從電子商務以迄進入數位時代，人們的生活行為開始產生劇烈的改變，間接影響了生活型態的改變。因此，自2000年以來，許多研究分析了數位生活型態的行為和傳統的人口統計或傳統生活形態。在數位化時代，數位生活型態和線上學習的各種創新已經日益擴大。然而，關於數位行為分析及數位生活型態內涵的探討課題，仍有其潛在的需求缺口存在。
為了填補上述研究的潛在缺口，本文透過用數位生活型態的方式對線上學習使用者進行了分析和分類。本研究利用網路問卷調查共收集了992份問卷，以獲取有關線上學習使用行為的相關資訊，並發現數位型態生活方式的測量結果，比人口統計學或傳統生活方式的測量更有效。在數位生活型態測量的四個因素的基礎上，確定了五個集群。五個群集是黏著客戶群，預警客戶群，淺嘗即止客戶群，潛潛力客戶群和消極客戶群。本文提出了研究結果，並提出了對於政府如何以及學習內容的服務業者，如何對線上學習行為做出相關的建議。
People have changed their behavior patterns and lifestyles dramatically as the digital era has dawned. As a consequence, since the year 2000, relevant studies have analyzed the behaviors of digital lifestyles, rather prevalent demographics or traditional lifestyles. In the digital era, the diverse innovations of digital media and online learning have broad-ened. However, little academic research has been published regarding digital media and online learning, even though they are vital in practice.
To fill the aforementioned research gap, this thesis analyzes and categorizes online learners based on digital lifestyle measurements. This work analyzed 992 questionnaires from the web for information regarding online learning behaviors, and discovered that measurements of digital lifestyle were more effective than are measurements of de-mographics or traditional lifestyle. On the basis of four factors of digital lifestyle measures, five clusters were identified. The five clusters are heavy online learners, per-ceived adoption online learners, trail online learners, potential online learners, and pas-sive online learners. This thesis presents findings and proposes implications on how the government and how education players react to the online learning patterns.
