Ethel: A Virtual Teaching Assistant

Abstract

Generative AI has shown potential in solving physics problems and providing feedback on assessments. However, results are sometimes still inaccurate, at the wrong level, or using notations and definitions not appropriate for a particular course. A possible solution is augmenting the prompts with course-specific reference materials. Also, for feedback on homework solutions and grading exams, the problem text and the sample solution or grading rubric can be injected into the prompts. Project Ethel at ETH Zurich aims to construct a virtual teaching assistant using these practices.

References in corpus (1)

• Could an Artificial-Intelligence agent pass an introductory physics course?

Cited by in corpus (5)

• Assessing Confidence in AI-Assisted Grading of Physics Exams through Psychometrics: An Exploratory Study
• Performance of ChatGPT on tasks involving physics visual representations: the case of the Brief Electricity and Magnetism Assessment
• Creating a customisable Socratic AI physics tutor
• Exploring Large Language Models (LLMs) through interactive Python activities
• When AI Evaluates Its Own Work: Validating Learner-Initiated, AI-Generated Physics Practice Problems