An AI Teaching Assistant for Motion Picture Engineering

TL;DR

This study presents the implementation and evaluation of an AI Teaching Assistant using Retrieval Augmented Generation in a Motion Picture Engineering course, demonstrating its effectiveness and impact on student learning.

Contribution

It provides detailed implementation, tuning, and evaluation of an AI-TA in a university course, including its use in open-book exams and student feedback analysis.

Findings

AI-TA showed positive student feedback with a mean of 4.22/5.

No significant difference in exam performance with or without AI-TA access.

The experiment involved 43 students, 296 sessions, and 1,889 queries over 7 weeks.

Abstract

The rapid rise of LLMs over the last few years has promoted growing experimentation with LLM-driven AI tutors. However, the details of implementation, as well as the benefit in a teaching environment, are still in the early days of exploration. This article addresses these issues in the context of implementation of an AI Teaching Assistant (AI-TA) using Retrieval Augmented Generation (RAG) for Trinity College Dublin's Master's Motion Picture Engineering (MPE) course. We provide details of our implementation (including the prompt to the LLM, and code), and highlight how we designed and tuned our RAG pipeline to meet course needs. We describe our survey instrument and report on the impact of the AI-TA through a number of quantitative metrics. The scale of our experiment (43 students, 296 sessions, 1,889 queries over 7 weeks) was sufficient to have confidence in our findings. Unlike previous studies, we experimented with allowing the use of the AI-TA in open-book examinations. Statistical analysis across three exams showed no performance differences regardless of AI-TA access (p > 0.05), demonstrating that thoughtfully designed assessments can maintain academic validity. Student feedback revealed that the AI-TA was beneficial (mean = 4.22/5), while students had mixed feelings about preferring it over human tutoring (mean = 2.78/5).