2022 Fiscal Year Final Research Report
Development and evaluation of IoT experiment learning materials specialized for self-directed learning class in information engineering course for data science.
| Project/Area Number |
19K02979
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| Research Category |
Grant-in-Aid for Scientific Research (C)
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| Allocation Type | Multi-year Fund |
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| Section | 一般 |
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| Review Section |
Basic Section 09070:Educational technology-related
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| Research Institution | Tohoku Gakuin University |
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Principal Investigator |
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| Co-Investigator(Kenkyū-buntansha) |
淡野 照義 東北学院大学, 工学部, 教授 (50176004)
森島 佑 東北学院大学, 工学部, 講師 (40734132)
鈴木 順 仙台高等専門学校, 総合工学科, 准教授 (00639255)
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| Project Period (FY) |
2019-04-01 – 2023-03-31
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| Keywords | 教育工学 / AI技術 / 物体検出 / 誤配線検出 |
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| Outline of Final Research Achievements |
This study aims to develop and validate a teaching material model to support the acquisition of IoT development skills for students enrolled in information science departments or programs at universities and other educational institutions. The focus is particularly on software development techniques necessary for extracurricular classes and self-directed learning at home, as well as circuit development techniques involving the use of electronic devices. Due to the COVID-19 pandemic, planned experimental demonstrations of the extracurricular learning model within the university campus had to be postponed. However, efforts were made to modify and support software for autonomous learning and propose an AI-based approach for detecting wiring errors in electronic circuit implementations, which is difficult to solve even with current AI generation technologies. As a result of this research, certain achievements were obtained.
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| Free Research Field |
教育工学
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| Academic Significance and Societal Importance of the Research Achievements |
本研究では、情報系学生が自律してIoT機器の開発技術などを修得するために必要な教材が持つべき要件について問題点を明確にし、その具体的な解決方法をAI技術を用いて提案していることに学術的意義があると考える。研究期間中に直面した新型コロナウイルス感染症の感染拡大による未曽有の災害下にあっても遠隔授業等において、電子回路構築の学習支援を自動化あるいは補助するシステムの開発は、教育効果を保証し、自律学習を試みる学習者の技術力を養成するために重要である。本研究を進めることで、大学などの教育機関のみならず、広く産業界においてIoT開発を支援しうる技術としても社会的意義は十分認められる。
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