An Intelligent Assessment Mechanism for Online Short Text
Chenn‐Jung Huang, Shun-Chih Chang, Heng-Ming Chen, Sheng-Yuan Chien · International Journal of Automation and Control Engineering · 2015
In this work, an intelligent online short text assessment mechanism that detects whether the learners address the expected discussion issues is proposed. The concept maps related to the learning topics are first outlined by the instructor. After each learner issues a short text post on the online discussion platform, a feature selection approach is adopted to derive the input parameters of a Support Vector Machines (SVMs) classifier. The classifier then determines if the learners’ posts are related to the concept maps previously outlined by the instructor. Notably, a feedback rule construction mechanism is used to issue feedback messages to learners in cases where the online short text assessment mechanism detects that the learners have strayed astray from the expected learning topics in their posts. The experimental results revealed that the proposed approach achieved very good classification results and verified its effectiveness.