Math balance aids based on Internet of Things for arithmetic operational learning
Industry 4.0 has changed various aspects of human life towards an era heavily influenced by information technology. The impact of industry 4.0 on the education sector has led to the emergence of the term education 4.0. The Internet of Things (IoT) is one of the pillars of industry 4.0. With its capa...
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| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Science and Information Organization
2022
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| Subjects: | |
| Online Access: | http://eprints.utm.my/id/eprint/98612/1/NovianAnggisSuwastika2022_MathBalanceAidsbasedonInternet.pdf http://eprints.utm.my/id/eprint/98612/ http://dx.doi.org/10.14569/IJACSA.2022.0130826 |
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| Summary: | Industry 4.0 has changed various aspects of human life towards an era heavily influenced by information technology. The impact of industry 4.0 on the education sector has led to the emergence of the term education 4.0. The Internet of Things (IoT) is one of the pillars of industry 4.0. With its capabilities, IoT can provide opportunities to develop innovations in the field of education. Several studies show that teaching aids can improve the quality of learning and learning outcomes. In Indonesia, mathematics is a compulsory subject taught from elementary school to higher education. Previous studies that used mathematical (math) balance aids to help students learn mathematical operations showed positive correlations between the learning process and student learning outcomes in the materials related to arithmetic operations. This study aims to develop an IoT-based mathematical balance tool to support three education 4.0 trends: remote access, personalization, and practice and feedback. This study used modifications of Fahmideh and Zogwhi's IoT development method. There are five phases of IoT development: initialization phase, analysis phase, design phase, implementation phase, and evaluation phase. From each phase of IoT development, IoT-based mathematical balance assistance systems have been successfully built and it complies with the functionality described in the analysis phase. The system performance also shows optimal results with 100% accuracy for reading the student's learning activities. Moreover, it uses less than 10 seconds for processing 1000 data requests. |
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