在教育部推動臺灣大專院校人工智慧學程聯盟（TAICA）之背景下 GPU 雲端算力平台已成為 AI 實作教學之關鍵基礎設施，惟其使用者體驗尚缺乏系統性之實證研究。本研究以 TAICA 聯盟部署之Glows.AI 平台為場域，整合「整合性科技接受與使用理論」（UTAUT2）、資訊系統成功模型與知覺價值理論 建構 以使用者滿意度與知覺價值為雙中介之研究模型，共提出 17 項 研究假設。
研究採探索性序列混合方法：先對課程助教與修課學生進行質性深度訪談（共3 位）， 以檢視構面內容效度並修訂後續問卷研究工具；再對修課學生施測問卷回收有效樣本 108 份，以 PLS-SEM 進行檢驗。結果顯示：17 項假設中 9 項獲得支持；使用者滿意度主要由系統品質、績效期望與習慣驅動，知覺價值由社會影響驅動；雙中介對持續使用意圖與推薦意圖之 四條路徑均達顯著 ，持續使用意圖並正向影響實際使用行為；年級正向調節績效期望對滿意度之效果：年級越高，績效期望對滿意度的影響越大 。質性與量化發現初步呼應 ：使用者對平台之態度主要源於親身體驗，社會訊號則作為價值評估之參考資訊。
本研究之貢獻有三：其一，為使用者滿意度與知覺價值之雙中介機制，提供新興教育算力平台情境之實證證據；其二，於制度化採用情境中辨識社會影響之雙軌作用型態，深化對強制與自願混合情境下社會影響機制之理解；其三，就系統品質投資、帳號支援流程、點數配額與計費體驗、分眾行銷等面向，對 KONST 提出具體可行之營運建議。

Under the Taiwan AI College Alliance (TAICA) initiative, GPU cloud computing platforms have become key infrastructure for hands-on AI education, yet systematic evidence on their user experience remains scarce. Focusing on the Glows.AI platform deployed under TAICA, this study integrates UTAUT2, the IS Success Model, and perceived value theory to construct a dual-mediation model in which user satisfaction and perceived value transmit the effects of the antecedents, and proposes seventeen hypotheses.
An exploratory sequential mixed-methods design was adopted: qualitative interviews with one teaching assistant and two students were conducted first to preliminarily examine construct relevance and refine the survey instrument, followed by a questionnaire survey yielding 108 valid responses analyzed with PLS-SEM. Nine of the seventeen hypotheses were supported. User satisfaction was driven by system quality, performance expectancy, and habit, whereas perceived value was driven by social influence; all four paths from the dual mediators to continuance intention and recommendation intention were significant, and continuance intention positively predicted actual use behavior. Academic stage moderated the effect of performance expectancy on satisfaction, such that the effect was stronger for more senior students. Qualitative and quantitative findings showed preliminary convergence: user attitudes stemmed mainly from first-hand experience, while social cues served as reference information for value assessment.
This study makes three contributions. First, it provides empirical evidence for the dual-mediation mechanism of user satisfaction and perceived value in the emerging context of educational GPU computing platforms. Second, it identifies a dual-track pattern of social influence in institutionalized adoption contexts—interpersonal influence did not affect satisfaction, whereas social cues informed value assessment—deepening the understanding of mixed mandatory–voluntary settings. Third, it offers actionable recommendations for KONST regarding system quality investment, account support processes, credit allocation and billing experience, and segmented marketing.

臺灣大專院校人工智慧學程聯盟（2025）. TAICA計畫緣起 Origin of the Project. https://taicatw.net/
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