Quantifying the mismatch between course content and students' dialogue in online learning environments

Sunghoon Lim, Conrad S. Tucker, Kathryn Weed Jablokow, Bart Pursel

Research output: Chapter in Book/Report/Conference proceedingConference contribution

1 Citation (Scopus)

Abstract

Due to the internet's increasing global availability, online learning has become a new paradigm for distance learning in higher education. While student interactions and reactions are readily observable in a physical classroom environment, monitoring student interactions and quantifying divergence between lecture topics and the topics that interest students are challenging in online learning platforms. Understanding the effects of this divergence is important for monitoring student engagement and aiding instructors, who are focused on improving the quality of their online courses. The authors of this paper propose a topic modeling method, based on latent Dirichlet allocation (LDA), that quantifies the effects of divergence between course topics (mined from textual transcriptions) and studentdiscussed topics (mined from discussion forums). Correlations between the measured dissimilarities and (a) the number of posts and comments in discussion forums, (b) the number of submitted assignments, and (c) students' average performance scores are presented. A case study involving video lecture transcripts and discussion forum posts/comments in a massive open online course (MOOC) platform demonstrates the proposed method's potential success and informs course providers about the challenges of measuring the topics that interest students.

Original languageEnglish (US)
Title of host publication19th International Conference on Advanced Vehicle Technologies; 14th International Conference on Design Education; 10th Frontiers in Biomedical Devices
PublisherAmerican Society of Mechanical Engineers (ASME)
ISBN (Electronic)9780791858158
DOIs
StatePublished - Jan 1 2017
EventASME 2017 International Design Engineering Technical Conferences and Computers and Information in Engineering Conference, IDETC/CIE 2017 - Cleveland, United States
Duration: Aug 6 2017Aug 9 2017

Publication series

NameProceedings of the ASME Design Engineering Technical Conference
Volume3

Other

OtherASME 2017 International Design Engineering Technical Conferences and Computers and Information in Engineering Conference, IDETC/CIE 2017
CountryUnited States
CityCleveland
Period8/6/178/9/17

Fingerprint

Online Learning
Learning Environment
Divergence
Students
Monitoring
Distance Learning
Dissimilarity
Higher Education
Modeling Method
Interaction
Transcription
Dirichlet
Quantify
Assignment
Availability
Paradigm
Distance education
Demonstrate
Dialogue
Education

All Science Journal Classification (ASJC) codes

  • Mechanical Engineering
  • Computer Graphics and Computer-Aided Design
  • Computer Science Applications
  • Modeling and Simulation

Cite this

Lim, S., Tucker, C. S., Jablokow, K. W., & Pursel, B. (2017). Quantifying the mismatch between course content and students' dialogue in online learning environments. In 19th International Conference on Advanced Vehicle Technologies; 14th International Conference on Design Education; 10th Frontiers in Biomedical Devices (Proceedings of the ASME Design Engineering Technical Conference; Vol. 3). American Society of Mechanical Engineers (ASME). https://doi.org/10.1115/DETC2017-67339
Lim, Sunghoon ; Tucker, Conrad S. ; Jablokow, Kathryn Weed ; Pursel, Bart. / Quantifying the mismatch between course content and students' dialogue in online learning environments. 19th International Conference on Advanced Vehicle Technologies; 14th International Conference on Design Education; 10th Frontiers in Biomedical Devices. American Society of Mechanical Engineers (ASME), 2017. (Proceedings of the ASME Design Engineering Technical Conference).
@inproceedings{4ab618820ef74c349715b31cbc464e03,
title = "Quantifying the mismatch between course content and students' dialogue in online learning environments",
abstract = "Due to the internet's increasing global availability, online learning has become a new paradigm for distance learning in higher education. While student interactions and reactions are readily observable in a physical classroom environment, monitoring student interactions and quantifying divergence between lecture topics and the topics that interest students are challenging in online learning platforms. Understanding the effects of this divergence is important for monitoring student engagement and aiding instructors, who are focused on improving the quality of their online courses. The authors of this paper propose a topic modeling method, based on latent Dirichlet allocation (LDA), that quantifies the effects of divergence between course topics (mined from textual transcriptions) and studentdiscussed topics (mined from discussion forums). Correlations between the measured dissimilarities and (a) the number of posts and comments in discussion forums, (b) the number of submitted assignments, and (c) students' average performance scores are presented. A case study involving video lecture transcripts and discussion forum posts/comments in a massive open online course (MOOC) platform demonstrates the proposed method's potential success and informs course providers about the challenges of measuring the topics that interest students.",
author = "Sunghoon Lim and Tucker, {Conrad S.} and Jablokow, {Kathryn Weed} and Bart Pursel",
year = "2017",
month = "1",
day = "1",
doi = "10.1115/DETC2017-67339",
language = "English (US)",
series = "Proceedings of the ASME Design Engineering Technical Conference",
publisher = "American Society of Mechanical Engineers (ASME)",
booktitle = "19th International Conference on Advanced Vehicle Technologies; 14th International Conference on Design Education; 10th Frontiers in Biomedical Devices",

}

Lim, S, Tucker, CS, Jablokow, KW & Pursel, B 2017, Quantifying the mismatch between course content and students' dialogue in online learning environments. in 19th International Conference on Advanced Vehicle Technologies; 14th International Conference on Design Education; 10th Frontiers in Biomedical Devices. Proceedings of the ASME Design Engineering Technical Conference, vol. 3, American Society of Mechanical Engineers (ASME), ASME 2017 International Design Engineering Technical Conferences and Computers and Information in Engineering Conference, IDETC/CIE 2017, Cleveland, United States, 8/6/17. https://doi.org/10.1115/DETC2017-67339

Quantifying the mismatch between course content and students' dialogue in online learning environments. / Lim, Sunghoon; Tucker, Conrad S.; Jablokow, Kathryn Weed; Pursel, Bart.

19th International Conference on Advanced Vehicle Technologies; 14th International Conference on Design Education; 10th Frontiers in Biomedical Devices. American Society of Mechanical Engineers (ASME), 2017. (Proceedings of the ASME Design Engineering Technical Conference; Vol. 3).

Research output: Chapter in Book/Report/Conference proceedingConference contribution

TY - GEN

T1 - Quantifying the mismatch between course content and students' dialogue in online learning environments

AU - Lim, Sunghoon

AU - Tucker, Conrad S.

AU - Jablokow, Kathryn Weed

AU - Pursel, Bart

PY - 2017/1/1

Y1 - 2017/1/1

N2 - Due to the internet's increasing global availability, online learning has become a new paradigm for distance learning in higher education. While student interactions and reactions are readily observable in a physical classroom environment, monitoring student interactions and quantifying divergence between lecture topics and the topics that interest students are challenging in online learning platforms. Understanding the effects of this divergence is important for monitoring student engagement and aiding instructors, who are focused on improving the quality of their online courses. The authors of this paper propose a topic modeling method, based on latent Dirichlet allocation (LDA), that quantifies the effects of divergence between course topics (mined from textual transcriptions) and studentdiscussed topics (mined from discussion forums). Correlations between the measured dissimilarities and (a) the number of posts and comments in discussion forums, (b) the number of submitted assignments, and (c) students' average performance scores are presented. A case study involving video lecture transcripts and discussion forum posts/comments in a massive open online course (MOOC) platform demonstrates the proposed method's potential success and informs course providers about the challenges of measuring the topics that interest students.

AB - Due to the internet's increasing global availability, online learning has become a new paradigm for distance learning in higher education. While student interactions and reactions are readily observable in a physical classroom environment, monitoring student interactions and quantifying divergence between lecture topics and the topics that interest students are challenging in online learning platforms. Understanding the effects of this divergence is important for monitoring student engagement and aiding instructors, who are focused on improving the quality of their online courses. The authors of this paper propose a topic modeling method, based on latent Dirichlet allocation (LDA), that quantifies the effects of divergence between course topics (mined from textual transcriptions) and studentdiscussed topics (mined from discussion forums). Correlations between the measured dissimilarities and (a) the number of posts and comments in discussion forums, (b) the number of submitted assignments, and (c) students' average performance scores are presented. A case study involving video lecture transcripts and discussion forum posts/comments in a massive open online course (MOOC) platform demonstrates the proposed method's potential success and informs course providers about the challenges of measuring the topics that interest students.

UR - http://www.scopus.com/inward/record.url?scp=85034651364&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=85034651364&partnerID=8YFLogxK

U2 - 10.1115/DETC2017-67339

DO - 10.1115/DETC2017-67339

M3 - Conference contribution

AN - SCOPUS:85034651364

T3 - Proceedings of the ASME Design Engineering Technical Conference

BT - 19th International Conference on Advanced Vehicle Technologies; 14th International Conference on Design Education; 10th Frontiers in Biomedical Devices

PB - American Society of Mechanical Engineers (ASME)

ER -

Lim S, Tucker CS, Jablokow KW, Pursel B. Quantifying the mismatch between course content and students' dialogue in online learning environments. In 19th International Conference on Advanced Vehicle Technologies; 14th International Conference on Design Education; 10th Frontiers in Biomedical Devices. American Society of Mechanical Engineers (ASME). 2017. (Proceedings of the ASME Design Engineering Technical Conference). https://doi.org/10.1115/DETC2017-67339