電子化政府網站的學習

Abstract

電子化政府網站的學習 本研究包括兩個部份。第一部份探討如何改進電子化政府網站，以利學習；第二部 份探討那些因素，會影響使用者上電子化政府網站學習。 第一部份從學習者觀點探討電子化政府網站的改進 本研究首先發展一個分析架構，將電子化政府網站的特性和學習者知識的取得，用 一矩陣表示。本研究將訪問有興趣在電子化政府網站上學習的人，首先要求受訪者進入 某個政府網站，並學習一個自己感興趣的主題，然後回答問卷。事後並將舉辦焦點討論， 以更進一步瞭解使用者的想法。分析方法將採用grounded theory。此研究領先從學習 者的角度，探討電子化政府網站。 第二部份影響在電子化政府網站上學習的因素 本研究探討科技接受模式(TAM)，是否可以用來解釋和預測在電子化政府網站上學 習的意願。本研究將採便利抽樣，利用問卷搜集資料，並利用結構方程式方法分析資 料。此模式將可找出影響在電子化政府網站上學習的前因，有助於在電子化政府網站 上學習的推廣。

E-governmentWebsite for Learning This study consists of two parts. The first part explores the opportunities for enhancing e-government website for learning. The second part investigates the antecedents of intention of learning from e-government websites. Part I E-government website enhancement opportunities –A learning perspective This study develops a framework of analysis that categorizes features of e-government website design in a matrix of knowledge-acquiring process versus learners’ values.The proposed framework supports a development plan for a cyber governmental website that may involve all aspects of a learning process. A framework for analysis is first proposed. Data will be obtained from respondents who may be interested in learning from e-government websites. Participants will be requested to enter a website to learn a subject. The instruments used for obtaining their opinions are open-ended questionnaires. Focus group interviews will also be conducted. An iterative analyzing strategy based on grounded theory will be employed to obtain the results. Analytical results of the data based on the framework should reveal many insights. This study will be the first to examine an e-government website from a learner perspective. Furthermore, this investigation will present a framework that facilitates analyzing and improving e-government websites. Part II Elucidating Intention of E-Government Learning: a Perspective of the Extended Technology Acceptance Model This work proposes and verifies that the technology acceptance model (TAM) can be employed to explain and predict the acceptance of learning from e-government. The study will identify factors that account for individual differences to enhance the explanatory power of the model. A survey will be conducted to collect data. Most of the constructs in the model will be measured using existing scales, while some measurement items were created specifically for this research. Structural equation modeling will be employed to examine the fit of the data with the model by using the LISREL software. There is scant research available in the literature on user acceptance of e-government from learning perspective. The present research will find out antecedents of user acceptance of e-government learning. The model will enhance our understanding of consumer motivation of e-government learning. This understanding can aid our efforts when promoting e-government learning.