TY - GEN
T1 - Capturing difficulty expressions in student online Q&A discussions
AU - Yoo, Jaebong
AU - Jihie, Kim
N1 - Publisher Copyright:
Copyright © 2014, Association for the Advancement of Artificial Intelligence.
PY - 2014
Y1 - 2014
N2 - We introduce a new application of online dialogue analysis: supporting pedagogical assessment of online Q&A discussions. Extending the existing spcech act framework, we capture common emotional expressions that often appear in student discussions, such as frustration and degree of certainty, and present a viable approach for the classification. We demonstrate how such dialogue information can be used in analyzing student discussions and identifying difficulties. In particular, the difficulty expressions are aligned to discussion patterns and student performance. We found that frustration occurs more frequently in longer discussions. The students who frequently express frustration tend to get lower grades than others. On the other hand, frequency of high certainty expressions is positively correlated with the performance. We expect such dialogue analyses can become a powerful assessment tool for instructors and education researchers.
AB - We introduce a new application of online dialogue analysis: supporting pedagogical assessment of online Q&A discussions. Extending the existing spcech act framework, we capture common emotional expressions that often appear in student discussions, such as frustration and degree of certainty, and present a viable approach for the classification. We demonstrate how such dialogue information can be used in analyzing student discussions and identifying difficulties. In particular, the difficulty expressions are aligned to discussion patterns and student performance. We found that frustration occurs more frequently in longer discussions. The students who frequently express frustration tend to get lower grades than others. On the other hand, frequency of high certainty expressions is positively correlated with the performance. We expect such dialogue analyses can become a powerful assessment tool for instructors and education researchers.
UR - http://www.scopus.com/inward/record.url?scp=84908207309&partnerID=8YFLogxK
M3 - Conference contribution
AN - SCOPUS:84908207309
T3 - Proceedings of the National Conference on Artificial Intelligence
SP - 208
EP - 214
BT - Proceedings of the 28th AAAI Conference on Artificial Intelligence and the 26th Innovative Applications of Artificial Intelligence Conference and the 5th Symposium on Educational Advances in Artificial Intelligence
PB - AI Access Foundation
T2 - 28th AAAI Conference on Artificial Intelligence, AAAI 2014, 26th Innovative Applications of Artificial Intelligence Conference, IAAI 2014 and the 5th Symposium on Educational Advances in Artificial Intelligence, EAAI 2014
Y2 - 27 July 2014 through 31 July 2014
ER -