TY - GEN
T1 - Adapting learning activities selection in an intelligent tutoring system to affect
AU - Odo, Chinasa
N1 - Publisher Copyright:
© Springer International Publishing AG, part of Springer Nature 2018.
PY - 2018/6/20
Y1 - 2018/6/20
N2 - My PhD focuses on adapting learning activities selection to learner affect in an intelligent tutoring system. The research aims to investigate the affective states considered for adapting learning activity selection, and how to adapt to these. It also seeks to know how learner’s affective state can be obtained through tutor-learner interaction rather than via sensors or questionnaires. The research will use of a mixture of qualitative and quantitative methods to achieve these aims. This research will significantly contribute to the area of intelligent tutoring technology by providing more insights into how to adapt to affective states, and improve the delivery of learning. The result will lead to an algorithm for learning activity selection based on affect, which also incorporates other relevant learner characteristics, such as personalty, that moderate affect.
AB - My PhD focuses on adapting learning activities selection to learner affect in an intelligent tutoring system. The research aims to investigate the affective states considered for adapting learning activity selection, and how to adapt to these. It also seeks to know how learner’s affective state can be obtained through tutor-learner interaction rather than via sensors or questionnaires. The research will use of a mixture of qualitative and quantitative methods to achieve these aims. This research will significantly contribute to the area of intelligent tutoring technology by providing more insights into how to adapt to affective states, and improve the delivery of learning. The result will lead to an algorithm for learning activity selection based on affect, which also incorporates other relevant learner characteristics, such as personalty, that moderate affect.
KW - Affective state
KW - Learning activity selection
KW - Personalization
UR - http://www.scopus.com/inward/record.url?scp=85049367793&partnerID=8YFLogxK
U2 - 10.1007/978-3-319-93846-2_98
DO - 10.1007/978-3-319-93846-2_98
M3 - Published conference contribution
AN - SCOPUS:85049367793
SN - 9783319938455
T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
SP - 521
EP - 525
BT - Artificial Intelligence in Education - 19th International Conference, AIED 2018, Proceedings
A2 - Luckin, Rose
A2 - Porayska-Pomsta, Kaska
A2 - du Boulay, Benedict
A2 - Mavrikis, Manolis
A2 - Penstein Rosé, Carolyn
A2 - McLaren, Bruce
A2 - Martinez-Maldonado, Roberto
A2 - Hoppe, H. Ulrich
PB - Springer Verlag
T2 - 19th International Conference on Artificial Intelligence in Education, AIED 2018
Y2 - 27 June 2018 through 30 June 2018
ER -