Publication Type

Conference Proceeding Article

Version

acceptedVersion

Publication Date

4-2023

Abstract

Collaborative Problem Solving, the resolution of complex problems with the collaboration of multiple peoplepooling their knowledge, skills and effort is postulated as an essential 21st century skills for the futureworkforce. Collaborative Problem Solving has been embraced in schools where both online and face-to-face collaboration are afforded through the proliferation of educational technology tools. Assessing the amount of collaboration that has taken place among the students has however been challenging. In this research, we seek to identify the collaboration patterns of our students by mining the temporal sequence of their actions logs captured within a digital whiteboard tool. With the use of Hidden Markov Model, we have uncovered three collaboration states of students (Low Activity, Solitary Contributor, Cognitive Collaboration) from the temporal sequences of their actions within the digital whiteboard. Contrary to common belief, the level of collaboration was also found to have no influence on the quality of the final artifact produced by a student team. Collaborative behaviour was also discovered to persist within the team which suggests opportunities for implementing interventions at an early phase of the learning activity for a longer-lasting team collaboration.

Keywords

collaborative problem solving, unsupervised, machine learning, temporal, digital whiteboard, education datamining

Discipline

Databases and Information Systems | Instructional Media Design

Research Areas

Data Science and Engineering

Publication

Proceedings of the 15th International Conference on Computer Supported Education, Lisbon, Portugal, 2023 April 21-23

First Page

363

Last Page

373

ISBN

9789897586415

Identifier

10.5220/0012011500003470

Publisher

CSEDU

City or Country

Lisbon, Portugal

Additional URL

https://doi.org/10.5220/0012011500003470

Download

Share

COinS