Updated on 2024/10/02

Information

 

写真a

 
MA BOXUAN
 
Organization
Faculty of Arts and Science Division for Theoretical Natural Science Assistant Professor
Title
Assistant Professor
Contact information
メールアドレス
Tel
0928026016
Profile
Boxuan is currently working as an Assistant Professor in the Faculty of Arts and Science at Kyushu University. His main research interests include educational data mining, learning analytics, human-computer interaction, and recommender systems.
Homepage
External link

Research Areas

  • Informatics / Learning support system

  • Informatics / Human interface and interaction

Degree

  • Doctor of Engineering

Research History

  • Kyushu University Faculty of Arts and Science Assistant Professor

    2023.4 - Present

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Research Interests・Research Keywords

  • Research theme：学習支援システム

    Keyword：学習支援システム

    Research period： 2024

  • Research theme：言語学習支援

    Keyword：言語学習支援

    Research period： 2024

  • Research theme：知識追跡

    Keyword：知識追跡

    Research period： 2024

  • Research theme：推薦システム

    Keyword：推薦システム

    Research period： 2024

  • Research theme：学習診断

    Keyword：学習診断

    Research period： 2024

  • Research theme：利用者インタフェース

    Keyword：利用者インタフェース

    Research period： 2024

  • Research theme：ラーニングアナリティクス

    Keyword：ラーニングアナリティクス

    Research period： 2024

Papers

  • Investigating Concept Definition and Skill Modeling for Cognitive Diagnosis in Language Learning Invited Reviewed

    Boxuan Ma, Sora Fukui, Yuji Ando, Shin’ichi Konomi

    Journal of Educational Data Mining (JEDM)   16 ( 1 )   303 - 329   2024.6

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    Authorship：Lead author,　Last author,　Corresponding author  

    DOI： 10.5281/zenodo.10948071

    Scopus

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  • Exploring the Effectiveness of Vocabulary Proficiency Diagnosis Using Linguistic Concept and Skill Modeling Reviewed

    Boxuan Ma, Gayan, Prasad Hettiarachchi, Sora Fukui, Yuji Ando

    Proceedings of the 16th International Conference on Educational Data Mining   149 - 159   2023.7

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    Language：English   Publishing type：Research paper (other academic)  

  • Exploring the Effectiveness of Vocabulary Proficiency Diagnosis Using Linguistic Concept and Skill Modeling Reviewed

    Boxuan Ma, Gayan, Prasad Hettiarachchi, Sora Fukui, Yuji Ando

    Proceedings of the 16th International Conference on Educational Data Mining   149 - 159   2023.7

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    Authorship：Lead author,　Last author,　Corresponding author   Language：English   Publishing type：Research paper (international conference proceedings)  

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  • Each Encounter Counts: Modeling Language Learning and Forgetting Reviewed

    Boxuan Ma, Gayan Prasad Hettiarachchi, Sora Fukui, Yuji Ando

    ACM International Conference Proceeding Series   79 - 88   2023.3   （ ISBN:9781450398657 ）

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    Language：Others   Publishing type：Research paper (other academic)  

    Language learning applications usually estimate the learner's language knowledge over time to provide personalized practice content for each learner at the optimal timing. However, accurately predicting language knowledge or linguistic skills is much more challenging than math or science knowledge, as many language tasks involve memorization and retrieval. Learners must memorize a large number of words and meanings, which are prone to be forgotten without practice. Although a few studies consider forgetting when modeling learners' language knowledge, they tend to apply traditional models, consider only partial information about forgetting, and ignore linguistic features that may significantly influence learning and forgetting. This paper focuses on modeling and predicting learners' knowledge by considering their forgetting behavior and linguistic features in language learning. Specifically, we first explore the existence of forgetting behavior and cross-effects in real-world language learning datasets through empirical studies. Based on these, we propose a model for predicting the probability of recalling a word given a learner's practice history. The model incorporates key information related to forgetting, question formats, and semantic similarities between words using the attention mechanism. Experiments on two real-world datasets show that the proposed model improves performance compared to baselines. Moreover, the results indicate that combining multiple types of forgetting information and item format improves performance. In addition, we find that incorporating semantic features, such as word embeddings, to model similarities between words in a learner's practice history and their effects on memory also improves the model.

    DOI： 10.1145/3576050.3576062

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  • Exploring jump back behavior patterns and reasons in e-book system Reviewed

    Boxuan Ma, Min Lu, Yuta Taniguchi, Shin’ichi Konomi

    Smart Learning Environments   9 ( 1 )   2022.12   （ eISSN:2196-7091 ）

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    Language：Others   Publishing type：Research paper (scientific journal)  

    With the increasing use of digital learning materials in higher education, the accumulated operational log data provide a unique opportunity to analyzing student learning behaviors and their effects on student learning performance to understand how students learn with e-books. Among the students’ reading behaviors interacting with e-book systems, we find that jump-back is a frequent and informative behavior type. In this paper, we aim to understand the student’s intention for a jump-back using user learning log data on the e-book materials of a course in our university. We at first formally define the “jump-back” behaviors that can be detected from the click event stream of slide reading and then systematically study the behaviors from different perspectives on the e-book event stream data. Finally, by sampling 22 learning materials, we identify six reading activity patterns that can explain jump backs. Our analysis provides an approach to enriching the understanding of e-book learning behaviors and informs design implications for e-book systems.

    DOI： 10.1186/s40561-021-00183-6

    Web of Science

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  • Investigating course choice motivations in university environments Reviewed

    Smart Learning Environments   8 ( 1 )   2021.12

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    Language：Others   Publishing type：Research paper (scientific journal)  

    DOI： 10.1186/s40561-021-00177-4

  • CourseQ: the impact of visual and interactive course recommendation in university environments Reviewed

    Research and Practice in Technology Enhanced Learning   16 ( 1 )   2021.12

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    Language：Others   Publishing type：Research paper (scientific journal)  

    DOI： 10.1186/s41039-021-00167-7

  • Course Recommendation for University Environment. Reviewed

    Boxuan Ma, Yuta Taniguchi, Shin'ichi Konomi

    Proceedings of the 13th International Conference on Educational Data Mining(EDM)   2020.7

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    Language：Others   Publishing type：Research paper (other academic)  

  • Making Course Recommendation Explainable: A Knowledge Entity-Aware Model using Deep Learning Reviewed

    Tianyuan Yang, Baofeng Ren, Boxuan Ma, Md Akib Zabed Khan, Tianjia He, Shin'Ichi Konomi

    International Conference on Educational Data Mining (EDM 2024), 2024.   2024.7

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    Language：Others  

  • A Survey on Explainable Course Recommendation Systems Invited Reviewed

    Boxuan Ma, Tianyuan Yang, Baofeng Ren

    International Conference on Distributed, Ambient, and Pervasive Interactions (DAPI 2024), Held as Part of HCI International 2024, 2024.   2024.7

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    Language：Others  

  • Enhancing Programming Education with ChatGPT: A Case Study on Student Perceptions and Interactions in a Python Course Reviewed

    Boxuan Ma, Li Chen, Shin'ichi Konomi

    International Conference on Artificial Intelligence in Education (AIED 2024), 2024   2024.7

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    Language：Others  

  • How Do Strategies for Using ChatGPT Affect Knowledge Comprehension? Reviewed

    Li Chen, Gen Li, Boxuan Ma, Cheng Tang, Fumiya Okubo, Atsushi Shimada

    International Conference on Artificial Intelligence in Education (AIED 2024), 2024.   2024.7

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    Language：Others  

  • Enhancing Programming Education with ChatGPT: A Case Study on Student Perceptions and Interactions in a Python Course Reviewed

    Boxuan Ma, Li Chen, Shin'ichi Konomi

    International Conference on Artificial Intelligence in Education (AIED 2024), 2024   2024.7

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    Authorship：Lead author,　Last author,　Corresponding author  

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  • Making Course Recommendation Explainable: A Knowledge Entity-Aware Model using Deep Learning Reviewed

    Tianyuan Yang, Baofeng Ren, Boxuan Ma, Md Akib Zabed Khan, Tianjia He, Shin'Ichi Konomi

    International Conference on Educational Data Mining (EDM 2024), 2024.   2024.7

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  • How Do Strategies for Using ChatGPT Affect Knowledge Comprehension? Reviewed

    Li Chen, Gen Li, Boxuan Ma, Cheng Tang, Fumiya Okubo, Atsushi Shimada

    International Conference on Artificial Intelligence in Education (AIED 2024), 2024.   2024.7

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  • Investigating Concept Definition and Skill Modeling for Cognitive Diagnosis in Language Learning Invited Reviewed

    Journal of Educational Data Mining (JEDM)   2024.6

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    Language：Others  

  • Personalized Navigation Recommendation for E-book Page Jump Reviewed

    Boxuan Ma, Li Chen, Min Lu

    The 6th Workshop on Predicting Performance Based on the Analysis of Reading Behavior (DC@LAK24), 2024.   2024.3

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    Language：English  

  • Personalized Navigation Recommendation for E-book Page Jump Reviewed

    Boxuan Ma, Li Chen, Min Lu

    The 6th Workshop on Predicting Performance Based on the Analysis of Reading Behavior (DC@LAK24), 2024.   2024.3

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    Authorship：Lead author,　Last author,　Corresponding author  

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  • Personalized Navigation Recommendation for E-book Page Jump

    Ma B., Chen L., Lu M.

    CEUR Workshop Proceedings   3667   32 - 41   2024   （ ISSN:16130073 ）

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    Publisher：CEUR Workshop Proceedings  

    As the utilization of digital learning materials continues to rise in higher education, the accumulated operational log data provide a unique opportunity to analyze student reading behaviors. Previous works on reading behaviors for e-books have identified jump-back as frequent student behavior, which refers to students returning to previous pages to reflect on them during the reading. However, the lack of navigation in e-book systems makes finding the right page at once challenging. Students usually need to try several times to find the correct page, which indicates the strong demand for personalized navigation recommendations. This work aims to help the student alleviate this problem by recommending the right page for a jump-back. Specifically, we propose a model for personalized navigation recommendations based on neural networks. A two-phase experiment is conducted to evaluate the proposed model, and the experimental result on real-world datasets validates the feasibility and effectiveness of the proposed method.

    Scopus

  • How Do Strategies for Using ChatGPT Affect Knowledge Comprehension?

    Chen L., Li G., Ma B., Tang C., Okubo F., Shimada A.

    Communications in Computer and Information Science   2150 CCIS   151 - 162   2024   （ ISSN:18650929 ISBN:9783031643149 ）

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    Publisher：Communications in Computer and Information Science  

    This study investigates the effects of generative AI on the knowledge comprehension of university students, focusing on the use of ChatGPT strategies. Data from 81 junior students who used the ChatGPT worksheet were collected and analyzed. Path analysis revealed complex interactions between ChatGPT strategy use, e-book reading behaviors, and students’ prior perceived understanding of concepts. Students’ prior perceived understanding and reading behaviors indirectly affected their final scores, mediated by the ChatGPT strategy use. The mediation effects indicated that reading behaviors significantly influenced final scores through ChatGPT strategies, indicating the importance of the interaction with learning materials. Further regression analysis identified the specific ChatGPT strategy related to verifying and comparing information sources as significantly influenced by reading behaviors and directly affecting students’ final scores. The findings provide implications for practical strategic guidance for integrating ChatGPT in education.

    DOI： 10.1007/978-3-031-64315-6_12

    Scopus

  • Enhancing Programming Education with ChatGPT: A Case Study on Student Perceptions and Interactions in a Python Course

    Ma B., Chen L., Konomi S.

    Communications in Computer and Information Science   2150 CCIS   113 - 126   2024   （ ISSN:18650929 ISBN:9783031643149 ）

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    Publisher：Communications in Computer and Information Science  

    The integration of ChatGPT as a supportive tool in education, notably in programming courses, addresses the unique challenges of programming education by providing assistance with debugging, code generation, and explanations. Despite existing research validating ChatGPT’s effectiveness, its application in university-level programming education and a detailed understanding of student interactions and perspectives remain limited. This paper explores ChatGPT’s impact on learning in a Python programming course tailored for first-year students over eight weeks. By analyzing responses from surveys, open-ended questions, and student-ChatGPT dialog data, we aim to provide a comprehensive view of ChatGPT’s utility and identify both its advantages and limitations as perceived by students. Our study uncovers a generally positive reception toward ChatGPT and offers insights into its role in enhancing the programming education experience. These findings contribute to the broader discourse on AI’s potential in education, suggesting paths for future research and application.

    DOI： 10.1007/978-3-031-64315-6_9

    Scopus

  • A Survey on Explainable Course Recommendation Systems Invited Reviewed

    Boxuan Ma, Tianyuan Yang, Baofeng Ren

    International Conference on Distributed, Ambient, and Pervasive Interactions (DAPI 2024), Held as Part of HCI International 2024, 2024.   14719   273 - 287   2024   （ ISSN:0302-9743 ISBN:978-3-031-60011-1 eISSN:1611-3349 ）

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    Authorship：Lead author,　Last author,　Corresponding author  

    DOI： 10.1007/978-3-031-60012-8_17

    Web of Science

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  • Format-Aware Item Response Theory for Predicting Vocabulary Proficiency Reviewed

    Boxuan Ma, Gayan Prasad Hettiarachchi, Yuji Ando

    Proceedings of the 15th International Conference on Educational Data Mining   695 - 700   2022.7

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    Language：English   Publishing type：Research paper (other academic)  

  • Format-Aware Item Response Theory for Predicting Vocabulary Proficiency Reviewed

    Boxuan Ma, Gayan Prasad Hettiarachchi, Yuji Ando

    Proceedings of the 15th International Conference on Educational Data Mining   695 - 700   2022.7

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    Authorship：Lead author,　Last author,　Corresponding author   Language：English   Publishing type：Research paper (international conference proceedings)  

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  • UNDERSTANDING STUDENT SLIDE READING PATTERNS DURING THE PANDEMIC Reviewed

    Boxuan Ma, Min Lu, Shin'ichi Konomi

    18th International Conference on Cognition and Exploratory Learning in Digital Age, CELDA 2021   87 - 94   2021.10

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    Language：Others   Publishing type：Research paper (other academic)  

  • Exploration and Explanation: An Interactive Course Recommendation System for University Environments Reviewed

    Boxuan Ma, Min Lu, Yuta Taniguchi, Shin'ichi Konomi

    CEUR Workshop Proceedings   2903   2021.4

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    Language：Others   Publishing type：Research paper (other academic)  

  • Exploring the Design Space for Explainable Course Recommendation Systems in University Environments Reviewed

    Companion Proceedings of the 10th International Conference on Learning Analytics & Knowledge (LAK20)   2020.3

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    Language：Others  

  • Understanding Jump Back Behaviors in E-book System Reviewed

    Companion Proceedings of the 10th International Conference on Learning Analytics & Knowledge (LAK20)   2020.3

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    Language：Others  

  • Design of an elective course recommendation system for university environment Reviewed

    Boxuan Ma

    EDM 2019 - Proceedings of the 12th International Conference on Educational Data Mining   699 - 701   2019.7

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    Language：Others   Publishing type：Research paper (other academic)  

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Presentations

  • Making Course Recommender Systems Interpretable: A Feature-aware Deep Learning-based Approach

    The 86th National Convention of IPSJ, 2024.  2024.3 

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    Event date： 2024.3

    Language：English  

    Country：Japan  

  • Design a Course Recommendation System Based on Association Rule for Hybrid Learning Environments

    Hinokuni-Land of Fire Information Processing Symposium  2019.3 

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    Language：Others  

    Country：Other  

  • Learning path recommendation in university environments based on sequence mining

    The 81st National Convention of IPSJ  2019.2 

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    Language：Others  

    Country：Other  

  • Comparative Analysis of Adaptive Learning Path Recommendation Algorithms

    Joint Conference of Electrical, Electronics and Information Engineers in Kyushu  2018.9 

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    Language：Others  

    Country：Other  

MISC

  • Making Course Recommender Systems Interpretable: A Feature-aware Deep Learning-based Approach

    Tianyuan Yang, Baofeng Ren, Boxuan Ma, Shin’ichi Konomi

    The 86th National Convention of IPSJ, 2024.   2024.3

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  • Learning path recommendation in university environments based on sequence mining

    2019.2

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    Language：English  

  • アダプティブなラーニングバス推薦アルゴリズムに関する比較解析

    馬 博軒, 谷口 雄太, 木實 新一

    電気関係学会九州支部連合大会講演論文集   2018.9

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    Language：Japanese  

    Adaptive learning path recommendation system efficiently guides learners by constructing appropriate learning sequences from a set of recommended learning materials to reach their goals. As a vital role in adaptive learning path, recommendation algorithms could be grouped into three categories: intelligent optimization, data mining and knowledge-based algorithm. This paper summarizes the strategies of relevant algorithms in the learning path recommendation, as well as their strengths and weaknesses. This paper also compares and analyzes their performance to discuss their practical application value in learning path recommendation.

    DOI： 10.11527/jceeek.2018.0_258

Professional Memberships

  • The Institute of Electrical and Electronics Engineers (IEEE)

    2023 - Present

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  • International Educational Data Mining Society (IEDMS)

    2020 - Present

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  • Association for Computing Machinery (ACM)

    2020 - Present

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  • Society for Learning Analytics Research (SoLAR)

    2020 - Present

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  • Association for Computing Machinery (ACM)

  • International Educational Data Mining Society (IEDMS)

  • Society for Learning Analytics Research (SoLAR)

  • The Institute of Electrical and Electronics Engineers (IEEE)

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Academic Activities

  • PC member International contribution

    The 17th International Conference on Educational Data Mining  （ UnitedStatesofAmerica ） 2024.7

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    Type：Competition, symposium, etc. 

  • The 17th International Conference on Educational Data Mining

    2024 - Present

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    Type：Academic society, research group, etc. 

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  • Journal of Educational Data Mining (JEDM)

    Role(s)： Peer review

    2024 - Present

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  • Transactions on Knowledge and Data Engineering (TKDE)

    Role(s)： Peer review

    2024 - Present

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  • Research and Practice in Technology Enhanced Learning (RPTEL)

    Role(s)： Peer review

    2023 - Present

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  • Screening of academic papers

    Role(s)： Peer review

    2023

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    Type：Peer review 

    Number of peer-reviewed articles in foreign language journals：6

    Proceedings of International Conference Number of peer-reviewed papers：4

  • International Journal of Artificial Intelligence in Education (IJAIED)

    Role(s)： Peer review

    2021 - Present

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    Type：Peer review 

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Research Projects

  • A Framework for Fast, Accurate, and Explainable Computerized Adaptive Language Test

    Grant number：24K20903  2024 - 2026

    Japan Society for the Promotion of Science  Grants-in-Aid for Scientific Research  Early-Career Scientists

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    Authorship：Principal investigator  Grant type：Scientific research funding

    CiNii Research

  • 英語学習支援システムに関する研究

    2023.6 - 2026.5

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    Authorship：Principal investigator 

  • 英単語アプリ「ターゲットの友」による英語学習支援システムの研究、開発。

    2023.6 - 2024.5

    共同研究

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    Authorship：Principal investigator  Grant type：Other funds from industry-academia collaboration

  • Exploring Forgetting Behavior From Learning Data for Enhancing Knowledge Tracing

    2023 - 2024

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    Authorship：Principal investigator  Grant type：On-campus funds, funds, etc.

  • Distributed Cooperative Learning Analytics for Developing Communities

    Grant number：20H00622  2020.4 - 2025.3

    Grants-in-Aid for Scientific Research  Grant-in-Aid for Scientific Research (A)

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    Grant type：Scientific research funding

    CiNii Research

Educational Activities

  • 2023 - Current KIKAN Education Seminar （English）
    2024 - Current (IUPE) Computer Programming Exercise
    2024 - Current Methodologies for practical data analysis
    2023 - Current KIKAN Education Seminar
    2023 - Current Programming Exercise (Python)

Class subject

  • プログラミング演習

    2023.12 - 2024.2   Winter quarter

  • 基幹教育セミナー

    2023.6 - 2023.8   Summer quarter

  • プログラミング演習

    2023.6 - 2023.8   Summer quarter

  • プログラミング演習

    2023.4 - 2023.9   First semester

FD Participation

  • 2023.4   Role：Participation   Title：令和５年度 第１回全学ＦＤ（新任教員の研修）The 1st All-University FD (training for new faculty members) in FY2023

    Organizer：University-wide