TY - GEN
T1 - Predicting learner's project performance with dialogue features in online Q&A discussions
AU - Yoo, Jaebong
AU - Kim, Jihie
PY - 2012
Y1 - 2012
N2 - Although many college courses adopt online tools such as Q&A online discussions, there is no easy way to evaluate their impact on learning. In this paper, we investigate a predictive relation between characteristics of discussion contributions and student performance. For the modeling dynamics of conversational dialogue, speech acts (Q&A dialog roles that participants play) and emotional features covered by LIWC (Linguistic Inquiry and Word Count) were used. These dialogue information is used for correlation and regression analyses for predicting the performance of learners (173 student groups). Our current results indicate that the number of answers provided to others, the degree of positive emotion expressions, and how early students exchange information before the deadline correlate with project grades. This finding confirms the argument that in assessing student online activities, we need to capture how they interact, not just what they produce.
AB - Although many college courses adopt online tools such as Q&A online discussions, there is no easy way to evaluate their impact on learning. In this paper, we investigate a predictive relation between characteristics of discussion contributions and student performance. For the modeling dynamics of conversational dialogue, speech acts (Q&A dialog roles that participants play) and emotional features covered by LIWC (Linguistic Inquiry and Word Count) were used. These dialogue information is used for correlation and regression analyses for predicting the performance of learners (173 student groups). Our current results indicate that the number of answers provided to others, the degree of positive emotion expressions, and how early students exchange information before the deadline correlate with project grades. This finding confirms the argument that in assessing student online activities, we need to capture how they interact, not just what they produce.
KW - group projects
KW - Online discussions
KW - speech act classifiers
UR - http://www.scopus.com/inward/record.url?scp=84862502523&partnerID=8YFLogxK
U2 - 10.1007/978-3-642-30950-2_74
DO - 10.1007/978-3-642-30950-2_74
M3 - Conference contribution
AN - SCOPUS:84862502523
SN - 9783642309496
T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
SP - 570
EP - 575
BT - Intelligent Tutoring Systems - 11th International Conference, ITS 2012, Proceedings
T2 - 11th International Conference on Intelligent Tutoring Systems, ITS 2012
Y2 - 14 June 2012 through 18 June 2012
ER -