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| Main Authors: | , , , |
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| Format: | Preprint |
| Published: |
2021
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| Subjects: | |
| Online Access: | https://arxiv.org/abs/2104.12558 |
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| _version_ | 1866917094113673216 |
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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 |