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題名:人工智慧的教育應用模式與潛力
書刊名:教育研究月刊
作者:黃國禎付慶科
作者(外文):Hwang, Gwo-jenFu, Qing-ke
出版日期:2019
卷期:307
頁次:頁48-65
主題關鍵詞:人工智慧的教育應用個人化學習智慧學習環境數據分析適性化學習Artificial intelligence in educationPersonalized learningSmart learning environmentsLearning analyticsAdaptive learning
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當前飛速發展的科學技術正在深刻影響和改變著我們的世界,試圖讓人們的生活更加便利。而人工智慧技術成熟,更使得人工智慧在教育的應用(Artificial Intelligence in Education, AIED)及智慧學習環境的議題受到廣泛的重視。透過人工智慧的技術,學者們嘗試提供個人化、適性化的學習指導與回饋,讓學習更有效果及效率。本研究透過文獻分析,發現在過去數十年來,在這方面的相關研究不斷地隨著電腦及人工智慧技術的普及有快速增加的趨勢;同時,應用領域主要集中在計算機科學、工程學、數學和社會科學等。另外,在近幾年,結合了行動科技及數據分析等新興技術的相關研究也愈來愈多。最後,本研究基於文獻分析的結果,提出人工智慧在教育應用的模式,以及未來的研究建議,包括將學習者的自我評估納入產生個人化學習指引的決策過程,以及探討人工智慧技術應用在不同教學情境中的有效策略及應用效果等議題。
Nowadays the rapid development of modern technologies has been influencing and changing our society, trying to make our lives more convenient and intelligent. Smart learning environments (SLEs) are such kind of efforts to offer learners personalized learning effectively and efficiently. In the past half century, a steady development on the literature on smart learning environment was identified. Moreover, it was found that most of studies has been conducted in the fields of computer science, engineering, mathematics, and social science. In the meantime, several technological components of SLEs were identified as follows: overall, dynamic and open models of learners, mobile technologies and innovative technologies, intelligent cloud service, educational big data and learning analytics; And some salient pedagogical affordances of SLEs were also presented, such as personalized learning contents and paths, cognitive guiding, developing high-order abilities, facilitating diverse learning modes, and fostering autonomous learning and lifelong learning abilities. At last, several future developmental trends or suggestions are proposed, such as taking learners’ self-assessments into consideration of decision-making on personalized guiding, investigating the effects of the mixed learning modes on different teaching contexts, and so on.
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