Investigating collaborative problem solving temporal dynamics using interactions within a digital whiteboard

• Main Author: FWA, Hua Leong
• Format: text
• Language: English
• Published: Institutional Knowledge at Singapore Management University 2023
• Subjects: collaborative problem solving; unsupervised; machine learning; temporal; digital whiteboard; education datamining; Databases and Information Systems; Instructional Media Design
• Online Access: https://ink.library.smu.edu.sg/sis_research/7821; https://ink.library.smu.edu.sg/context/sis_research/article/8824/viewcontent/iwb_mining.pdf
• Institution: Singapore Management University

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.