This paper introduces PIVOT, a framework that generates educational videos for STEM subjects by integrating pedagogical principles throughout the AI generation process, ensuring the content is effective for learning, not just visually coherent.

In plain terms

Current AI systems can create educational videos, but they often focus only on making the video look good, neglecting how people actually learn. This results in videos that might lack a clear teaching structure, reliable quality, or ways to check if students understand the material. To address this, researchers developed PIVOT (Pedagogy-guided Instructional VideO Tutoring), a system designed to generate instructional video tutors specifically for STEM (Science, Technology, Engineering, Math) subjects. PIVOT embeds *pedagogy*, which is the art and science of teaching, into every stage of video creation. This includes guiding the initial storyboard, generating and verifying the video's content for both accuracy and teaching effectiveness, and connecting it with assessments to identify and correct student misunderstandings. Experiments and evaluations by experts across four STEM areas showed that PIVOT produced videos with content well-aligned with teaching goals, clear and engaging presentation, and a logical instructional flow, leading to perceived effectiveness for learning. This highlights that AI systems in education should be judged not just by what they create, but by how well they support teaching practices, learner understanding, and corrective feedback.