Virtual teaching assistant for undergraduate students using natural language processing & deep learning
保存先:
| 出版年: | arXiv.org (Nov 13, 2024), p. n/a |
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| 第一著者: | |
| その他の著者: | , , , |
| 出版事項: |
Cornell University Library, arXiv.org
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| 主題: | |
| オンライン･アクセス: | Citation/Abstract Full text outside of ProQuest |
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MARC
| LEADER | 00000nab a2200000uu 4500 | ||
|---|---|---|---|
| 001 | 3128885044 | ||
| 003 | UK-CbPIL | ||
| 022 | |a 2331-8422 | ||
| 024 | 7 | |a 10.1063/5.0192090 |2 doi | |
| 035 | |a 3128885044 | ||
| 045 | 0 | |b d20241113 | |
| 100 | 1 | |a Sakib, Sadman Jashim | |
| 245 | 1 | |a Virtual teaching assistant for undergraduate students using natural language processing & deep learning | |
| 260 | |b Cornell University Library, arXiv.org |c Nov 13, 2024 | ||
| 513 | |a Working Paper | ||
| 520 | 3 | |a Online education's popularity has been continuously increasing over the past few years. Many universities were forced to switch to online education as a result of COVID-19. In many cases, even after more than two years of online instruction, colleges were unable to resume their traditional classroom programs. A growing number of institutions are considering blended learning with some parts in-person and the rest of the learning taking place online. Nevertheless, many online education systems are inefficient, and this results in a poor rate of student retention. In this paper, we are offering a primary dataset, the initial implementation of a virtual teaching assistant named VTA-bot, and its system architecture. Our primary implementation of the suggested system consists of a chatbot that can be queried about the content and topics of the fundamental python programming language course. Students in their first year of university will be benefited from this strategy, which aims to increase student participation and involvement in online education. | |
| 653 | |a Teaching assistants | ||
| 653 | |a Python | ||
| 653 | |a Computer assisted instruction--CAI | ||
| 653 | |a Deep learning | ||
| 653 | |a Natural language processing | ||
| 653 | |a Student retention | ||
| 653 | |a Education | ||
| 653 | |a Learning | ||
| 653 | |a Programming languages | ||
| 653 | |a Undergraduate study | ||
| 653 | |a Students | ||
| 653 | |a Colleges & universities | ||
| 700 | 1 | |a Baktiar Kabir Joy | |
| 700 | 1 | |a Rydha, Zahin | |
| 700 | 1 | |a Nuruzzaman, Md | |
| 700 | 1 | |a Annajiat Alim Rasel | |
| 773 | 0 | |t arXiv.org |g (Nov 13, 2024), p. n/a | |
| 786 | 0 | |d ProQuest |t Engineering Database | |
| 856 | 4 | 1 | |3 Citation/Abstract |u https://www.proquest.com/docview/3128885044/abstract/embedded/ZKJTFFSVAI7CB62C?source=fedsrch |
| 856 | 4 | 0 | |3 Full text outside of ProQuest |u http://arxiv.org/abs/2411.09001 |