Kyoto University · Computer Science
Professor Rwitajit Majumdar's research lab specializes in learning analytics, educational technology, and digital pedagogy, with a focus on enhancing self-directed learning, critical reading, and the design of interactive digital tools for education. The lab develops data-driven visual analytics platforms—such as iSAT and BookRoll—to support formative assessment, learner engagement, and the systematic analysis of student behaviors in both online and blended learning environments. A key research direction involves the digitization of traditional knowledge systems, exemplified by the development of a mobile-based framework for teaching Bharatanatyam, an Indian classical dance form, through gamified, grammar-based digital interaction. The lab also investigates the impact of emergency remote teaching during crises like the COVID-19 pandemic, emphasizing the role of e-book platforms and AI in sustaining educational continuity.
Figures are computed from collected data and may differ slightly.
Self-directed learning (SDL) ability, its usefulness in higher education and life-long learning have been highlighted in previous literature. However, there has been much less understanding of the effects of SDL ability in the school settings, specifically the effects on learners’ SDL behaviors and processes. To address this limitation, this study investigated the relations between SDL ability, SDL behaviors, and reading outcomes and further explored the process of planning behaviors in SDL. Thi
The 9th International Learning Analytics and Knowledge (LAK) Conference : March 4-8, 2019, Tempe, Arizona, USA
Abstract This study investigates learner’s reading behaviors in a critical reading task in humanities course using learning analytics techniques. A Critical Analysis of Literature and Cinema course was selected as a context. The course activities evolved over 10 years, and for this instance, some face-to-face classroom critical reading activities were migrated to online mode by using BookRoll, a learning analytics enhanced eBook platform. Students ( n =22 out of the 50 registered) accessed Hayav
UNESCO reported that 90% of students are affected in some way by COVID-19 pandemic. Like many countries, Japan too imposed emergency remote teaching and learning at both school and university level. In this study, we focus on a national university in Japan, and investigate how teaching and learning were facilitated during this pandemic period using an ebook platform, BookRoll, which was linked as an external tool to the university’s learning management system. Such an endeavor also reinforced th
Bharatanatyam is one of the most ancient Indian classical dance forms. There are students spread across the globe who learn this dance form at dance schools. Yet there exists no digital platform to help them systematically understand and independently practice the dance. This paper illustrates an effort to develop a digital Bharatanatyam interaction. A hierarchical architecture is extracted from the dance movements by analyzing its grammar. This is used in developing a framework to digitize the
Interactive Stratified Attribute Tracking (iSAT) is a visual analytics tool for cohort analysis. In this paper, we show how instructors can use iSAT to visualize transitions of groups of students during teaching-learning activities. Interactive visual analytics gives the instructor the affordance of understanding the dynamics of the class of students and their activities from the data collected in their own teaching-learning context. We take an example of a peer instruction (PI) activity and des
Representational competence (RC), defined as "the ability to simultaneously process and integrate multiple external representations (MERs) in a domain", is a marker of expertise in science and engineering. However, the cognitive mechanisms underlying this ability and how this ability develops in learners, is poorly understood. In this paper, we report a fully controllable interface, designed to help school students develop RC. Further, as the design emerged from the application of distributed an
We have created a visual representation called Stratified Attribute Tracking (SAT) Diagram to explicate trends that are otherwise implicit in learning analytics data. SAT Diagram is a unified graph that enables tracking individual attribute values in a dataset and stratifying them according to criteria set by the researcher. SAT diagram represents the transition of samples between strata across attributes. In this paper we introduce the SAT diagram and illustrate how to generate, interpret and a
The 9th International Learning Analytics and Knowledge (LAK) Conference : March 4-8, 2019, Tempe, Arizona, USA
For the 21st century learner, developing self-direction skill is crucial for both academic activities and maintaining one's healthy lifestyle. While there are technology supports for specific self-regulated learning tasks and health monitoring, research is limited on how to support development of meta-skill of self-direction process itself. In our work, we focus on designing seamless technology infrastructure to foster self-directedness of learners. We consider learning and physical activities d
Educational explainable AI (XAI) applications are gaining research focus and have distinct needs in the domain of Education. This research presents Educational eXplainable AI Tool (EXAIT), a system for math quiz recommendations, along with an explanation. EXAIT was implemented in a Japanese public high school where students received the top 5 math problems based on Bayesian Knowledge Tracing (BKT) algorithm in a learning analytics dashboard. It aimed to help them complete their summer vacation a
Interactive Stratified Attribute Tracking Diagram (iSAT) is a data visualization and tool to assist interactive visual analytics of multi-attribute learning dataset. The present work reports the evolution of this diagram through a design based research methodology following its three design iterations. There are two output at the current stage i) iSAT and its Web-based interaction. ii) A Learning Analytics method suitable for both researchers and practitioners to trace student attribute value. W
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