TY - GEN
T1 - Sensor-free affect detection for a simulation-based science inquiry learning environment
AU - Paquette, Luc
AU - Baker, Ryan S.J.D.
AU - Sao Pedro, Michael A.
AU - Gobert, Janice D.
AU - Rossi, Lisa
AU - Nakama, Adam
AU - Kauffman-Rogoff, Zakkai
PY - 2014
Y1 - 2014
N2 - Recently, there has been considerable interest in understanding the relationship between student affect and cognition. This research is facilitated by the advent of automated sensor-free detectors that have been designed to "infer" affect from the logs of student interactions within a learning environment. Such detectors allow for fine-grained analysis of the impact of different affective states on a range of learning outcome measures. However, these detectors have to date only been developed for a subset of online learning environments, including problem-solving tutors, dialogue tutors, and narrative-based virtual environments. In this paper, we extend sensor-free affect detection to a science microworld environment, affording the possibility of more deeply studying and responding to student affect in this type of learning environment.
AB - Recently, there has been considerable interest in understanding the relationship between student affect and cognition. This research is facilitated by the advent of automated sensor-free detectors that have been designed to "infer" affect from the logs of student interactions within a learning environment. Such detectors allow for fine-grained analysis of the impact of different affective states on a range of learning outcome measures. However, these detectors have to date only been developed for a subset of online learning environments, including problem-solving tutors, dialogue tutors, and narrative-based virtual environments. In this paper, we extend sensor-free affect detection to a science microworld environment, affording the possibility of more deeply studying and responding to student affect in this type of learning environment.
KW - Educational data mining
KW - affect detection
KW - affective computing
UR - http://www.scopus.com/inward/record.url?scp=84958527919&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=84958527919&partnerID=8YFLogxK
U2 - 10.1007/978-3-319-07221-0_1
DO - 10.1007/978-3-319-07221-0_1
M3 - Conference contribution
AN - SCOPUS:84958527919
SN - 9783319072203
T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
SP - 1
EP - 10
BT - Intelligent Tutoring Systems - 12th International Conference, ITS 2014, Proceedings
PB - Springer
T2 - 12th International Conference on Intelligent Tutoring Systems, ITS 2014
Y2 - 5 June 2014 through 9 June 2014
ER -