| 研究生: |
李思佳 Szu-chia Li |
|---|---|
| 論文名稱: |
探討大學生使用數位學習系統持續使用意圖之研究- An Investigation of Undergraduates Students'' Continuance Behavioral Intentions to Use e-Learning System - An Integration of Post-Acceptance Model, Unified Theory of Acceptance Use of Technology(UTAUT), and Success Model of Information |
| 指導教授: |
李憶萱
Yi-hsuan Lee |
| 口試委員: | |
| 學位類別: |
碩士 Master |
| 系所名稱: |
管理學院 - 企業管理學系 Department of Business Administration |
| 畢業學年度: | 98 |
| 語文別: | 中文 |
| 論文頁數: | 183 |
| 中文關鍵詞: | 接受後資訊系統持續使用模式 、數位學習 、資訊成功模型 、整合性科技接受理論 、自律特質 、系統持續使用意圖 |
| 外文關鍵詞: | E-learning, Post-Acceptance Model, Trait Self-Regulation, Uunified Theory of Acceptance and Use of Technol, Success Model of Information, System Continuance Intention, Expectancy-Disconfirmation Theory |
| 相關次數: | 點閱:15 下載:0 |
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進入知識經濟的時代下,人力資源將成為各國累積實力的重要資產,因此將教育資源有效運用、提供更有效率的學習空間及培養學生自我持續學習之能力,成為高等教育領域中必須正視的課題。
數位學習提供了彈性自主的學習空間,並整合廣泛多元的知識內涵,讓學習者可以在更自主性的環境下,透過數位內容的傳輸,持續培養個人之能力。藉由了解數位學習使用者對於系統的認知及探討影響數位學習使用者持續使用意願之因素,將使數位學習方式更符合學生需求,以促進學習成效及動機,進而培養持續學習的動力。
本研究以高等教育學生對於數位學習系統的持續使用意圖為主題,以接受後資訊使用模式為理論架構,並細分資訊成功模型中「系統」、「資訊」及「服務」三種品質概念,並加入「自律特質」及整合性科技接受模型中「社會影響」與「有利條件」等因素。
本研究對象為某大學曾經使用該校數位學習系統的學生,有效樣本數為616份,以SPSS17.0與AMOS 16.0進行個人資料的描述性分析、信度與效度分析,及結構方程模式(SEM)分析研究架構的路徑因果關係及解釋力,研究結果如下:
一、「系統品質期望不確認」、「資訊品質期望不確認」會透過數位學習系統的「認知有用性」、「滿意度」,正向影響使用者的「持續使用意圖」。
二、「服務品質期望不確認」則僅透過「滿意度」,正向影響使用者的「持續使用意圖」。
三、個人因素中「自律特質」透過數位學習系統的「認知有用性」,正向影響使用者的「滿意度」與「持續使用意圖」
四、「社會影響」、「有利條件」會正向影響使用者的「持續使用意圖」
Into the age of knowledge economy, human resources will become an important national asset accumulation of power.Therefore, the higher education institutions must pay attention to the issue of the effective use of the educational resources , and provide more efficient space for students to accumulate their learning ability in order to achieve self-sustained learning.
E-Learning provides a flexible space for self-learning and integrates a wide range and diversity of knowledge contents.Through the transmission of digital content, it help leaners studing autonomy and cultivating their personal ability continuously. By understanding the E-learning users’ cognition system and exploring the key factors that affect the users’ continuance intentions to use the E-learning system, it will allow the design of E-learning meet the users’ needs, enhence the effectiveness of learning, and motivate the users’ continued learning.
The purpose of this study is to investigate the higher education students’ behavior of continuance intentions to use the E-learning system. This study combined the unified theory of Post-Acceptance Model and IS success model which include system quality, information quality and service quality. Additionally, this research model integrates trait self-regation of Personal characteristics, social influence and facilitating conditions of unified theory of acceptance and use of technology (UTAUT) to propose a new hybrid model to study students’ behavior of continuance intentions to use the e-learning system.
The participants of this study were the 616 students in a university which have adopted the e-learning systems. The statistical software of SPSS17.0 and Amos16.0 were used to analyze the descriptive statistics of demographic information, reliability and validity. Besides, the structural equation modeling (SEM) was conducted to identify the causal effect among the factors. The results of this study were summarized as follows:
1.The system quality disconfirmation and the information quality disconfirmation had significant influence on the the continuance intention of the E-learning user through the perceived usefulness and the satisfaction.
2.The service quality disconfirmation had significant influence on the continuance intention of the E-learning user through the satisfaction.
3.The trait self-regation of Personal characteristics had significant influence on continuance intention and the satisfaction of the E-learning user through perceived usefulness
4.The social influence and facilitating conditions of UTAUT had significant influence on the the continuance intention of the E-learning user.
By explaining the key factors that affected students’ behavioral continuance intentions, the findings of this research help to develop more user-friendly e-learning systems and also provide insight into best way to promote e-learning systems for students in higher education institutions.
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