = 6.57, p = 0.087"

Discussion¶

Related Claims¶

• 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 — 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