Analyzing the Effects of Cloud Educational Technology on the Learning Experience
| Autor: | Yu-Hsin Hung, 洪鈺欣 |
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| Rok vydání: | 2017 |
| Druh dokumentu: | 學位論文 ; thesis |
| Popis: | 106 With the rapid development of educational technology, the new type of digital instructional material been widely applied in various learning management systems (LMS). Personalized learning, gamification, educational data mining, Internet of thing (IoT) and massive open online courses (MOOCs) are the popular cases of innovation in the education. E-learning takes advantage of the interactive abilities of the online digital media to enhance students’ learning efficiency. It is critical to consider that educational technology can be designed with various types of instructional materials, and learning performance is improved depends on the kind of instructional materials provided to the learner. Personalized learning has received considerable attention, considering the learning styles when developing adaptive educational systems. In this study, we develop the various educational technologies in the different learning activity such as animation, the interactive game, and IoT solution. For ensuring the quality of learning activity, the usability of educational technology evaluation is needed. The proposed system and the existing educational technology were included in this study to evaluate system performance. Personalized learning has recently become a popular trend in e-learning. The cloud-based learning profile can be retrieved and maintained automatically based on the framework of information and communication technology (ICT) when learners interact with the LMS. This study also applied the data mining techniques in the learning profile to investigate the relationship between personal trait and learning experience, user’s perception. The findings of this study demonstrate the relationship between tool, human behavior, and data. First, this study integrates game-based learning and personalized learning into a problem-solving activity and computer science education to maximize learner motivation and learning effects. Second, we explore the personal traits and learning preference on using the proposed system and the popular educational technology. Finally, the query-based classification was used to personalize the learning material. |
| Databáze: | Networked Digital Library of Theses & Dissertations |
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