EduLive: Re-Creating Cues for Instructor-Learners Interaction in Educational Live Streams with Learners' Transcript-Based Annotations

Educational live streaming has become a complement to in-person teaching. While synchronous instructor-learner communication is useful, the technology-mediated nature of live streaming can obscure many interaction cues (e.g., learners' facial expressions and body language), which dampens the instructors' ability to respond to remote learners' needs. We explore the opportunity of leveraging real-time transcripts generated from instructors' audio as a basis for re-creating interaction cues. Transcripts can be leveraged to reveal the content of live streams in a form that learners can trace back and annotate, and such annotations can be further aggregated and presented to instructors as signals to assist them in tracking learners' engagement. By designing and evaluating our proof-of-concept prototype system, EduLive, we show that instructors benefited from the summative information extracted from learners' annotations, and the context provided by the transcript enhanced their ability to answer learners' questions. Our system contributes to the design space of social annotations in CSCW by employing social annotations in educational live streaming scenarios.

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Publication Details

Journal
Proceedings of the ACM on Human-Computer Interaction
Published
2024-11-07
DOI
https://doi.org/10.1145/3686960
Primary Topic
Online Learning and Analytics
Type
article
Field-Weighted Citation Impact
0.00
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article

EduLive: Re-Creating Cues for Instructor-Learners Interaction in Educational Live Streams with Learners' Transcript-Based Annotations

Jeongeon Park, Jingchao Fang, Hao‐Chuan Wang, Juho Kim
Proceedings of the ACM on Human-Computer Interaction
Online Learning and Analytics
article

EduLive: Re-Creating Cues for Instructor-Learners Interaction in Educational Live Streams with Learners' Transcript-Based Annotations

Jeongeon Park, Jingchao Fang, Hao‐Chuan Wang, Juho Kim
article en

Abstract

Educational live streaming has become a complement to in-person teaching. While synchronous instructor-learner communication is useful, the technology-mediated nature of live streaming can obscure many interaction cues (e.g., learners' facial expressions and body language), which dampens the instructors' ability to respond to remote learners' needs. We explore the opportunity of leveraging real-time transcripts generated from instructors' audio as a basis for re-creating interaction cues. Transcripts can be leveraged to reveal the content of live streams in a form that learners can trace back and annotate, and such annotations can be further aggregated and presented to instructors as signals to assist them in tracking learners' engagement. By designing and evaluating our proof-of-concept prototype system, EduLive, we show that instructors benefited from the summative information extracted from learners' annotations, and the context provided by the transcript enhanced their ability to answer learners' questions. Our system contributes to the design space of social annotations in CSCW by employing social annotations in educational live streaming scenarios.

Proceedings of the ACM on Human-Computer InteractionVol. 8(CSCW2)
Korea Advanced Institute of Science and Technology (KR), Daegu Gyeongbuk Institute of Science and Technology (KR), University of California, Davis (US)
Quality Education
Openalex Percentile: Top 79%
Online Learning and Analytics
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EduLive: Re-Creating Cues for Instructor-Learners Interaction in Educational Live Streams with Learners' Transcript-Based Annotations — Jeongeon Park, Jingchao Fang, et al. · Proceedings of the ACM on Human-Computer Interaction (2024) | TGRS Research Map | TGRS