Investigating teacher orchestration load in scripted CSCL
A multimodal data analysis perspective
Bibliographic Data
| ID | 21297847 |
|---|---|
| Authors | Lubna Hakami (0000-0002-7370-8072, Department of Information and Communication Technologies Universitat Pompeu Fabra (UPF) Barcelona Spain, corresponding author), Davinia Hernandez-Leo (0000-0003-0548-7455, Department of Information and Communication Technologies Universitat Pompeu Fabra (UPF) Barcelona Spain), Ishari Amarasinghe (0000-0003-2960-4804, Department of Information and Communication Technologies Universitat Pompeu Fabra (UPF) Barcelona Spain), Batuhan Sayis (0000-0002-8802-9945, Department of Information and Communication Technologies Universitat Pompeu Fabra (UPF) Barcelona Spain) |
| Language | EN |
| References cited | 27 |
Despite the growing interest in using multimodal data to analyse students' actions in Computers‐Supported Collaborative Learning (CSCL) settings, studying teacher's orchestration load in such settings remains overlooked. The notion of classroom orchestration, and orchestration load, offer a lens to study the implications of increasingly complex technology‐supported learning environments on teacher performance. A combination of multimodal data may aid in understanding teachers' orchestration actions and, as a result, gain insights regarding the orchestration load teachers perceive in scripted CSCL situations. Studying teacher orchestration load in CSCL helps understand the workload teachers experience while facilitating student collaboration and assists in informing design decisions for teacher supporting tools. In this paper, we collect and analyse data from different modalities (i.e. electrodermal activity, observation notes, log data, dashboard screen recordings and responses to self‐reported questionnaires) to study teachers' orchestration load in scripted CSCL. A tool called PyramidApp was used to deploy CSCL activities and a teacher‐facing dashboard was used to facilitate teachers in managing collaboration in real time. The findings of the study show the potential of multimodal data analysis in investigating and estimating the orchestration load experienced by teachers in scripted CSCL activities. Study findings further demonstrate factors emerging from multimodal data such as task type, activity duration, and number of students influenced teachers' orchestration load
Art · Orchestration · Perspective (graphical) · Artificial Intelligence · Computer Science · Educational Tools and Methods · Innovative Teaching and Learning Methods · Model-Driven Software Engineering Techniques · Psychology
| Highly cited | No |
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