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    题名: AI and Big Data in Education: Learning Patterns Identification and Intervention Leads to Performance Enhancement
    作者: 呂欣澤
    Lu, Owen H.T;Yang, Stephen J.H.;Lin, Chien-Chang;Huang, Anna Y.Q.;Hou, Chia-Chen;Ogata, Hiroaki
    贡献者: 創國學士班
    关键词: learning pattern;learning analytics;self-regulated learning;intervention
    日期: 2023-07
    上传时间: 2024-10-04 14:13:10 (UTC+8)
    摘要: Improving learning outcomes is always one of the key objectives of learning analytics (LA) and educational data mining (EDM). In recent years, many Massive Open Online Courses (MOOC) have been deployed and making it easier to collect learners’ data for further analysis. Naturally, leveraging AI to process such kind of big data becomes one of the main research streams to support education. In this paper, we collected data and defined student learning patterns by leveraging online courses on Python programming and we then verified if their learning performance was influenced by different learning patterns and interventions. We designed the intervention process, explored the impact of final learning outcomes, and analyze Self-Regulated Learning (SRL) abilities. From the experimental results, we share the learning outcomes and the difference in SRL with detailed explanation based on different groups.
    關聯: Information and Technology in Education and Learning, Vol.3, No.1, pp.1-11
    数据类型: article
    DOI 連結: https://doi.org/10.12937/itel.3.1.Inv.p002
    DOI: 10.12937/itel.3.1.Inv.p002
    显示于类别:[創國學士班] 期刊論文

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