Open Source Physics learning analytics of on-line simulations.

ORAL

Abstract

A large number of the educational simulations in the Open Source Physics digital library were created with the Easy JavaScript Simulation (EJS) authoring tool and are suitable for inclusion on online courses for supervised or unsupervised student learning. We describe the current and planned features of EJS that allow teachers to collect data from students' interactions with our simulations in a customizable, instructional-aware format, so that teachers can automatically obtain valuable pedagogic information by applying either Learning Analytics or Educational Data Mining techniques to these data. Simulations created with EJS can be embedded in popular leaning management systems via a plugin that serves the simulation and collects the interaction data desired by the teacher. The data can then be mined to elicit information on the student's behavior, performance, or learning strategies to help teachers improve their materials, detect disconnection of the student with the course, predict potential failure and provide timely assistance. We describe the current state of our development and architecture and describe future directions for our work and our plans to use these features for research in physics students' on-line learning.

Authors

  • Francisco Esquembre

    Universidad de Murcia, Spain

  • Felix Jesus Garcia-Clemente

    Universidad de Murcia, Spain

  • Rafael Chicon

    Universidad de Murcia, Spain

  • Lawrence Wee

    Ministry of Education, Singapore

  • Leon Tze Kwang

    Ministry of Education, Singapore

  • Darren Tan

    Ministry of Education, Singapore