피지컬 컴퓨팅을 통한 생명과학 분야 빅데이터 기술의 교육적 활용
Educational Application in Biology of the Big Data Technology Based on Physical Computing
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Due to the explosive increase in digital data, big data technology is using physical computing that undergoes data generation, output, transmission, collection, analysis, and processing processes is being used in various places in society as it enables prediction and customized services through data analysis. It is already possible to calculate in a form that facilitates real-time data collection and analysis using MBL in science curriculum. However, it does not provide a function to collect and view data generated by multiple devices in one place, it is necessary to observe real-time data. Therefore, this study was to explore the possibility of using big data technology based on physical computing centered on learners in educational environment. This study was also to examine the principles and research procedures of physical computing and big data technology, and to present educational application plans and possibilities. After installing Arduino device connecting temperature, humidity, CO2, and TVOC sensors in the classroom and laboratory, big data was collected every minute for a week, and classified according to conditions, then visualized in a graph according to the time axis and changed by time. We compared and analyzed the patterns that change according to the progress of class. This study could be provided opportunities for learners to develop their own capacity to manufacture devices and directly utilize big data technology, while enhancing inquiry and problem-solving capabilities from the experience of data science that analyzes big data.
Abstract
Due to the explosive increase in digital data, big data technology is using physical computing that undergoes data generation, output, transmission, collection, analysis, and processing processes is being used in various places in society as it enables prediction and customized services through data analysis. It is already possible to calculate in a form that facilitates real-time data collection and analysis using MBL in science curriculum. However, it does not provide a function to collect and view data generated by multiple devices in one place, it is necessary to observe real-time data. Therefore, this study was to explore the possibility of using big data technology based on physical computing centered on learners in educational environment. This study was also to examine the principles and research procedures of physical computing and big data technology, and to present educational application plans and possibilities. After installing Arduino device connecting temperature, humidity, CO2, and TVOC sensors in the classroom and laboratory, big data was collected every minute for a week, and classified according to conditions, then visualized in a graph according to the time axis and changed by time. We compared and analyzed the patterns that change according to the progress of class. This study could be provided opportunities for learners to develop their own capacity to manufacture devices and directly utilize big data technology, while enhancing inquiry and problem-solving capabilities from the experience of data science that analyzes big data.
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