Two studies on educational technology

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This study analyzed opinions of students on different learning methods like face-to-face, e-learning and b-learning using a questionnaire. The questionnaire was divided into two parts collecting student demographics and open-ended responses on their views. Responses were analyzed using ATLAS.ti software to code and organize data. A second study focused on introducing multimedia software in public education to improve learning efficiency without extensive training. The purpose was to identify education trends and develop an effective way to apply multimedia supporting various subjects and allowing foreign language learning through comprehension over grammar.

Education Technology

Done by: Maryam Al-Balushi. Narjis Al-Hinai.

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Authors: • Jeong Shick Yoon Professor of Industrial Design, Korean University of Technology and Education • Dosung Chung Professor of Industrial Design, Kookmin University STUDY TWO A Study on Multimedia Learning in the Public Education System

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Educational data mining (EDM) is one of the applications of data mining. In educational data mining, there are two key domains, i.e. student domain and faculty domain. Different type of research work has been done in both domains. In existing system the faculty performance has calculated on the basis of two parameters i.e. Student feedback and the result of student in that subject. In existing system we define two approaches one is multiple classifier approach and the other is a single classifier approach and comparing them, for relative evaluation of faculty performance using data mining Techniques. In multiple classifier approach K-nearest neighbor (KNN) is used in first step and Rule based classification is used in the second step of classification while in single classifier approach only KNN is used in both steps of classification. But in proposed system, I will analyse the faculty performance using 4 parameters i.e., student complaint about faculty, Student review feedback for faculty, students feedback, and students result etc. For this proposed system I will be going to use opinion mining technique for analyzing performance of faculty and calculating score of each faculty.

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