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An adaptive personalized learning system |
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| รหัสดีโอไอ | |
| Creator | 1. Aekavute Sujarae 2. Natchaya Kijmongkolchai 3. Chutiporn Anutariya |
| Title | An adaptive personalized learning system |
| Publisher | Faculty of Engineering, Khon Kaen University |
| Publication Year | 2559 |
| Journal Title | KKU Engineering Journal |
| Journal Vol. | 43 |
| Journal No. | S1 |
| Page no. | 14-17 |
| Keyword | Adaptive personalized learning system, Blended learning, Automatic in-class assessment, Support vector machine (SVM) |
| ISSN | 0125-8273 |
| Abstract | Classroom assessment enables instructors to determine learners' needs, adjust instruction, and provide feedbacks to learners on their learning progress. To be truly effective, assessment should be blended as a part of the teaching sequence in order to verify learners' perception of the exposed context. However, this could be time-consuming and resulting in delay and discontinuity of class lectures; thus, making the practice difficult to carry out, especially for a large class size. This paper presents an adaptive personalized learning system that integrates learning technologies with classroom teaching in order to enable a dynamic response learning environment. With an easy-to-use interface, the system supports instructors in continuous assessment of learner's learning progress and automatic selection of supplementary learning materials to suit individual learners based on their performance in a "feedback loop" fashion. In addition, learners' comments and questions are collected and classified into relevant topic categories using Support Vector Machine (SVM)-based text categorization for further review and lecture improvement. |
