新課綱將資訊科技設為中學階段必修科目並推動運算思維教育，同時強調STEM這種橫向跨領域知識的重要性。物聯網可作為一種STEM教學，其作品整合了電路、物理、機械、資訊等領域的綜合性知識與技術之應用。
然而，一般的資訊科技教師是以專家程式設計思考程序教導學生編寫程式，相較之下，6E模式更能提升學習者設計與探究的能力，搭配實作教學活動可以整合理論知識與實作經驗，但在6E模式下學生的參與度和學習動機就成為影響學習的重要因素。本研究將遊戲化元素（故事、得分、排行榜、挑戰）結合6E模式，提出「遊戲化6E模式」，使學生在實作過程中更積極參與並能累積成就感，進而獲得更好的學習表現。
本研究透過準實驗設計探討不同教學模式（遊戲化6E模式、6E模式、專家程式設計思考程序）對於高中生學習態度（學習動機、自我效能）、學習成效（物聯網知識、運算思維、實作能力）之影響，並透過行為編碼後進行序列分析，觀察學習者在實作活動中的行為轉換模式。透過共變數分析，結果發現在學習態度上，學習動機與自我效皆達顯著差異，遊戲化6E模式組別之表現最佳；在學習成效上物聯網知識、實作能力達顯著差異，遊戲化6E模式組別之表現最佳，運算思維則未達顯著差異；透過行為序列分析，發現不同教學模式的學生在物聯網實作課程，皆需要頻繁地和老師進行雙向溝通，並需要與組員進行分工實作；採用遊戲化6E模式組別之學生為賺取得分獲而採取更為積極的互動方式，會在討論後展開協同實作，並主動詢問或幫助其他同學，具有更多與他人雙向互動之行為轉換達顯著，佐以說明學生有更良好的學習動機、態度與成效。

12-Year Baisc Education Curriculum Outline sets information technology as a compulsory subject in the secondary education and promotes computational thinking. At the same time, it emphasizes the importance of horizontal and cross-domain knowledge such as STEM. The Internet of Things can be used for STEM teaching. Its integrates the comprehensive knowledge and application of technology in the fields of circuits, physics, machinery, and information.
The general information technology teacher teaches students to program using the “Expert programming thinking process”. In contrast, the “6E model” can improve learners' design and inquiry abilities. With hands-on activities, 6E model can integrate theoretical knowledge and hands-on experience. However, under the 6E mode, students’ participation and learning motivation have become important factors affecting learning. So, this study proposes the “Gamification 6E model”, combines gamification elements (story, scores, rankings, challenges) with the 6E model, in order to enable learners to participate more actively in the hands-on process and accumulate a sense of accomplishment, thereby gaining better learning performance.
This study explores the impact of different teaching model (Gamification 6E model, 6E model, Expert programming thinking process) on high school students' learning attitude (learning motivation, self-efficacy) and learning effectiveness (IoT knowledge, computational thinking, hands-on ability) through quasi-experimental design. And through the sequence analysis after the behavior coding, observe the learner's behavior transformation in the hands-on activities. The ANCOVA results on learning attitudes found that there are significant differences in learning motivation and self-efficacy, and the gamification 6E model performs best of all. In terms of learning effectiveness results found that there are significant differences in IoT knowledge and hands-on ability, and the gamification 6E model performs the best, but there is no significant difference in computational thinking. The behavior sequence analysis result show that all of the students require frequent two-way communication with the teacher, and need to implement division of labor with the group members in different teaching model. Students in the “Gamification 6E model” group adopt a more active interactive way to earn points, and will start collaborative hands-on after discussion, and actively ask or help other students. There are more significant two-way interactions with other behaviors, which shows that students have better learning motivation, attitude and effectiveness.

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