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Participation at ICALT 2022
TIDE will be participating at the 22nd IEEE International Conference on Advanced Learning Technologies (ICALT 2022), with the contributions:
Crespi, F., Amarasinghe, I., Vujovic, M., & Hernandez-Leo, D., (2022). Estimating Orchestration Load in CSCL Situations Using EDA, 22nd International Conference on Advanced Learning Technologies, to appear
Abstract: This study investigates to what extent Electroder- mal Activity (EDA) sensor data can be triangulated with self-perception measures to estimate facets of teachers’ orchestration load in the context of Computer-Supported Collaborative Learning (CSCL). It was expected to observe variances in the EDA signal as a result of stressful moments and incidents related to orchestration. Study findings indicated that EDA variations concurred with situations in which the teacher reported feeling stressed when orchestrating CSCL Pyramid scripts.
Dieckmann, M., Hernández-Leo, D., & Amarasinghe I., Flagging in teacher-facing orchestration dashboards: factors affecting its use in Pyramid CSCL debriefing, 22nd International Conference on Advanced Learning Technologies, to appear
Abstract—Teacher-led debriefing has the potential to positively affect learning gains when conducted at the end of collaborative learning activities. In order for debriefing to be effective, the teacher needs to base it on the learner’s process during the activity. Research in the field of Computer-Supported Collaborative Learning (CSCL) is proposing teaching-facing dashboards as tools that facilitate the monitoring and orchestration of activities. However, research has paid less attention to how these dashboards can support debriefing. We explore how adding a “flagging” feature to a CSCL orchestration dashboard can support debriefing by reporting a qualitative preliminary study in which the flagging feature was used during a Pyramid CSCL script activity. Results indicate that the dashboard interface design, number of student responses, number of errors in student responses, and whether student responses meet the teachers expectations most influence the use and utility of the feature. Additionally, we identified avenues for improving and extending the design of the feature.