Artificial Intelligence for Video-based Learning at Scale

Kyoungwon Seo; Sidney Fels; Dongwook Yoon; Ido Roll; Samuel Dodson; Matthew Fong

doi:10.1145/3386527.3405937

Artificial Intelligence for Video-based Learning at Scale

Kyoungwon Seo, Sidney Fels, Dongwook Yoon, Ido Roll, Samuel Dodson, Matthew Fong

Dept. of Applied Artificial Intelligence

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

16 Scopus citations

Abstract

Video-based learning (VBL) is widespread; however, there are numerous challenges when teaching and learning with video. For instructors, creating effective instructional videos takes considerable time and effort. For students, watching videos can be a passive learning activity. Artificial intelligence (AI) has the potential to improve the VBL experience for students and teachers. This half-day workshop will bring together multi-disciplinary researchers and practitioners to collaboratively envision the future of VBL enhanced by AI. This workshop will be comprised of a group discussion followed by a presentation session. The goal of the workshop is to facilitate the cross-pollination of design ideas and critical assessments of AI approaches to VBL.

Original language	English
Title of host publication	L@S 2020 - Proceedings of the 7th ACM Conference on Learning @ Scale
Publisher	Association for Computing Machinery
Pages	215-217
Number of pages	3
ISBN (Electronic)	9781450379519
DOIs	https://doi.org/10.1145/3386527.3405937
State	Published - 12 Aug 2020
Event	7th Annual ACM Conference on Learning at Scale, L@S 2020 - Virtual, Online, United States Duration: 12 Aug 2020 → 14 Aug 2020

Publication series

Name	L@S 2020 - Proceedings of the 7th ACM Conference on Learning @ Scale

Conference

Conference	7th Annual ACM Conference on Learning at Scale, L@S 2020
Country/Territory	United States
City	Virtual, Online
Period	12/08/20 → 14/08/20

Keywords

artificial intelligence
computer vision
machine learning
natural language processing
video-based learning

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

Access to Document

10.1145/3386527.3405937

Cite this

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title = "Artificial Intelligence for Video-based Learning at Scale",

abstract = "Video-based learning (VBL) is widespread; however, there are numerous challenges when teaching and learning with video. For instructors, creating effective instructional videos takes considerable time and effort. For students, watching videos can be a passive learning activity. Artificial intelligence (AI) has the potential to improve the VBL experience for students and teachers. This half-day workshop will bring together multi-disciplinary researchers and practitioners to collaboratively envision the future of VBL enhanced by AI. This workshop will be comprised of a group discussion followed by a presentation session. The goal of the workshop is to facilitate the cross-pollination of design ideas and critical assessments of AI approaches to VBL.",

keywords = "artificial intelligence, computer vision, machine learning, natural language processing, video-based learning",

author = "Kyoungwon Seo and Sidney Fels and Dongwook Yoon and Ido Roll and Samuel Dodson and Matthew Fong",

note = "Publisher Copyright: {\textcopyright} 2020 ACM.; 7th Annual ACM Conference on Learning at Scale, L@S 2020 ; Conference date: 12-08-2020 Through 14-08-2020",

year = "2020",

month = aug,

day = "12",

doi = "10.1145/3386527.3405937",

language = "English",

series = "L@S 2020 - Proceedings of the 7th ACM Conference on Learning @ Scale",

publisher = "Association for Computing Machinery",

pages = "215--217",

booktitle = "L@S 2020 - Proceedings of the 7th ACM Conference on Learning @ Scale",

}

Seo, K, Fels, S, Yoon, D, Roll, I, Dodson, S & Fong, M 2020, Artificial Intelligence for Video-based Learning at Scale. in L@S 2020 - Proceedings of the 7th ACM Conference on Learning @ Scale. L@S 2020 - Proceedings of the 7th ACM Conference on Learning @ Scale, Association for Computing Machinery, pp. 215-217, 7th Annual ACM Conference on Learning at Scale, L@S 2020, Virtual, Online, United States, 12/08/20. https://doi.org/10.1145/3386527.3405937

Artificial Intelligence for Video-based Learning at Scale. / Seo, Kyoungwon; Fels, Sidney; Yoon, Dongwook et al.
L@S 2020 - Proceedings of the 7th ACM Conference on Learning @ Scale. Association for Computing Machinery, 2020. p. 215-217 (L@S 2020 - Proceedings of the 7th ACM Conference on Learning @ Scale).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

TY - GEN

T1 - Artificial Intelligence for Video-based Learning at Scale

AU - Seo, Kyoungwon

AU - Fels, Sidney

AU - Yoon, Dongwook

AU - Roll, Ido

AU - Dodson, Samuel

AU - Fong, Matthew

PY - 2020/8/12

Y1 - 2020/8/12

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AB - Video-based learning (VBL) is widespread; however, there are numerous challenges when teaching and learning with video. For instructors, creating effective instructional videos takes considerable time and effort. For students, watching videos can be a passive learning activity. Artificial intelligence (AI) has the potential to improve the VBL experience for students and teachers. This half-day workshop will bring together multi-disciplinary researchers and practitioners to collaboratively envision the future of VBL enhanced by AI. This workshop will be comprised of a group discussion followed by a presentation session. The goal of the workshop is to facilitate the cross-pollination of design ideas and critical assessments of AI approaches to VBL.

KW - artificial intelligence

KW - computer vision

KW - machine learning

KW - natural language processing

KW - video-based learning

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DO - 10.1145/3386527.3405937

M3 - Conference contribution

AN - SCOPUS:85094889904

T3 - L@S 2020 - Proceedings of the 7th ACM Conference on Learning @ Scale

SP - 215

EP - 217

BT - L@S 2020 - Proceedings of the 7th ACM Conference on Learning @ Scale

PB - Association for Computing Machinery

T2 - 7th Annual ACM Conference on Learning at Scale, L@S 2020

Y2 - 12 August 2020 through 14 August 2020

ER -

Artificial Intelligence for Video-based Learning at Scale

Abstract

Publication series

Conference

Keywords

UN SDGs

Access to Document

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