Feedback and Analysis from Assessment Metadata in E-Learning

نویسندگان

  • Ching-Tang Hsieh
  • Timothy K. Shih
  • Wen-Chih Chang
  • Wen-Chieh Ko
چکیده

With fast development in e-learning, assessment plays an important role between teaching and learning. A good e-learning system is not only with good teaching strategy and better learning resources but also proper assessment model. In this paper, we proposed an assessment meta-data and assessment analysis feedback for recently e-learning environments. There are several proper feedback for teachers, students, and learning management systems. The feedback could provide proper teaching, learning resource delivering and learning progress suggestions. With the approach, assessment prompts the learning effort in e -learning. Keyword: cognition level, Item Discrimination Index, Item Difficulty Index, questionnaire, Assessment Analysis Model

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تاریخ انتشار 2003