Building a Virtual Experiment Diagnosis Scheme to Automatically Analyze Operational Portfolio in Natural Science

Abstract

Virtual Experiment (VE) plays an important role for fostering the student's high-level thinking and problem-solving abilities. Accordingly, VE has become the popular method to assist teachers in science teaching and students in practicing due to the time-consuming and labor-intensive of the Real Experiment (RE). However, the teaching and learning performance may be limited because the most of the existing VE systems cannot efficiently, automatically analyze and diagnose the students' VE operational portfolio. Therefore, this study proposes a Virtual Experiment Diagnosis Scheme (VEDS) to automatically diagnose the operational portfolio based on teacher-defined diagnostic knowledge and further to offer students the Visualized Personalized Diagnostic Report to describe the learning problems with suggestion for fostering the self-learning and experiment abilities.