Using Particle Swarm Optimization Approach for Student Engagement Measurement

ming liu

Abstract


Measuring Student Engagement is a difficult task. Previous research has used a cloud-based writing platform, Google Doc, which can store a number of document revisions with timestamps. Engagement measurement algorithm has taken the advantages of each timestamp in a revision and calculated how much time the student spent on a writing task. However, the parameters passed to the algorithm were fixed and hard to determine, for example, how much time means fully engaged or partially engaged. In this paper, we proposed a new student engagement measurement algorithm based on a computational intelligence approach, Particle Swarm Optimization technique, to find the optimized parameters for the engagement measurement algorithm. In the study, the proposed algorithm measures the engagement of two group of students in two different writing activities (long-term and short term writing activities) carried out in our cloud-based writing platform. The study results show that the correlations between the engagement measurement and student self-report are high. In addition, it indicates that this approach is robust to measure student engagement in both long-term and short term activities.


Keywords


Student Engagement Measurement, Writing, Innovative Methodologies in Learning

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References


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