Title page for etd-0118112-120714


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URN etd-0118112-120714
Author Hsiu-Fen Lin
Author's Email Address No Public.
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Department Information Management
Year 2011
Semester 1
Degree Master
Type of Document
Language zh-TW.Big5 Chinese
Title Design and implementation of a mobile application for personal learning analytics
Date of Defense 2012-01-07
Page Count 103
Keyword
  • Prototyping Implementation
  • Personalized Mobile Learning Analytics System
  • Learning Analytics
  • Mobile Learning
  • Abstract Learning analytics focuses on using existing accumulated learning data through analysis related techniques to provide appropriate information to learners and facilitating learners to adjust their learning strategies (personalization and adaptation) in improving learning effectiveness. Through learning analytics, activities of teaching, learning, and management processes will be significantly changed. Although learning analytics has been considered one of the six critical trends (ebook, mobile learning, augmented reality, game-based learning, natural user interface, and learning analytics) of high education in the near future, there are only few studies focusing on exploring learning analytics related issues. To address this void, this thesis aims for analyzing and designing a personalized mobile learning analytics system that is a mobile application prototyping system developed by incorporating concepts of learning analytics and mobile learning. User requirements of the prototyping system are collected by database analysis (LMS platform), focus groups (users of mobile learning), and expert interviews (experts and practitioners in e-learning domain). Those collected requirements have been translated into system functionalities and then they have been appropriately implemented through adequate system development tools. Finally, the implemented prototyping system has been tested and validated by experts and practitioners in e-learning domain. Therefore, this study has significant contributions on conducting an in-depth system analysis and design relating to mobile learning with learning analytics and validating the feasibility of learning analytics by the prototyping approach. We suggest that academics and practitioners can conduct more in-depth research on investigating learning analytics related issues based on the findings of this study.
    Advisory Committee
  • Pei-Chen Sun - chair
  • Chia-Ju Liu - co-chair
  • Kuo-Jen Chao - co-chair
  • Wu-Yuin Hwang - co-chair
  • Nian-Shing Chen - advisor
  • Files
  • etd-0118112-120714.pdf
  • indicate access worldwide
    Date of Submission 2012-01-18

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