| 研究課題/領域番号 |
20H01719
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| 配分区分 | 補助金 |
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| 研究機関 | 東京工業大学 |
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研究代表者 |
クロス ジェフリーS 東京工業大学, 環境・社会理工学院, 教授 (90532044)
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| 研究期間 (年度) |
2020-04-01 – 2025-03-31
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| キーワード | オンライン学習 / ラーニング分析 / 学習管理システム / 個人学習 / 人工知能 / メタ認知 |
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| 研究実績の概要 |
Personal Online Analytic Learning System (POALS) is a web-based learning management system (LMS) developed to help learners succeed when taking online learning courses. It is made up of three components: 1) the Metacognitive Tutor to equip students with metacognitive skills needed for autonomous learning crucial to online learning, 2) the Adaptive Engine to help students manage the cognitive strain of having metacognitive tutoring alongside domain knowledge learning, and the 3) Analytics Dashboard based on student responses on the Metacognitive Tutor to give feedback to teachers on where learner interventions might be needed. The Metacognitive Tutor was developed using the open edX LMS and was test with several online course. An extensive literature review was conducted on the theory behind the Metacognitive Tutor, which was presented at the IEEE Teaching, Assessment and Learning for Engineering (TALE) conference in Dec. 2020. Modeling was also conducted for the Adaptive Engine and the results were submitted to a journal for publication. Other related research done was on exploring the readiness of elementary school teachers to teach programming, a skill being prioritized by Japan, as well as research efficacy and English writing skills. These all stand to benefit from metacognition. Research achievements from this grant include seven conference presentations with one published proceeding and international workshop.
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| 現在までの達成度 (区分) |
現在までの達成度 (区分)
1: 当初の計画以上に進展している
理由
During the first year of research the learnming management system was developed POALS is a web-based system designed to help learners succeed in online learning environments. It is made up of three components as stated above. The research consists of the LMS development covering data handling, analysis and testing it in online course with actual learners. The research is actually on-schedule as denoted by the number of publications and conference presentations. The research for 2021 will focus on documenting all the results gathered thus far and prototyping the instructor analytics dashboard. In addition, research will be conducted on AI-supported English writing. Elementary school teacher readiness in teaching programming will likewise be continued. This complementary research is expected to contribute to the overall goal of POALS by shedding an understanding on teachers' capability to use ICT for instruction, which is the condition where POALS is situated at.
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| 今後の研究の推進方策 |
The POALS research plan for AY 2021 is to publish all the results gathered thus far. A prototype of the Instructor Analytics Dashboard will also be developed. This will involve the study of various natural language processing (NLP) techniques such as sentiment analysis, text similarity, and topic modeling as well as their usefulness in the online learning setting. Both traditional and emerging NLP techniques (e.g., deep learning approaches) will be explored. Another important aspect of the research is human-computer interaction, which can allow us to analyze whether the Analytics Dashboard will be usable for its intended user before a full-scale version is developed.
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