隨著網際網路日漸普及，物聯網於生活中的應用日益增多，物聯網的教育也成為全球資訊教育所關注的重要議題，然而過往的物聯網課程仍有待改進：使用開放硬體進行物聯網教學除了設備費用昂貴以外，也時常因為過程繁瑣、實驗過程難以觀察等因素而影響學習效果；在物聯網中所涉及的許多概念如「資料表示、處理與分析」、「網路協定」等，大多有著複雜的架構、繁複的處理流程，學生往往無法完整理解其架構與運作方法；此外在物聯網主題中也包含「演算法」等較為抽象的學習內容，然而傳統講授式教學較無法引導學生主動思考，導致學生無法掌握抽象的演算流程。以上的種種皆導致物聯網的教學在中、小學教育體系中不容易被落實。
為了將抽象且複雜的概念視覺化、具體化，以幫助學生理解，以及解決使用開放硬體進行教學所面臨的種種限制，本研究發展視覺化模擬輔助物聯網教學之教學策略，針對「硬體操作模擬」、「架構流程模擬」、「抽象概念模擬」三種模擬形式開發視覺化模擬輔助學習平台，並探討視覺化模擬輔助教學對物聯網學習成就、學習態度之影響。此外，為探究抽象推理能力對於學習物聯網此等抽象複雜的內容是否會造成影響，以及不同的教學策略是否對不同抽象推理能力的學生造成不同的影響，研究亦將抽象推理能力納入討論。經由教學實驗結果發現：
一、本研究發展之視覺化模擬輔助學習平台上，「硬體操作模擬」能幫助學生記憶模組的功能與應用，對於感知層的意義有較完整的理解，並且融入了模擬情境的設計，幫助學生將感知層相關概念與具體情境連結，因而能將課堂所學的概念類推應用至其他生活情境；「架構流程模擬」能幫助學生逐步觀察架構與流程的運作方式並與之互動，藉以掌握複雜的物聯網架構與運作流程；「抽象概念模擬」能透過設定參數與觀察演算法動態的模擬結果，幫助學生以視覺化的形式將抽象概念進行表徵，以更清楚理解演算法的邏輯、執行順序以及變項之間的關聯性，進而能描述較完整的演算法細節，因而，視覺化模擬輔助教學能提升學生物聯網的學習成就。
二、視覺化模擬輔助教學相較於傳統講述式教學，學生能以自己的步調進行學習，並藉由與平台的互動過程學習物聯網概念，且給予學生即時的回饋，使學生能隨時根據回饋修正思考，因此更能掌握自身理解概念的歷程，進一步擁有較高的自我效能。另一方面，使用視覺化模擬輔助教學，能幫助學生以視覺化的形式將抽象概念進行表徵，並使學生透過逐步觀察架構與流程的運作方式並與之互動，藉以掌握複雜的物聯網架構與運作流程，能降低學生的學習負擔，因而對於抽象主題的學習感受較為正向，且感受到的課程難度較低。此外，視覺化模擬輔助教學能提供更加系統化地統整物聯網的知識架構，學生可以按照物聯網的架構逐漸學習相關的物聯網概念，可以更有效的理解物聯網的完整架構，因此對自身在物聯網主題的理解程度有較正向的感受。在電腦科學學習興趣方面，因實驗組與控制組在課程中皆涵蓋許多生活中的物聯網案例，且有較多學習內容是與學生自身生活有連結，故兩組皆顯著提升電腦科學學習興趣。此外，從性別的因素來看，男生較認同視覺化模擬輔助教學之有效性，而此教學方式較能降低女生對於抽象學習主題的負面感受。
三、無論是在傳統講述式教學抑或是視覺化模擬輔助教學，可能由於本研究之物聯網課程內容超越抽象推理能力的範疇，所涉及的問題更為複雜，因此抽象推理能力未顯著影響物聯網學習成就。在學習態度方面，若施以傳統講述式教學，低抽象推理能力的學生所感受到的物聯網課程難度較高抽象推理能力的學生難，但透過視覺化模擬輔助教學，此差距將被拉近，表示其能有效地減少學生在學習複雜且抽象主題的學習困難，使得低抽象推理能力的學生對課程難度的感受與高抽象推理能力的學生無顯著差異；而在學習態度「電腦科學自我效能」、「電腦科學學習興趣」、「抽象主題學習感受」、「物聯網理解概況」、「視覺化模擬輔助之有效性」等面向，不論是施以傳統教學或視覺化模擬輔助教學，高、低抽象推理能力的學生之態度無顯著差異，可能由於本研究之物聯網課程內容複雜，所需之能力較為多元，並無法單就抽象推理能力探究其影響，在教學策略與抽象推理能力之間也無交互作用。然而，實驗結果發現視覺化模擬輔助教學能提升低抽象推理能力的學生對於電腦科學的學習興趣、自我效能，降低其對於物聯網課程的難度感受，並且在學習抽象主題(如演算法等)學習時擁有較正向的學習感受。

As the Internet becomes increasingly ubiquitous, the application of the Internet of Things (IoT) in daily life is on the rise. IoT education has also emerged as a significant concern in global information education. However, there are several issuses in IOT education that need to be addressed: teaching IoT with open hardware not only involves high costs for instruments but is also often hindered by intricate processes of assembling the components, affecting learning outcomes. The IoT topic include various types of concepts and skills, such as IoT data representation, processing, and analysis, the relavent algorithms, network architechture and protocols, are often complex and abstract. Students frequently struggle to fully comprehend their architectures and operational methods. All these challenges make it difficult to effectively implement IoT education in primary and secondary education systems.
To visualize and concretize the abstract and complex concepts involved in the IOT topic, as well as to address various limitations encountered in teaching with open hardware, this study developed simulaiton-based instruction for the IoT. The research focused on three types of simulation: "Hardware Operation Simulation," "Architecture and Process Simulation," and "Abstract Concept Simulation." The experiment results revealed that:
1. The "hardware operation simulation" aids students in establishing connections between concepts related to the perceptual layer of the IoT and its applications. Consequently, students can extrapolate and apply the learned concepts to various real-life scenarios. The "architecture and process simulation" assists students in observing and interacting with the architecture and the dynamic process of the IoT. The "abstract concept simulation" clarifies students’ concepts and help them understand the algorithm through setting and modifiying the parameters and observing the changes. Consequently, the proposed simulation-based instruction Hence, the incorporation of visual simulation in teaching enhances students' learning achievements in the realm of the Internet of Things.
2. Compared to traditional instruction, simulation-based instruction allows students to proceed at their own pace and learn Internet of Things concepts through interaction with the concepts and processes. Providing immediate feedback enables students to refine their concepts in real-time, enhancing their ability to grasp the concepts and fostering higher self-efficacy. Additionally, the use of visualized simulation helps represent abstract concepts in a visual and concrete form. Through step-by-step observation of the operation and interaction with the architecture and processes, students can comprehend the complexities of Internet of Things architectures and operational processes. This approach reduces the learning burden and promotes a more positive perception of learning abstract concepts. Regarding gender differences, males tend to acknowledge the effectiveness of simulation-based instruction more. This instructional method reduces females' negative perceptions toward learning abstract concepts.
3. The abstract reasoning ability of students does not have a significant influence on their learning achievements in the IoT. This might be because IoT concepts involve more than abstract reasoning, dealing with more complex cognition. In terms of learning attitudes, when traditional instruction is employed, students with lower abstract reasoning abilities perceive higher difficulty in the IoT course compared to students with higher abstract reasoning abilities. However, this disparity is lessened with the adoption of simulation-based instruction, indicating its effective reduction of learning difficulties for students tackling complex and abstract topics. Thus, students with lower abstract reasoning abilities perceive no significant difference in course difficulty compared to those with higher abstract reasoning abilities. Concerning learning attitudes in aspects such as "computer science self-efficacy," "interest in computer science learning," "perception of learning abstract topics," "understanding of IoT concepts," and "effectiveness of simulation tools," there is no significant difference in attitudes between students with high and low abstract reasoning abilities, whether through traditional or simulation-based instruction. This may be attributed to the complexity of the IoT concepts in this study, requiring diverse abilities, and abstract reasoning ability alone may not sufficiently explore its impact. There is also no interaction between instructional strategies and abstract reasoning ability. However, the experimental results reveal that simulation-based instruction enhances the interest and self-efficacy of students with lower abstract reasoning abilities in learning computer science. It reduces their perceived difficulty in the IoT course and fosters a more positive learning experience when dealing with abstract topics such as algorithms.

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