EduPal leaves no professor behind: Supporting faculty via a peer-powered recommender system
This addresses the problem of insufficient teaching support for faculty, especially in underresourced settings, though it appears incremental as it builds on existing recommender and chatbot concepts.
The paper tackled the gap in pedagogical support for faculty after COVID-19 by proposing a peer-powered recommender system chatbot, which received favorable feedback in a prototype for STEM faculty.
The swift transitions in higher education after the COVID-19 outbreak identified a gap in the pedagogical support available to faculty. We propose a smart, knowledge-based chatbot that addresses issues of knowledge distillation and provides faculty with personalized recommendations. Our collaborative system crowdsources useful pedagogical practices and continuously filters recommendations based on theory and user feedback, thus enhancing the experiences of subsequent peers. We build a prototype for our local STEM faculty as a proof concept and receive favorable feedback that encourages us to extend our development and outreach, especially to underresourced faculty.