Available at: https://digitalcommons.calpoly.edu/theses/3319
Date of Award
6-2026
Degree Name
MS in Computer Science
Department/Program
Computer Science
College
College of Engineering
Advisor
Silas Hsu
Advisor Department
Computer Science
Advisor College
College of Engineering
Abstract
AI auto graders and virtual assistants are increasingly prevalent in educational set- tings. Although current literature demonstrates that AI chatbots can positively im- pact student motivation, there is little definitive evidence exploring whether these systems can replicate the effective motivational methods used by human teachers. Thus, in this experiment, we investigate how the perception of the identity of a tutor (AI versus human) impacts the psychological needs of students. 27 undergraduates taking introductory computer science courses were asked to explain code in plain English (EiPE). Participants received feedback from two tutors in within-subjects fashion: one human and one labeled as “AI”. The “AI” tutor was actually the same human tutor. Quantitative trends indicate a preference for the human tutor across dimensions of autonomy, relatedness, and overall enjoyment. During interviews, par- ticipants reported a stronger connection with human tutors, feeling more understood, and experiencing greater freedom to converse. Conversely, the “AI” tutor was valued as a non-judgmental space for learning. Our findings highlight how not only con- tent and accuracy of feedback shapes students’ experiences, but also expectations. In addition, based on our findings, we suggest AI deployment guidelines based on situations in which AI chatbots vs human instructors are most useful.