TY - GEN
T1 - Design of machine learning powered visualizations to support rapid assessment of online student discussions
AU - Sharma, Priya
AU - Li, Qiyuan
AU - Akgun, Mahir
N1 - Publisher Copyright:
© 2022 International Society of the Learning Sciences (ISLS). All rights reserved.
PY - 2022
Y1 - 2022
N2 - This paper reports on the design of machine learning powered analytic visualizations to support instructors in rapidly assessing student behavioral and cognitive engagement in online discussions. We used Chi's (2009) Interactive-Constructive-Active-Passive framework to assess cognitive engagement and social network analysis to assess behavioral engagement. We used the Long-Short-Term-Memory (LSTM) model to automatically classify discourse data. The model was trained based on 4000 human-rater coded posts and despite imbalanced data, the model shows relatively high accuracy. Three use case scenarios of the visualizations show that network and discourse analyses together support the instructor in ascertaining students' cognitive and behavioral engagement. Next steps for addressing model accuracy and improving visualizations are presented.
AB - This paper reports on the design of machine learning powered analytic visualizations to support instructors in rapidly assessing student behavioral and cognitive engagement in online discussions. We used Chi's (2009) Interactive-Constructive-Active-Passive framework to assess cognitive engagement and social network analysis to assess behavioral engagement. We used the Long-Short-Term-Memory (LSTM) model to automatically classify discourse data. The model was trained based on 4000 human-rater coded posts and despite imbalanced data, the model shows relatively high accuracy. Three use case scenarios of the visualizations show that network and discourse analyses together support the instructor in ascertaining students' cognitive and behavioral engagement. Next steps for addressing model accuracy and improving visualizations are presented.
UR - http://www.scopus.com/inward/record.url?scp=85145582887&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85145582887&partnerID=8YFLogxK
M3 - Conference contribution
AN - SCOPUS:85145582887
T3 - Proceedings of International Conference of the Learning Sciences, ICLS
SP - 455
EP - 458
BT - International Collaboration toward Educational Innovation for All
A2 - Weinberger, Armin
A2 - Chen, Wenli
A2 - Hernandez-Leo, Davinia
A2 - Chen, Bodong
PB - International Society of the Learning Sciences (ISLS)
T2 - 15th International Conference on Computer-Supported Collaborative Learning, CSCL 2022
Y2 - 6 June 2022 through 10 June 2022
ER -