應用運算思維學習診斷機制於STEM實作課程以促進反思學習：準實驗研究

Applying Computational Thinking Learning Diagnostic Mechanisms in STEM Hands-on Courses to Promote Reflective Learning: A Quasi-experimental Study

在當前教育環境中，STEM實作課程以其融合科學，科技，工程與數學教育，對於學生高層次思維能力的培養扮演著重要角色，這些課程旨在提供學生以問題解決為導向的學習經驗，進而促進批判性思考，創造力等高層次思維能力，然而，傳統的STEM實作教學方法在學生學習過程的追蹤與反饋機制方面存在諸多不足，特別是在迅速識別和解決學生在學習過程中遇到的具體問題方面，針對上述問題，本研究提出了一種應用運算思維學習診斷機制於STEM實作課程以促進反思學習的新策略該診斷機制通過分析學生在課程中產生的錯誤資訊，精確地識別學生在運算思維過程中的具體不足，系統會進一步根據分析結果向學生提供個性化的反饋報表，引導學生進行深入的自我反思，從而釐清學習障礙並尋求改進策略透過在K-12階段進行的準實驗設計本研究比較了基於運算思維學習診斷機制的反思學習與傳統依賴學生自我記憶進行反思的差異，研究結果顯示應用運算思維學習診斷機制的方法顯著提高了學生在STEM實作課程中的知識建構效果以及高層次思維技能的發展，學生不僅能夠更加有效地識別和修正學習中的錯誤，同時也展示了更高層次的自我反思能力，從而促進了深度學習與持續的學習動機本研究的發現強調了在STEM實作課程中整合運算思維學習診斷機制的重要性和有效性，為教育實踐提供了新的視角，特別是在提升學生自我反思與高層次思維能力方面的應用潛力。

In the current educational environment, STEM hands-on courses play a crucial role in fostering students’higher-order thinking skills by integrating science, technology, engineering, and mathematics education. These courses aim to provide problem-solving-oriented learning experiences, thereby promoting critical thinking and creativity. However, traditional STEM instructional methods often fall short in tracking and providing feedback during the learning process, particularly in quickly identifying and addressing specific issues students encounter. To address these shortcomings, this study proposes a new strategy that applies a computational thinking (CT) diagnostic mechanism to STEM hands-on courses to promote reflective learning. This diagnostic mechanism accurately identifies specific deficiencies in students’CT processes by analyzing the error information generated during the course. The system further provides personalized feedback reports based on the analysis results, guiding students to conduct in-depth self-reflection to clarify learning obstacles and seek improvement strategies. This study employed a quasi-experimental design to compare reflective learning based on the CT diagnostic mechanism with traditional reflection methods that rely on students’self-recollection. The results indicate that applying the CT diagnostic mechanism significantly enhances students’knowledge construction and the development of higher-order thinking skills in STEM hands-on courses. Students were not only able to more effectively identify and correct learning errors but also demonstrated higher levels of self-reflection, promoting deep learning and sustained motivation. The findings underscore the importance and effectiveness of integrating the CT diagnostic mechanism in STEM hands-on courses, offering a new perspective for educational practice, particularly in enhancing students’self-reflection and higher-order thinking abilities.