Figurative Language in Computer Education: Evidence from YouTube Instructional Videos

Sherif Abdelhamid; Andrew Katz

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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: Computers in Education 4 - Online and Distributed Learning 1
Tagged Division: Computers in Education
Page Count: 13
DOI: 10.18260/1-2--37191
Permanent URL: https://peer.asee.org/37191
Download Count: 871

Paper Authors

biography

Sherif Abdelhamid Virginia Military Institute

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Sherif E. Abdelhamid serves as an Assistant Professor at the Computer and Information Sciences Department, Virginia Military Institute (VMI). Before joining VMI, he was an Assistant Professor at the College of Computing and Information Technology (AAST - Smart Village Campus, Egypt). He was also an Infrastructure Software Engineer at the Center for Open Science, Virginia, USA.

He obtained his Ph.D. and M.Sc. degrees in Computer Science from Virginia Tech and M.Sc. and B.Sc. degrees in Computer Science from AAST - Alexandria Campus, Egypt.

Dr. Abdelhamid’s research work spans three main fields, Computer Science, STEM Education, and Public Health. His research interests are in high-performance services-based computing solutions, novel digital educational technologies, and tools for the social network analysis of complex systems. More specifically, his research focuses on designing and building software systems and services (science-as-service) that enable students and domain experts from various fields to access and interact with various learning resources easily and perform data analyses and simulations to study large-scale biological information socio-technical (BIST) complex systems

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Andrew Katz Virginia Polytechnic Institute and State University

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Andrew Katz is an assistant professor in the Department of Engineering Education at Virginia Tech. He leads the Improving Decisions in Engineering Education Agents and Systems (IDEEAS) Lab, a group that uses multi-modal data to characterize, understand, and improve decisions made throughout engineering education ecosystems.

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Abstract

Educators are utilizing both traditional and novel electronic methods in teaching, including web-based modalities. According to existing literature, Web 2.0 in general and YouTube videos specifically are increasingly utilized in education. Web 2.0 applications, such as the popular online video network YouTube may enhance the students' learning and retention while providing connections with peers and faculty. The use of online video platforms, including Youtube in education, has been widely discussed in various research studies, including YouTube’s role in the students’ learning support, motivation, and engagement. Additionally, researchers have studied the use of YouTube videos in students’ self-regulated learning. However, few studies focused on the instructor’s stylistics in educational videos. Stylistics is the study and interpretation of texts or spoken language regarding their linguistic and tonal style. In this work, we studied instructor stylistics with a focus on the use of figurative language. In engineering courses, instructors tend to use metaphors, similes, and other forms of figurative language to connect new concepts with students’ existing knowledge base or communicate complex concepts with various non-technical audiences. Unfortunately for researchers interested in understanding instructional processes, most of these lectures or discussions are not recorded nor have footprints on the internet, making it hard to analyze and understand how instructors use this type of language in teaching. We utilized YouTube as a rich data source containing millions of educational videos that can be beneficial for both qualitative and quantitative studies that provide the opportunity to discover interesting patterns and themes. Specifically, We report on the results of a study in which we searched for, collected, and analyzed the use of figurative language in educational videos on YouTube teaching topics related to computer education. The videos are related to different topics in Computer Science and are targeting audiences of varying age groups. This approach is a multi-method one that involves both qualitative and quantitative data analyses. We present the data collection and analysis pipeline used in our study as a potential tool for other researchers to implement in their own work. The generated dataset from the pipeline consists of video transcripts, metadata, and other statistical and linguistic video attributes. Overall, this research work provides two contributions: (i) a view on the ways instructors utilize various forms of figurative languages across different topics and age groups in computer education and (ii) a fruitful approach to educational data collection. The results from the data analysis provide an opportunity for pedagogical and linguistic guidance to engineering education researchers and faculty members on the use and integration of accessible figurative language within the classroom. The generated dataset can also support linguists and computer scientists who are working on language, speech, and audio processing software systems and services, particularly conducting research within the fields of human-computer interaction, human-human interaction, video content understanding, and interactive dialog systems.

Citation
Format

Abdelhamid, S., & Katz, A. (2021, July), Figurative Language in Computer Education: Evidence from YouTube Instructional Videos Paper presented at 2021 ASEE Virtual Annual Conference Content Access, Virtual Conference. 10.18260/1-2--37191

TY - CPAPER
AB - Educators are utilizing both traditional and novel electronic methods in teaching, including web-based modalities. According to existing literature, Web 2.0 in general and YouTube videos specifically are increasingly utilized in education. Web 2.0 applications, such as the popular online video network YouTube may enhance the students&#39; learning and retention while providing connections with peers and faculty. The use of online video platforms, including Youtube in education, has been widely discussed in various research studies, including YouTube’s role in the students’ learning support, motivation, and engagement. Additionally, researchers have studied the use of YouTube videos in students’ self-regulated learning. However, few studies focused on the instructor’s stylistics in educational videos. Stylistics is the study and interpretation of texts or spoken language regarding their linguistic and tonal style.
In this work, we studied instructor stylistics with a focus on the use of figurative language. In engineering courses, instructors tend to use metaphors, similes, and other forms of figurative language to connect new concepts with students’ existing knowledge base or communicate complex concepts with various non-technical audiences. Unfortunately for researchers interested in understanding instructional processes, most of these lectures or discussions are not recorded nor have footprints on the internet, making it hard to analyze and understand how instructors use this type of language in teaching.
We utilized YouTube as a rich data source containing millions of educational videos that can be beneficial for both qualitative and quantitative studies that provide the opportunity to discover interesting patterns and themes. Specifically, We report on the results of a study in which we searched for, collected, and analyzed the use of figurative language in educational videos on YouTube teaching topics related to computer education. The videos are related to different topics in Computer Science and are targeting audiences of varying age groups. This approach is a multi-method one that involves both qualitative and quantitative data analyses. We present the data collection and analysis pipeline used in our study as a potential tool for other researchers to implement in their own work. The generated dataset from the pipeline consists of video transcripts, metadata, and other statistical and linguistic video attributes.
Overall, this research work provides two contributions: (i) a view on the ways instructors utilize various forms of figurative languages across different topics and age groups in computer education and (ii) a fruitful approach to educational data collection. The results from the data analysis provide an opportunity for pedagogical and linguistic guidance to engineering education researchers and faculty members on the use and integration of accessible figurative language within the classroom. The generated dataset can also support linguists and computer scientists who are working on language, speech, and audio processing software systems and services, particularly conducting research within the fields of human-computer interaction, human-human interaction, video content understanding, and interactive dialog systems.
AU - Sherif Abdelhamid
AU - Andrew Katz
CY - Virtual Conference
DA - 2021/07/26
PB - ASEE Conferences
TI - Figurative Language in Computer Education: Evidence from YouTube Instructional Videos
UR - https://peer.asee.org/37191
DO - 10.18260/1-2--37191
ER -