TY - GEN
T1 - Keeping the teacher in the loop
T2 - 18th International Conference on Artificial Intelligence in Education, AIED 2017
AU - Segal, Avi
AU - Hindi, Shaked
AU - Prusak, Naomi
AU - Swidan, Osama
AU - Livni, Adva
AU - Palatnic, Alik
AU - Schwarz, Baruch
AU - Gal, Ya’akov Kobi
N1 - Funding Information:
Thanks very much to the Math Forum for making it possible for us to use the development version of the VMT software. Thanks to Roy Fairstein for developing the NLP and visualization interfaces to SAGLET. This work was funded in part thanks to the Kamin fund by the Israeli Ministry of Trade and Industry.
Publisher Copyright:
© Springer International Publishing AG 2017.
PY - 2017/1/1
Y1 - 2017/1/1
N2 - Learning in groups allows students to develop academic and social competencies but requires the presence of a human teacher that is actively guiding the group. In this paper we combine data-mining and visualization tools to support teachers’ understanding of learners’ activities in an inquiry based learning environment. We use supervised learning to recognize salient states of activity in the group’s work, such as reaching a solution to a problem, exhibiting idleness, or experiencing technical challenges. These “critical” moments are visualized to teachers in real time, allowing them to monitor several groups in parallel and to intervene when necessary to guide the group. We embedded this technology in a new system, called SAGLET, which augments existing collaborative educational software and was evaluated empirically in real classrooms. We show that the recognition capabilities of SAGLET are compatible with that of a human domain expert. Teachers were able to use the system successfully to make intervention decisions in groups when deemed necessary, without overwhelming them with information. Our results demonstrate how AI can be used to augment existing educational environments to support the “teacher in the group”, and to scale up the benefits of group learning to the actual classroom.
AB - Learning in groups allows students to develop academic and social competencies but requires the presence of a human teacher that is actively guiding the group. In this paper we combine data-mining and visualization tools to support teachers’ understanding of learners’ activities in an inquiry based learning environment. We use supervised learning to recognize salient states of activity in the group’s work, such as reaching a solution to a problem, exhibiting idleness, or experiencing technical challenges. These “critical” moments are visualized to teachers in real time, allowing them to monitor several groups in parallel and to intervene when necessary to guide the group. We embedded this technology in a new system, called SAGLET, which augments existing collaborative educational software and was evaluated empirically in real classrooms. We show that the recognition capabilities of SAGLET are compatible with that of a human domain expert. Teachers were able to use the system successfully to make intervention decisions in groups when deemed necessary, without overwhelming them with information. Our results demonstrate how AI can be used to augment existing educational environments to support the “teacher in the group”, and to scale up the benefits of group learning to the actual classroom.
UR - http://www.scopus.com/inward/record.url?scp=85022199067&partnerID=8YFLogxK
U2 - 10.1007/978-3-319-61425-0_6
DO - 10.1007/978-3-319-61425-0_6
M3 - Conference contribution
AN - SCOPUS:85022199067
SN - 9783319614243
T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
SP - 64
EP - 76
BT - Artificial Intelligence in Education - 18th International Conference, AIED 2017, Proceedings
A2 - Andre, Elisabeth
A2 - Hu, Xiangen
A2 - Rodrigo, Ma. Mercedes T.
A2 - du Boulay, Benedict
A2 - Baker, Ryan
PB - Springer Verlag
Y2 - 28 June 2017 through 1 July 2017
ER -