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2021 | OriginalPaper | Chapter

EduPal Leaves No Professor Behind: Supporting Faculty via a Peer-Powered Recommender System

Authors : Nourhan Sakr, Aya Salama, Nadeen Tameesh, Gihan Osman

Published in: Artificial Intelligence in Education

Publisher: Springer International Publishing

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Abstract

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.

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previous chapter Exploring Dialogism Using Language Models

next chapter Computer-Supported Human Mentoring for Personalized and Equitable Math Learning

According to the Carnegie Classification of Institutions of Higher Education.

Future updates will verify that the user is faculty and that their recommendation is supported by research before incorporating their feedback/rating.

80% were STEM, 70% were female, experience ranged from 2 to 32 years.

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Title: EduPal Leaves No Professor Behind: Supporting Faculty via a Peer-Powered Recommender System
Authors: Nourhan Sakr
Aya Salama
Nadeen Tameesh
Gihan Osman
Publisher: Springer International Publishing
Book: Artificial Intelligence in Education
Print ISBN: 978-3-030-78269-6

Electronic ISBN: 978-3-030-78270-2

Copyright Year: 2021
DOI: https://doi.org/10.1007/978-3-030-78270-2_54

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