優良的教學策略制定可以提升學習者的學習動機、參與程度以及學習成效，然而，這些重要的評 估大多是在教學實驗結束後才能進行。授課者在教學過程難以隨時注意學習者的學習狀況，以至於無 法隨時調整自己的教學步調與難易程度。因此，如何即時協助授課者在講授時，隨時注意學習者的學 習狀況，以避免學生的腦部思考與心理壓力過度負載，為科學學習上的重要課題。隨著科技的發展， 人類開始得以藉由腦電波與心電波來探索學習過程的生理反應。本研究將發展微型生理訊號量測裝 置，廣泛落實在課堂教室上，使得在教學過程中可以隨時記錄學習者的生理狀況，並搭配每位學習者 的學習成效，進一步瞭解學習過程對於生理的影響。本計晝為一個三年期的整合型計晝，第一年將建 置雲端互動教室，用此探討開放/封閉教學問題的設計對認知負荷的影響；第二年將會開發微型生理訊 號量測裝置，應用於實境教學環境，探究不同先備知識程度與匿名非匿名學習環境對於認知負荷、記 憶回溯以及心理壓力的影響；第三年將雲端互動教室系統做整合，並建立分類器，達到即時回饋教學 者的目的。本子計晝將會提供子計晝一與子計晝二認知負荷與心理壓力的生物指標，並完成適性化開 放性問題設計與制定最佳合作學習的策略。 ;Effective instructional strategies in classroom can raise students’ learning motivation, participation will, and study performance. However, evaluating the effectiveness of instructional strategy is usually done after class. Since tutors usually do not know the learning performance of students on class in real-time, regulating the depth of teaching materials to fit students learning status is also not possible. Therefore, it is worthy to develop assistive learning technologies to help tutors understand students’ mental stress and cognitive load in classroom scenario. With the development of modern technologies, it allows people to study students’ physiological states by means of measuring subjects’ electrocardiography (ECG) and electroencephalography (EEG) signals. In this project, we intend to realize a biofeedback system to measure subjects’ physiological state during classroom learning. The system enables tutors to understand the relations between their instruction strategies and subjects’ learning performances. The proposed project is the subproject III of a three-year integrated project. In this first year, we will construct a CloudClassRoom (CCR) with biofeedback to study the influence of open- /close- ended questions on students’ cognitive loads. In the second year, we will develop wearable ECG/EEG monitoring system to discuss the effects of prior knowledge and anonymity learning environment on student’s cognitive load, memory retrieval and mental stress. In the last year, we will integrate our wearable devices with CCR. Biomarkers will be real-time calculated and provided to subproject I and II to improve the construction of adaptive question-driven science instruction in CloudClassRoom scenario.
