以Q方法論探討數位教育政策變遷下民眾對數位學習之信賴類型

An Investigation into Public Trust Typologies in Digital Learning Amid the Evolution of Digital Education Policies: A Study Employing Q Methodology

全球COVID-19疫情，引發全球數位教育轉型，各國政府投入大量資源，推動數位學習政策。然而，民眾對數位學習信任程度，直接影響政策推行成效，信任不足，可能導致政策實施受阻，甚至加劇數位落差。基於此背景，本研究運用Q方法論，探討民眾對數位學習的信任類型與主觀認知模式。本研究採用Q分類程序，收集資料，透過因素分析，識別出四種信任類型：「數位學習積極型」與「｛數位學習謹慎型｝」展現對數位學習的支持態度，認為數位學習能提升學習成效，並促進教育公平；「數位學習觀望型」與「數位學習迴避型」則對數位學習存在疑慮，主要關注資訊安全、學習品質不確定性，與數位認知落差等問題。研究結果顯示，政府推動數位教育政策時，需強化數位學習平台的可近性與安全性，確保系統穩定，並透過教育宣導，提升民眾信任感。針對數位弱勢族群，應提供適應性支持措施，包括設備補助、數位能力培訓與線下輔助，以縮小數位落差，促進數位教育的普及與永續發展。本研究為推動數位教育政策，提供實證基礎，有助於政府，制定更符合民眾需求的數位學習，推動策略，為後疫情時代的教育數位轉型提供重要參考。

The COVID-19 pandemic has expedited the global transition to digital education, prompting significant governmental investment. The effectiveness of such policies hinges on public trust, as its absence may impede implementation and deepen the digital divide. This study applies Q methodology to explore the types of public trust and subjective perceptions related to digital learning. Using Q-sort and factor analysis, this study identified four types of public trust toward digital learning: advocates and cautious supporters who see its benefits for equity and outcomes, and observers and avoiders who are concerned about security, quality, and literacy gaps. The results suggest that governments must enhance system reliability, cybersecurity, and accessibility, while building trust through tailored outreach. Support for digitally disadvantaged groups—like device access, training, and offline help—is key to narrowing the digital divide and ensuring inclusive digital education.