臺灣博碩士論文加值系統

在本文中，我們提出了基於雲端RPG學習之大數據分析於學習者狀態之應用，根據我們所提出的動態分配演算法，對應於學習者(學生)自身的能力，將他們個別分離成不同的等級。
動態分配演算法主要是考慮學生在使用這套學習系統的答題時間以及答題正確率，將合適的教學方案依學生的學習能力去做匹配。每個設計好的教學模塊可以放入雲平台上的虛擬機裡，而每位學習者的學習資訊也將會放在雲平台的資料庫裡。
此外，因為學習系統是建立在虛擬機裡，所以系統維護人員可以方便快速的配置學習系統，也因為整個系統是在雲平台上，不同的遠端設備都可以連線到伺服器上進行學習。

In this thesis, we propose an Individual Learner Big Data Based Cloud Role Player Game Learning Corresponding to Individual Learner Big Data according to the proposed dynamic assigning algorithm to separate individual learner (student) into different levels of learning ability. Based on dynamic assigning algorithm, student’s answering times and answering correct rate for each education scenario in cloud based digital game learning system is considered. Suitable teaching scenario will be provided for individual user corresponding to personal learning ability. Each designed modular teaching materials can be embedded into the game platform on the virtual machine in cloud. In addition, the whole learning system is established as a virtual machine. System maintainer can configure the learning system easily and quickly. Based on cloud, different remote devices can connect to server for learning.

English Abstract......i
Chinese Abstract......ii
Acknowledgements......iii
Table of Contents......iv
List of Tables......v
List of Figures......vi
Chapter 1 Introduction......1
1.1 The Development of modular role player game learning system......3
Chapter 2 Literature Review......6
Chapter 3 Algorithm, Verification and Implementation......8
3.1 Dynamic Assigning Algorithm......8
3.2 System Verification and Implementation......14
Chapter 4 Result......17
Chapter 5 Conclusion......20
Reference......21
Extended Abstract......24
Curriculum Vitae......29

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