An AI-based Solution for Enhancing Delivery of Digital Learning for Future Teachers

There has been a recent and rapid shift to digital learning hastened by the pandemic but also influenced by ubiquitous availability of digital tools and platforms now, making digital learning ever more accessible. An integral and one of the most difficult part of scaling digital learning and teachin...

Ausführliche Beschreibung

Gespeichert in:
Bibliographische Detailangaben
Hauptverfasser: Kang, Yong-Bin, Forkan, Abdur Rahim Mohammad, Jayaraman, Prem Prakash, Wieland, Natalie, Kollias, Elizabeth, Du, Hung, Thomson, Steven, Li, Yuan-Fang
Format: Artikel
Sprache:eng
Schlagworte:
Online-Zugang:Volltext bestellen
Tags: Tag hinzufügen
Keine Tags, Fügen Sie den ersten Tag hinzu!
container_end_page
container_issue
container_start_page
container_title
container_volume
creator Kang, Yong-Bin
Forkan, Abdur Rahim Mohammad
Jayaraman, Prem Prakash
Wieland, Natalie
Kollias, Elizabeth
Du, Hung
Thomson, Steven
Li, Yuan-Fang
description There has been a recent and rapid shift to digital learning hastened by the pandemic but also influenced by ubiquitous availability of digital tools and platforms now, making digital learning ever more accessible. An integral and one of the most difficult part of scaling digital learning and teaching is to be able to assess learner's knowledge and competency. An educator can record a lecture or create digital content that can be delivered to thousands of learners but assessing learners is extremely time consuming. In the paper, we propose an Artificial Intelligence (AI)-based solution namely VidVersityQG for generating questions automatically from pre-recorded video lectures. The solution can automatically generate different types of assessment questions (including short answer, multiple choice, true/false and fill in the blank questions) based on contextual and semantic information inferred from the videos. The proposed solution takes a human-centred approach, wherein teachers are provided the ability to modify/edit any AI generated questions. This approach encourages trust and engagement of teachers in the use and implementation of AI in education. The AI-based solution was evaluated for its accuracy in generating questions by 7 experienced teaching professionals and 117 education videos from multiple domains provided to us by our industry partner VidVersity. VidVersityQG solution showed promising results in generating high-quality questions automatically from video thereby significantly reducing the time and effort for educators in manual question generation.
doi_str_mv 10.48550/arxiv.2112.01229
format Article
fullrecord <record><control><sourceid>arxiv_GOX</sourceid><recordid>TN_cdi_arxiv_primary_2112_01229</recordid><sourceformat>XML</sourceformat><sourcesystem>PC</sourcesystem><sourcerecordid>2112_01229</sourcerecordid><originalsourceid>FETCH-LOGICAL-a679-f1bdc7e871302c08a136c725fbebfae1b7df6e90976ffb1999d8ea27c27293273</originalsourceid><addsrcrecordid>eNotz71ugzAUBWAvHaq0D9CpfgGofSkYjyj_ElKGsKNrc51YoqYyEDVvX5F2OsM5OtLH2JsU6WeZ5-ID44-_pSAlpEIC6Gd2rgKvjonBkTp-Hvp58kPgboh8G64YrA8XvqHe3yje-eD4xl_8hD2vCWNYymW6m6c5Em8I7ZXi-MKeHPYjvf7nijW7bbM-JPVpf1xXdYKF0omTprOKSiUzAVaUKLPCKsidIeOQpFGdK0gLrQrnjNRadyUhKAsKdAYqW7H3v9uHqv2O_gvjvV107UOX_QK3y0oq</addsrcrecordid><sourcetype>Open Access Repository</sourcetype><iscdi>true</iscdi><recordtype>article</recordtype></control><display><type>article</type><title>An AI-based Solution for Enhancing Delivery of Digital Learning for Future Teachers</title><source>arXiv.org</source><creator>Kang, Yong-Bin ; Forkan, Abdur Rahim Mohammad ; Jayaraman, Prem Prakash ; Wieland, Natalie ; Kollias, Elizabeth ; Du, Hung ; Thomson, Steven ; Li, Yuan-Fang</creator><creatorcontrib>Kang, Yong-Bin ; Forkan, Abdur Rahim Mohammad ; Jayaraman, Prem Prakash ; Wieland, Natalie ; Kollias, Elizabeth ; Du, Hung ; Thomson, Steven ; Li, Yuan-Fang</creatorcontrib><description>There has been a recent and rapid shift to digital learning hastened by the pandemic but also influenced by ubiquitous availability of digital tools and platforms now, making digital learning ever more accessible. An integral and one of the most difficult part of scaling digital learning and teaching is to be able to assess learner's knowledge and competency. An educator can record a lecture or create digital content that can be delivered to thousands of learners but assessing learners is extremely time consuming. In the paper, we propose an Artificial Intelligence (AI)-based solution namely VidVersityQG for generating questions automatically from pre-recorded video lectures. The solution can automatically generate different types of assessment questions (including short answer, multiple choice, true/false and fill in the blank questions) based on contextual and semantic information inferred from the videos. The proposed solution takes a human-centred approach, wherein teachers are provided the ability to modify/edit any AI generated questions. This approach encourages trust and engagement of teachers in the use and implementation of AI in education. The AI-based solution was evaluated for its accuracy in generating questions by 7 experienced teaching professionals and 117 education videos from multiple domains provided to us by our industry partner VidVersity. VidVersityQG solution showed promising results in generating high-quality questions automatically from video thereby significantly reducing the time and effort for educators in manual question generation.</description><identifier>DOI: 10.48550/arxiv.2112.01229</identifier><language>eng</language><subject>Computer Science - Artificial Intelligence ; Computer Science - Computers and Society</subject><creationdate>2021-11</creationdate><rights>http://creativecommons.org/licenses/by/4.0</rights><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><link.rule.ids>228,230,776,881</link.rule.ids><linktorsrc>$$Uhttps://arxiv.org/abs/2112.01229$$EView_record_in_Cornell_University$$FView_record_in_$$GCornell_University$$Hfree_for_read</linktorsrc><backlink>$$Uhttps://doi.org/10.48550/arXiv.2112.01229$$DView paper in arXiv$$Hfree_for_read</backlink></links><search><creatorcontrib>Kang, Yong-Bin</creatorcontrib><creatorcontrib>Forkan, Abdur Rahim Mohammad</creatorcontrib><creatorcontrib>Jayaraman, Prem Prakash</creatorcontrib><creatorcontrib>Wieland, Natalie</creatorcontrib><creatorcontrib>Kollias, Elizabeth</creatorcontrib><creatorcontrib>Du, Hung</creatorcontrib><creatorcontrib>Thomson, Steven</creatorcontrib><creatorcontrib>Li, Yuan-Fang</creatorcontrib><title>An AI-based Solution for Enhancing Delivery of Digital Learning for Future Teachers</title><description>There has been a recent and rapid shift to digital learning hastened by the pandemic but also influenced by ubiquitous availability of digital tools and platforms now, making digital learning ever more accessible. An integral and one of the most difficult part of scaling digital learning and teaching is to be able to assess learner's knowledge and competency. An educator can record a lecture or create digital content that can be delivered to thousands of learners but assessing learners is extremely time consuming. In the paper, we propose an Artificial Intelligence (AI)-based solution namely VidVersityQG for generating questions automatically from pre-recorded video lectures. The solution can automatically generate different types of assessment questions (including short answer, multiple choice, true/false and fill in the blank questions) based on contextual and semantic information inferred from the videos. The proposed solution takes a human-centred approach, wherein teachers are provided the ability to modify/edit any AI generated questions. This approach encourages trust and engagement of teachers in the use and implementation of AI in education. The AI-based solution was evaluated for its accuracy in generating questions by 7 experienced teaching professionals and 117 education videos from multiple domains provided to us by our industry partner VidVersity. VidVersityQG solution showed promising results in generating high-quality questions automatically from video thereby significantly reducing the time and effort for educators in manual question generation.</description><subject>Computer Science - Artificial Intelligence</subject><subject>Computer Science - Computers and Society</subject><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2021</creationdate><recordtype>article</recordtype><sourceid>GOX</sourceid><recordid>eNotz71ugzAUBWAvHaq0D9CpfgGofSkYjyj_ElKGsKNrc51YoqYyEDVvX5F2OsM5OtLH2JsU6WeZ5-ID44-_pSAlpEIC6Gd2rgKvjonBkTp-Hvp58kPgboh8G64YrA8XvqHe3yje-eD4xl_8hD2vCWNYymW6m6c5Em8I7ZXi-MKeHPYjvf7nijW7bbM-JPVpf1xXdYKF0omTprOKSiUzAVaUKLPCKsidIeOQpFGdK0gLrQrnjNRadyUhKAsKdAYqW7H3v9uHqv2O_gvjvV107UOX_QK3y0oq</recordid><startdate>20211109</startdate><enddate>20211109</enddate><creator>Kang, Yong-Bin</creator><creator>Forkan, Abdur Rahim Mohammad</creator><creator>Jayaraman, Prem Prakash</creator><creator>Wieland, Natalie</creator><creator>Kollias, Elizabeth</creator><creator>Du, Hung</creator><creator>Thomson, Steven</creator><creator>Li, Yuan-Fang</creator><scope>AKY</scope><scope>GOX</scope></search><sort><creationdate>20211109</creationdate><title>An AI-based Solution for Enhancing Delivery of Digital Learning for Future Teachers</title><author>Kang, Yong-Bin ; Forkan, Abdur Rahim Mohammad ; Jayaraman, Prem Prakash ; Wieland, Natalie ; Kollias, Elizabeth ; Du, Hung ; Thomson, Steven ; Li, Yuan-Fang</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-a679-f1bdc7e871302c08a136c725fbebfae1b7df6e90976ffb1999d8ea27c27293273</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2021</creationdate><topic>Computer Science - Artificial Intelligence</topic><topic>Computer Science - Computers and Society</topic><toplevel>online_resources</toplevel><creatorcontrib>Kang, Yong-Bin</creatorcontrib><creatorcontrib>Forkan, Abdur Rahim Mohammad</creatorcontrib><creatorcontrib>Jayaraman, Prem Prakash</creatorcontrib><creatorcontrib>Wieland, Natalie</creatorcontrib><creatorcontrib>Kollias, Elizabeth</creatorcontrib><creatorcontrib>Du, Hung</creatorcontrib><creatorcontrib>Thomson, Steven</creatorcontrib><creatorcontrib>Li, Yuan-Fang</creatorcontrib><collection>arXiv Computer Science</collection><collection>arXiv.org</collection></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext_linktorsrc</fulltext></delivery><addata><au>Kang, Yong-Bin</au><au>Forkan, Abdur Rahim Mohammad</au><au>Jayaraman, Prem Prakash</au><au>Wieland, Natalie</au><au>Kollias, Elizabeth</au><au>Du, Hung</au><au>Thomson, Steven</au><au>Li, Yuan-Fang</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>An AI-based Solution for Enhancing Delivery of Digital Learning for Future Teachers</atitle><date>2021-11-09</date><risdate>2021</risdate><abstract>There has been a recent and rapid shift to digital learning hastened by the pandemic but also influenced by ubiquitous availability of digital tools and platforms now, making digital learning ever more accessible. An integral and one of the most difficult part of scaling digital learning and teaching is to be able to assess learner's knowledge and competency. An educator can record a lecture or create digital content that can be delivered to thousands of learners but assessing learners is extremely time consuming. In the paper, we propose an Artificial Intelligence (AI)-based solution namely VidVersityQG for generating questions automatically from pre-recorded video lectures. The solution can automatically generate different types of assessment questions (including short answer, multiple choice, true/false and fill in the blank questions) based on contextual and semantic information inferred from the videos. The proposed solution takes a human-centred approach, wherein teachers are provided the ability to modify/edit any AI generated questions. This approach encourages trust and engagement of teachers in the use and implementation of AI in education. The AI-based solution was evaluated for its accuracy in generating questions by 7 experienced teaching professionals and 117 education videos from multiple domains provided to us by our industry partner VidVersity. VidVersityQG solution showed promising results in generating high-quality questions automatically from video thereby significantly reducing the time and effort for educators in manual question generation.</abstract><doi>10.48550/arxiv.2112.01229</doi><oa>free_for_read</oa></addata></record>
fulltext fulltext_linktorsrc
identifier DOI: 10.48550/arxiv.2112.01229
ispartof
issn
language eng
recordid cdi_arxiv_primary_2112_01229
source arXiv.org
subjects Computer Science - Artificial Intelligence
Computer Science - Computers and Society
title An AI-based Solution for Enhancing Delivery of Digital Learning for Future Teachers
url https://sfx.bib-bvb.de/sfx_tum?ctx_ver=Z39.88-2004&ctx_enc=info:ofi/enc:UTF-8&ctx_tim=2025-01-24T11%3A08%3A02IST&url_ver=Z39.88-2004&url_ctx_fmt=infofi/fmt:kev:mtx:ctx&rfr_id=info:sid/primo.exlibrisgroup.com:primo3-Article-arxiv_GOX&rft_val_fmt=info:ofi/fmt:kev:mtx:journal&rft.genre=article&rft.atitle=An%20AI-based%20Solution%20for%20Enhancing%20Delivery%20of%20Digital%20Learning%20for%20Future%20Teachers&rft.au=Kang,%20Yong-Bin&rft.date=2021-11-09&rft_id=info:doi/10.48550/arxiv.2112.01229&rft_dat=%3Carxiv_GOX%3E2112_01229%3C/arxiv_GOX%3E%3Curl%3E%3C/url%3E&disable_directlink=true&sfx.directlink=off&sfx.report_link=0&rft_id=info:oai/&rft_id=info:pmid/&rfr_iscdi=true