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Main Authors: Sakr, Nourhan, Salama, Aya, Tameesh, Nadeen, Osman, Gihan
Format: Preprint
Published: 2021
Subjects:
Online Access:https://arxiv.org/abs/2104.12558
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author Sakr, Nourhan
Salama, Aya
Tameesh, Nadeen
Osman, Gihan
author_facet Sakr, Nourhan
Salama, Aya
Tameesh, Nadeen
Osman, Gihan
contents 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.
format Preprint
id arxiv_https___arxiv_org_abs_2104_12558
institution arXiv
publishDate 2021
record_format arxiv
spellingShingle EduPal leaves no professor behind: Supporting faculty via a peer-powered recommender system
Sakr, Nourhan
Salama, Aya
Tameesh, Nadeen
Osman, Gihan
Computers and Society
Information Retrieval
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.
title EduPal leaves no professor behind: Supporting faculty via a peer-powered recommender system
topic Computers and Society
Information Retrieval
url https://arxiv.org/abs/2104.12558