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How Students Search Video Captions to Learn: An Analysis of Search Terms and Behavioral Timing Data

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Conference

2021 ASEE Virtual Annual Conference Content Access

Location

Virtual Conference

Publication Date

July 26, 2021

Start Date

July 26, 2021

End Date

July 19, 2022

Conference Session

Studies of Shifting In-person Courses to Online and Students' Online Behavior

Tagged Division

Educational Research and Methods

Page Count

25

Permanent URL

https://peer.asee.org/37257

Download Count

54

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Paper Authors

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Zhilin Zhang University of Illinois at Urbana-Champaign

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Zhilin Zhang is a 5-year BS-MS student in Computer Science at the University of Illinois at Urbana-Champaign (UIUC), co-advised by Professor Lawrence Angrave and Professor Karrie Karahalios. His research interests are in Human-Computer Interaction and Learning Sciences. He studies, designs, and builds intelligent systems to support scalable and accessible teaching and learning through a computational lens.

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Bhavya Bhavya University of Illinois at Urbana-Champaign

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Bhavya is a Ph.D. student in Computer Science at the University of Illinois at Urbana-Champaign advised by Dr. Chengxiang Zhai. Her research interests are in novel applications of text mining, machine learning, and human-machine collaboration, particularly for improving education and health care.

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Lawrence Angrave University of Illinois at Urbana-Champaign Orcid 16x16 orcid.org/0000-0001-9762-7181

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Lawrence Angrave is an award winning Fellow and Teaching Professor at the department of computer science at the University of Illinois at Urbana-Champaign (UIUC). His interests include (but are not limited to) joyful teaching, empirically-sound educational research, campus and online courses, computer science, engaging underrepresented students, improving accessibility and creating novel methods that encourage new learning opportunities and foster vibrant learning communities.

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Ruihua Sui University of Illinois at Urbana-Champaign

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Ruihua Sui is a senior student in Mathematics and Computer Science at the University of Illinois at Urbana-Champaign. He is interested in software development, and was nominated for Illinois Innovation Prize and received ICCP James N. Snyder Memorial Award in 2020 because of his contribution to the educational software ClassTranscribe.

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Rob Kooper University of Illinois at Urbana-Champaign Orcid 16x16 orcid.org/0000-0002-5781-7287

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Rob Kooper is a lead research programmer at the software directorate at the National Center for Super computing Applications. He is interested in enabling scientists to do research work using software developed with the help of NCSA as well as teaching good software principles during this process. He is interested in software deployment and scaling software deployments from small research projects to larger installations with many users.

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Chirantan Mahipal University of Illinois at Urbana-Champaign

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I'm a Computer Science grad student at University of Illinois, Urbana-Champaign, working under the mentorship of Prof. Lawrence Angrave. Prior to this, I was working as a Research Fellow at Microsoft Research in the Technology for Emerging Markets (TEM) group.

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Yun Huang University of Illinois at Urbana-Champaign

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Dr. Yun Huang is faculty in the School of Information Sciences at the University of Illinois at Urbana-Champaign. Her expertise is in the area of social computing, human-computer interaction, Internet of Things, and human-AI interaction. In her work, she designs, implements and evaluates social computing systems that can engage community members to co-create new services for better community wellbeing.

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Abstract

Engineering students used ClassTranscribe, an accessible video player, in multiple engineering courses to view course videos and search for video content. The tool collected detailed timestamped student behavioral data from 1,894 students across 25 engineering courses that included what individual students searched for and when. A previous analysis, published in ASEE 2020 [1], found that using ClassTranscribe caption search significantly predicted improvement in final exam scores in a computer science course. In this paper we present how students used the search functionality based on a more detailed analysis of the log data. ClassTranscribe automatically created captions and transcripts for all lecture videos using an Azure speech-to-text system that was supplemented with crowd-sourced editing to fix captioning errors. The search functionality used the timestamped caption data to find specific video moments both within the current video or across the entire course. The number of search activities per person ranged from zero to 186 events. An in-depth analysis of the students (N=167) who performed 1,022 searches was conducted to gain insight into student search needs and behaviors. Based on the total number of searches performed, students were grouped into “Infrequent Searcher” (< 18 searches) and “Frequent Searcher” (18 to 110 searches) using clustering algorithms. The search queries used by each group were found to follow the Zipf’s Law and were categorized into STEM-related terms, course logistics and others. Our study reports on students’ search context, behaviors, strategies, and optimizations. Using Universal Design for Learning as a foundation, we discuss the implications for educators, designers, and developers who are interested in providing new learning pathways to support and enhance video-based learning environments.

Zhang, Z., & Bhavya, B., & Angrave, L., & Sui, R., & Kooper, R., & Mahipal, C., & Huang, Y. (2021, July), How Students Search Video Captions to Learn: An Analysis of Search Terms and Behavioral Timing Data Paper presented at 2021 ASEE Virtual Annual Conference Content Access, Virtual Conference. https://peer.asee.org/37257

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