Validation of Learning Effort Algorithm for Real-Time Non-Interfering Based Diagnostic Technique

The objective of this research is to validate the algorithm of learning effort which is an indicator of a new real-time and non-interfering based diagnostic technique. IC3 Mentor, the adaptive e-learning platform fulfilling the requirements of intelligent tutor system, was applied to 165 university students. The learning records of the subjects who attended IC3 Mentor were converted into Characteristic Learning Effort (CLE) curves through the algorithms of learning effort. By evaluating CLE curves and questionnaire survey reports, the findings indicate that the learning effort algorithm is verified to be an effective real-time and non-interfering diagnostic technique. Furthermore, CLE curve is proven to be an effective user-friendly tool for learners and instructors in diagnosing learning progress under adaptive e-learning context. The CLE curve generated by the algorithm of learning effort is a visualized graphic tool which can be applied in the adaptive e-learning platform of education and industry fields.