{"id":322904,"date":"2023-11-28T12:39:00","date_gmt":"2023-11-28T04:39:00","guid":{"rendered":"https:\/\/www.um.edu.mo\/news-and-press-releases\/campus-news\/detail\/57240-2\/"},"modified":"2023-12-04T16:33:37","modified_gmt":"2023-12-04T08:33:37","slug":"57240","status":"publish","type":"post","link":"https:\/\/www.um.edu.mo\/pt-pt\/news-and-press-releases\/campus-news\/detail\/57240\/","title":{"rendered":"Data science driving personalised education"},"content":{"rendered":"\n \n
In an ideal world, personalised education would be accessible to everyone, and data science is gradually making this dream a reality. According to Chen Fu, assistant professor in the Faculty of Education (FED) at the University of Macau (UM), technologies such as educational data mining and learning analytics are revolutionising teaching and learning.<\/div>
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Predicting and Enhancing Student Performance<\/div>
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Big data tools enable educators and schools to analyse, predict, and enhance student academic performance. \u2018For example, machine learning models trained on historical data can identify incoming students who are likely to struggle in their studies,\u2019 says Prof Chen.<\/div>
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Moreover, data science-driven innovations are contributing to learning path recommendations, automated grading, game-based learning, and the use of virtual learning assistants powered by large language models, adds Prof Chen.<\/div>
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As an expert in educational data mining, Prof Chen has studied the digital reading literacy of over 70,000 students across 14 countries and regions. Analysing data about their learning process and outcomes, he has proposed strategies for improvement. Through deep-learning models, he is also developing a system to assess and interpret students\u2019 cognitive states during learning, such as skill levels, emotions, and engagement levels, as well as learning outcomes such as correct or incorrect responses.<\/div>
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Prof Chen emphasises that data cleaning, statistical analysis, data visualisation, and data-driven decision-making are essential skills for those engaged in teaching and learning analytics. These skills form the backbone of the Analytics in Teaching and Learning specialisation under UM\u2019s Master of Science in Data Science programme, a collaborative offering between the university\u2019s Institute of Collaborative Innovation and FED.<\/div>
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Prof Chen, a faculty member in the programme, says that some graduates have applied their skills to analyse the problem-solving abilities of adults in technology-rich environments, based on cognitive diagnosis models. Others have created a comprehensive teaching quality evaluation platform for a variety of stakeholders, including teachers, students, and school administrators.<\/div>
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Enhancing Human Intelligence With AI<\/div>
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Mastering data skills not only prepares graduates for careers in data analysis, educational design, learning analytics, and educational data science but also enables teachers to enhance their teaching effectiveness. Furthermore, some of the graduates are pursuing doctoral degrees to further explore the applications of data science in education. \u2018Even those in traditional teaching roles may find themselves in need of a certain level of proficiency in data analysis, which will improve their ability to tailor learning paths for their students,\u2019 says Prof Chen.<\/div>
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Chinese & English Text \/ Davis Ip, Senior UM Reporter Amber Gu<\/div>
Photo \/ Provided by the interviewee<\/div>
Source: UMagazine<\/i> ISSUE 28<\/div>
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