近年來，世界各國正掀起一波創客教育的浪潮，我國政府也積極的在推動創客運動，而「創客教育」隨即在各級學校不斷落實及實踐，甚至已擁有屬於自己的創客基地或創客空間，然歸因於創客教育具有跨學科、領域性，目前還沒有專職的創客教師，因而在創客教育中恐衍伸出一些教學挑戰；其一是恐因過於複雜且多元的創客任務，而造成學生無法理解或完成創客任務的內容與步驟，亦或者是無法自行操作創客工具的使用方法等，導致學習成效不彰的情形；其二則是學生在面臨實作問題的處理方式，便是立即尋求教師的協助，這恐由於頻繁地依賴教師而導致缺乏問題解決能力，進而衍伸出師資不足的現象。
因資訊科技的快速進步，智慧教育機器人技術和深度學習技術已逐漸成熟，本研究試圖改善教學現場師資不足的問題，即開發了一套教育機器人系統，稱為創客教育虛擬互動機器人；並嘗試經由創客教育虛擬互動機器人導入創客活動中，探討學習者的學習成效、任務理解、任務完成度的影響，以及學生自我效能與參與度是否皆有明顯的提升。為此，本研究以“Micro:bit自走車”作為創客活動主題，並招募自願參加實驗之國小五、六年級生，共25人。在創客活動中導入本研究所開發的虛擬互動機器人來輔助學生從事各項任務，在此會記錄學生們的使用機器人的行為與相關歷程作為後續分析使用；同時，本研究還蒐集各小組討論互動過程，試圖從語音情緒辨識系來來獲知小組討論之氣氛。從研究結果顯示，發現機器人對學習者的學習成效、任務理解、任務完成度、自我效能與參與度皆有所提升及改善，尤其對低成就之學生較為明顯；情緒辨識系統則由於語言文化的不同所產生之差異，導致辨識率偏低現象，而此語言差異的結果可作為未研究參考與改善之依據。

Recently, the Maker Education has been continuously implemented in schools, and even has its own maker space in Taiwan. Because of the interdisciplinary and field nature of maker education, there are currently no full-time maker educators that is face a new challenge. The one is complex of maker tasks cause students to be unable to understand or complete the them, or students don’t know how to use maker tools resulting in ineffective learning; the other is students immediately seek the assistance of teachers when they are face problem, which will lead the phenomenon of insufficient teachers.
This study aims to improve the problem of insufficient teachers by developing a Maker-based Virtual Agent Robotic. Introduce the virtual agent robotic into maker activities to explore the impact of learners' learning performance, task understanding, task completion, self-efficacy and students' engagement have been significantly improved. Therefore, the theme of the the maker activity in this study is "Micro:bit obstacles avoidance car", and invited 25 students in the fifth and sixth grades of elementary schools who volunteer to participate in this experiment. The virtual agent robotic is used to assist students in various maker tasks, meanwhile, students’ behavior and learning processes of using the robot will be recorded for analysis. Moreover, this robotic also collects group discussions during the interactive process, it tries to analysis students' emotion of discussion through the speech emotion recognition system. According to the results, this finding found that robotic has improved learners’ engaging in maker, especially for low-achievement students.

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