ANVIL: Analogies and Videos for Lecturers
This work addresses the need for scalable creation of pedagogical animations for computer science educators, though the results are preliminary and incremental.
ANVIL automates the creation of analogy-based instructional animations for computer science, generating textual analogies and executable animations with a repair mechanism. Teacher evaluations and user studies show that produced materials are frequently rated as adequate and educators respond positively to its value and usability.
We present ANVIL, a multimodal generative system that automates the production of analogy-based instructional animations for computer science topics. Given a concept definition, ANVIL generates a textual analogy, compiles it into a structured visual screenplay, and produces executable manim code to render an animation, with an automated repair mechanism to improve robustness. Evaluating such systems at scale requires balancing pedagogical validity with scalability. We begin with a teacher evaluation to ground the quality assessment and use its findings to guide automated screening. For textual analogies, we introduce an LLM-based evaluator for scalable quality screening; for videos, where subjective judgments are difficult to automate, we instead assess fidelity to the intended screenplay using an automated proxy for auditing and error analysis. We further conduct a user study with educators to examine adoption requirements and risks. Our findings suggest that ANVIL can produce materials that are frequently rated as adequate, and that educators respond positively to its perceived value and usability.