近年來創客教育風靡全球，許多教育工作者都致力於創客教育的研究以提升學習者的未來競爭力，因此如何有效量測學習者的學習表現成為教育研究中一項重要的研究課題；過往的研究指出，學習者在課程中的討論表現與其學習效果有一定的關聯；而在創客教育中常使用學習成績、自我報告等方式來衡量學習者的學習成果，可能會因為學習者的個人主觀意識影響導致量測結果出現偏差，並且無法了解學習者在參與創客活動中討論的主題，而採用觀察法需耗費大量的人力與時間成本。近年來隨著科技的快速發展讓使用學習者的討論數據進行學習者學習成果的量測成為可能。故本研究提出一個使用自然語言處理技術於學習者討論討論記錄分析之方法，本方法使用語音轉文字技術將音檔轉譯為文本檔案以代替傳統逐字稿手續，並透過自然語言處理技術分析討論文本，用以有效識別學習者討論主題，並以此為依據判斷學習者在創客活動中的學習表現。
受新冠肺炎影響本研究以Micro:bit作為創客動手做活動教材，以此設計遠距創客活動，以期探討系統是否適用於遠距創客活動中的討論分析；研究結果顯示學習者的討論和學習成效、參與度與團隊協作有顯著關聯；另一方面，本研究利用創客動手做活動之實作成績及學習單成績作為衡量學習成就之因子，探討討論內容對學習成就的影響，發現在創客動手做活動中，學習者越多地進行針對程式撰寫的討論，其學習成就越高，這也說明了學習者更積極地進行與課程相關的討論會獲得更好的學習表現。。因此，基於本研究的方法可以有效地分析學習者的討論，同時可以透過討論衡量學習者的學習成就。

Influenced by the teaching concept of learning by doing, maker education, which is based on hands-on learning, has gradually been promoted. Countries around the world are actively promoting maker education and related policies to cultivate learners' creativity and innovation ability. However, previous studies have used scales, questionnaires or self-reports to analysis learning performance. This may lead to deviations in the measurement results due to the influence of the learner's personal subjective consciousness. In recent years, with the rapid development of science and computer’s technology, it is possible to use learners' discussion data to measure learners' learning outcomes. This study proposes a method of using natural language processing technology to analyze the discussion records of learners. This method uses speech-to-text technology to translate audio files into text files instead of traditional verbatim procedures, and analyzes the discussion text through natural language processing ,which is used to effectively identify the topics discussed by learners, and based on this to judge the learning performance of learners in maker activities.

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