Visually Enhanced E-learning Environments Using Deep Cross-Medium Matching
Publish Year: 1397
نوع سند: مقاله کنفرانسی
زبان: English
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شناسه ملی سند علمی:
ICELEARNING13_019
تاریخ نمایه سازی: 20 خرداد 1398
Abstract:
In the past few years, e-learning solutions are gradually replacing the traditional learning environments. The short attention span and lack of focus in many students is one of the factors which requires attention of e-learning course designers. Visually enhanced and dynamic e-learning courses proved to be more effective in keeping the attention of the students. In this paper, a framework for designing visually enhanced e-learning environments using deep cross-medium matching is proposed. The proposed framework uses deep neural networks for matching the textual and visual information together in order to suggest dynamic visual content for the textual e-learning materials. The proposed framework can improve the learning experience of students by providing dynamic visually enhanced e-learning environment.
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Authors
Mozhdeh Dokhani
Department of Computer Engineering Khatam University Tehran, Iran
Babak Majidi
Department of Computer Engineering Khatam University Tehran, Iran
Ali Movaghar
Department of Computer Engineering Sharif University of Technology Tehran, Iran