Integration of Multiple Data Sources for predicting the Engagement of Students in Practical Activities
This work presents the integration of an automatic assessment system for virtual/remote laboratories and the institutional Learning Management System (LMS), in order to analyze the students’ progress and their collaborative learning in virtual/remote laboratories. As a result of this integration, it is feasible to extract useful information for the characterization of the students’ learning process and detecting the students’ engagement with the practical activities of our subjects. From this integration, a dashboard has been created to graphically present to lecturers the analyzed results. Thanks to this, faculty can use the analyzed information in order to guide the learning/teaching process of each student. As an example, a subject focused on the configuration of network services has been chosen to implement our proposal.
|Year of Publication||
International Journal of Interactive Multimedia and Artificial Intelligence
Special Issue on Multisensor User Tracking and Analytics to Improve Education and other Application Fields
|Number of Pages||