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Affiliation |
Graduate School of Engineering Science Department of Mathematical Science and Electrical-Electronic-Computer Engineering Human-Centered Computing Course |
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Date of Birth |
1986 |
LU MIN
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Research Interests 【 display / non-display 】
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Geographic Information Science
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Human-centered Mobile Mapping
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Learning Support System
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Spatial Information Science
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モバイルマッピング
Graduating School 【 display / non-display 】
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2004.09-2008.07
Peking University School of Space and Earth Sciences Geographic Information System Graduated
Graduate School 【 display / non-display 】
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2011.10-2014.09
The University of Tokyo Graduate School of Frontier Sciences Socio-Cultural Environmental Studies Doctor's Course Completed
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2008.09-2011.07
Peking University School of Space and Earth Sciences Cartology and Geographyic Information System Master's Course Completed
Campus Career 【 display / non-display 】
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2022.09-Now
Akita University Graduate School of Engineering Science Department of Mathematical Science and Electrical-Electronic-Computer Engineering Human-Centered Computing Course Assistant Professor
Research Areas 【 display / non-display 】
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Natural Science / Human geosciences
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Humanities & Social Sciences / Geography
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Informatics / Learning support system
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Informatics / Human interface and interaction
Thesis for a degree 【 display / non-display 】
Research Achievements 【 display / non-display 】
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Li Chen, Xuewang Geng, Min Lu, Atsushi Shimada, Masanori Yamada
SAGE Open ( SAGE Open ) 13 ( 3 ) 2023.07 [Refereed]
Research paper (journal) Domestic Co-author
Developed to maximize learning performance, learning analytics dashboards (LAD) are becoming increasingly commonplace in education. An LAD’s effectiveness depends on how it is used and varies according to users’ academic levels. In this study, two LADs and a learning support system were used in a higher education course to support students’ cognitive and self-regulated learning (SRL) strategies. A total of 54 students’ learning logs on three systems and their learning performance scores were collected; descriptive statistics of learning behaviors, Mann-Whitney U test, and lag sequential analysis were used to explore how students with different learning performances used LADs to support their learning. Compared to low-performers, high-performers used the LADs more frequently during preview and review phases and conducted more monitoring and reflection strategies to support their learning. Finally, some practical implications for improving the design and use of LADs were provided.
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Mobile Collaborative Heatmapping to Infer Self-Guided Walking Tourists’ Preferences for Geomedia
Iori Sasaki, Masatoshi Arikawa, Min Lu, Ryo Sato
ISPRS International Journal of Geo-Information ( ISPRS International Journal of Geo-Information ) 12 ( 7 ) 2023.07 [Refereed]
Research paper (journal) Domestic Co-author
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Cross-language font style transfer
Chenhao Li, Yuta Taniguchi, Min Lu, Shin’ichi Konomi, Hajime Nagahara
Applied Intelligence ( Springer Science and Business Media LLC ) 2023.02 [Refereed]
Research paper (journal)
Abstract
In this paper, we propose a cross-language font style transfer system that can synthesize a new font by observing only a few samples from another language. Automatic font synthesis is a challenging task and has attracted much research interest. Most previous works addressed this problem by transferring the style of the given subset to the content of unseen ones. Nevertheless, they only focused on the font style transfer in the same language. In many cases, we need to learn font style from one language and then apply it to other languages. Existing methods make this difficult to accomplish because of the abstraction of style and language differences. To address this problem, we specifically designed the network into a multi-level attention form to capture both local and global features of the font style. To validate the generative ability of our model, we constructed an experimental font dataset of 847 fonts, each containing English and Chinese characters with the same style. Results show that our model generates 80.3% of users’ preferred images compared with state-of-the-art models. -
Proposal and Demonstration Experiment of a Simple Framework for Realizing Indoor AR Navigation
Masatoshi Arikawa, Kohei Oba, Shinpei Ito, Ryo Sato, Min Lu
63 ( 12 ) 1821 - 1829 2022.12 [Refereed]
Research paper (journal) Domestic Co-author
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Exploring jump back behavior patterns and reasons in e-book system
Boxuan Ma, Min Lu, Yuta Taniguchi, Shin’ichi Konomi
Smart Learning Environments ( Springer Science and Business Media LLC ) 9 ( 2 ) 1 - 23 2022.01 [Refereed]
Research paper (journal) Domestic Co-author
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.
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Adaptive visualization of tourists' preferred spots and streets using trajectory articulation
Iori Sasaki, Masatoshi Arikawa, Min Lu
Proceedings of the 2nd ACM SIGSPATIAL International Workshop on Animal Movement Ecology and Human Mobility ( ACM ) 27 - 32 2022.11 [Refereed]
Research paper (international conference proceedings) Domestic Co-author
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Understanding Student Slide Reading Patterns During the Pandemic
Boxuan Ma, Min Lu, Shin’ichi Konomi
Proceedings of 18th International Conference on Cognition and Exploratory Learning in Digital Age (CELDA 2021) ( IADIS Press ) 87 - 94 2021.10 [Refereed]
Research paper (international conference proceedings) Domestic Co-author
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Exploration and Explanation: An Interactive Course Recommendation System for University Environments
Boxuan Ma, Min Lu, Yuta Taniguchi, Shin'ichi Konomi
CEUR Workshop Proceedings ( CEUR-WS ) 2903 2021.04 [Refereed]
Research paper (international conference proceedings) Domestic Co-author
The abundance of courses available in university and the highly personalized curriculum is often overwhelming for students who must select courses relevant to their academic interests. A large body of research in course recommendation systems focuses on optimizing prediction and improving accuracy. However, those systems usually afford little or no user interaction, and little is known about the influence of user-perceived aspects for course recommendations, such as transparency, controllability, and user satisfaction. In this paper, we argue that involving students in the course recommendation process is important, and we present an interactive course recommendation system that provides explanations and allows students to explore courses in a personalized way. A within-subject user study was conducted to evaluate our system and the results show a significant improvement in many user-centric metrics.
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Few-Shot Font Style Transfer Between Different Languages
Chenhao Li, Yuta Taniguchi, Min Lu, Shin'ichi Konomi
Proceedings of the IEEE/CVF Winter Conference on Applications of Computer Vision (WACV), 2021 ( Institute of Electrical and Electronics Engineers Inc. ) 433 - 442 2021.01 [Refereed]
Research paper (international conference proceedings) Domestic Co-author
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Factors of the use of learning analytics dashboard that affect metacognition
Li Chen, Min Lu, Yoshiko Goda, Atsushi Shimada, Masanori Yamada
17th International Conference on Cognition and Exploratory Learning in Digital Age, CELDA 2020 ( IADIS Press ) 295 - 302 2020.11 [Refereed]
Research paper (international conference proceedings) Domestic Co-author
© 2020 17th International Conference on Cognition and Exploratory Learning in Digital Age, CELDA 2020. All rights reserved. In this study, we used a learning analytics dashboard (LAD) in a higher education course to support students' metacognition and evaluated the effects of its use. The LAD displays students' reading path and specific behaviors when viewing digital learning materials. The study was conducted on 53 university students to identify the factors that affected metacognition changes in terms of their awareness and behavior dimensions when using the LAD. In terms of results, first, the students' perception of visual attraction for the LAD, and behaviors related to reflection such as deleting annotations they had previously added, positively affected the changes in the knowledge of cognition dimension of metacognition. Second, students' perception of behavioral changes by using the LAD had positive effects on the regulation of cognition dimension of metacognition. However, the behaviors of using some cognitive tools, negatively affected knowledge of cognition, which indicated the necessity to provide more guidance or feedback to students.
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Adaptable Data-Driven Geofences for Notifying Points of Interest Using Tourists' GPS Trajectories
Iori Sasaki, Masatoshi Arikawa, Min Lu, Ryo Sato, Tomihiro Utsumi
Proceedings of the 7th ACM SIGSPATIAL Workshop on Location-based Recommendations, Geosocial Networks and Geoadvertising ( ACM ) 2023.11 [Refereed]
Summary of the papers read (international conference) Domestic Co-author
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Iori Sasaki, Masatoshi Arikawa, Min Lu, Ryo Sato
Abstracts of the ICA ( Copernicus GmbH ) 6 1 - 2 2023.08 [Refereed]
Summary of the papers read (international conference) Domestic Co-author
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Learning Analytics Dashboard Supporting Metacognition
Li Chen, Min Lu, Yoshiko Goda, Atsushi Shimada, Masanori Yamada
Balancing the Tension between Digital Technologies and Learning Sciences ( Springer International Publishing ) 129 - 149 2021.02 [Refereed]
Domestic Co-author
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Visualizing Studying Activities for a Learning Dashboard Supporting Meta-cognition for Students
Min Lu, Li Chen, Yoshiko Goda, Atsushi Shimada, Masanori Yamada
Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) ( Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) ) 12203 LNCS 569 - 580 2020.07 [Invited]
Domestic Co-author
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Pilot Study to Estimate "Difficult" Area in e-Learning Material by Physiological Measurements.
Kaori Tamura, Tsuyoshi Okamoto, Misato Oi, Atsushi Shimada, Kohei Hatano, Masanori Yamada, Min Lu, Shin'ichi Konomi
Proceedings of the Sixth ACM Conference on Learning @ Scale, L@S 2019, Chicago, IL, USA, June 24-25, 2019. ( ACM ) 35:1 - 35:4 2019.06
◆Original paper【 display / non-display 】
◆International conference proceedings【 display / non-display 】
◆Other【 display / non-display 】
Books 【 display / non-display 】
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Ubiquitous Mapping: Perspectives from Japan - Chapter 2: Ubiquitous Digital Storytelling with Local and Dynamic Georeferencing of Analog Maps
Masatoshi Arikawa, Min Lu
Springer Singapore 2022.07 ISBN: 978-981-19-1535-2
Grant-in-Aid for Scientific Research 【 display / non-display 】
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Grant-in-Aid for Scientific Research(C)
Project Year： 2023.04 - 2027.03
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Grant-in-Aid for Scientific Research(A)
Project Year： 2022.04 - 2026.03
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Grant-in-Aid for Challenging Research (Pioneering)/(Exploratory)
Project Year： 2021.07 - 2025.03
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Grant-in-Aid for Early-Career Scientists
Project Year： 2020.04 - 2023.03
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Fund for the Promotion of Joint International Research
Project Year： 2019.10 - 2023.03
Presentations 【 display / non-display 】
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Design and Implementation of Programming Classes using MediaLib for Beginners in Universities
Min Lu, Jingyun Wang, Masatoshi Arikawa, Ryo Sato
The 85th National Convention of IPSJ 2023.03 - 2023.03
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Development of Learning Analytics Platform for Macro and Micro Learning Analytics
Masanori YAMADA, Min LU, Yuta TANIGUCHI, Fumiya OKUBO, Chen LI,Rin-Ichiro TANIGUCHI
Annual conference of Japanese Society of Educational Technology 2022 Spring 2022.03 - 2022.03
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Smart code recommendation system for supporting the learning process of programming beginners
IEICE SIG ET Technical Report 2020.12 - 2020.12
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Formative Evaluation of Learning Analytics Dashboard "Metaboard" for Enhancement of Metacognition
2020.09 - 2020.09
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Development of a Learning Dashboard Prototype Supporting Meta-cognition for Students
Min Lu, Li Chen, Yoshiko Goda, Atsushi Shimada, Masanori Yamada
10th International Conference on Learning Analytics & Knowledge (LAK20) (Frankfurt, Germany (Online)) 2020.03 - 2020.03 Society for Learning Analytics Research