Dr. Rwitajit Majumdar

Associate Professor, Kumamoto University 

I am an Associate Professor at the Research and Educational Institute for Semiconductors and Informatics.
and the Graduate School of Social and Cultural Sciences, Division of Instructional System Studies at Kumamoto University.

Before this, I was a Senior Lecturer at the Academic Center for Computing and Media Studies (ACCMS), and the Department of Social Informatics at the Graduate School of Informatics at Kyoto University. I am associated with the project in Prof. Hiroaki Ogata's Learning and Educational Technologies Research Unit. 

My research focuses on Learning Analytics and Human-data interactions. With a team of students and researchers, I design user workflow for data-informed decision-making in the teaching-learning context. Given any technology-enhanced learning context, I investigate the user and system interactions based on the log data generated while the user operates in the technology platform to complete their set tasks. Based on that data analysis, I aim to inform AI technology design, evaluate its effectiveness, and theorize the teaching and learning process that the technology supports. My primary stakeholders are teachers and students. I am fortunate to work with a group of extremely motivated collaborators on various projects!

For the teachers, I am focusing on developing Learning Evidence Analytics Framework (LEAF) to support Technology-enhanced and Evidenced-based Education and Learning (TEEL). This open-source framework aims to extract evidence of effective teaching and learning practices by harnessing the power of learning analytics. Applying co-design methodology along with instructors, developers and researchers, we are building the infrastructure to store the evidence base of instructional practice. We aim to analyze the gathered knowledge base of evidence and recommend them to the practitioners. 

• For more details please visit the site for the LEAF Framework &TEEL workshops and SPIRITS2020 project.

For the students, I am focusing on designing and developing the technology support for the acquisition of skills of being self-directed in this data-driven age.  It is the Goal Oriented Active Learner (GOAL) project. The project is in the interface of quantified-self and learning analytics where the learner's own learning and physical activity data is automatically synchronized in the GOAL system. Their visualized data is presented to them to support analysis, planning, monitoring, and reflection. I completed a JSPS research startup project (#18H05746, 2.99M JPY from 2018-2020) and JSPS early-career grant (#20K20131, 4.16M JPY from 2020-2022) to partially support this research. Currently, the project received the JSPS Kiban B (#22H03902, 17.68M JPY from 2022-2025).

• For more details please visit the site for the GOAL project 

During my graduate studies in the Inter-Disciplinary Program in Educational Technology at Indian Institute of Technology Bombay, I under the guidance of my Ph.D. supervisor Prof. Sridhar Iyer, IDP in Educational Technology & Dept. of Computer Science and Engineering, and Prof. Aniruddha Joshi, Industrial Design Center, IIT Bombay. I developed a visual analytics framework, Interactive Stratified Attribute Tracking (iSAT) to visualize transition patterns in any existing educational dataset. iSAT tool was built on that framework to assist visual cohort analysis. If you are an Educational Technology researcher, Classroom / MOOC instructor or involve in making data-driven decisions in educational settings, you can possibly use iSAT to visualize transition patterns with your data and interpret meaning in your context.

Education

• • Ph.D. Indian Institute of Technology Bombay, Mumbai, 2018

  • Doctoral Course work, Indian Institute of Science, Bangalore, 2012

  • Masters in Engineering, Design Engineering
    Birla Institute of Technology and Science, Pilani, 2012

  • Masters in Science (Technology), Engineering Technology
    Birla Institute of Technology and Science, Pilani, 2009

Research Grants

As Principal Investigator (PI)

• • Title: miXai^learn: Multimodal Interactions, and Explainable AI for Embodied learning

    • funding: 2024 - 2026 JSPS Grant-in-Aid for Joint International Research B (20,930,000 円)

    • project number: 24KK0051

  • Title: GOAL project: AI-supported self-directed learning lifestyle in data-rich educational ecosystem

    • funding: 2022 - 2025 JSPS Grant-in-Aid for Scientific Research B (17,680,000 円)

    • project number: 22H03902

  • Title: GOAL Project: SMART AI Support with Student's Learning and Wellbeing Data.

    • funding: 2020 - 2023 JSPS Grant-in-Aid for Early Career Research (4,160,000 円)

    • project number: 20K20131

  • Title: LA-ReflecT: Modeling meta-cognitive processes in reflective reading & its open book assessments

    • funding: 2020 - 2022 Kyoto University SPIRITS Grant, Supporting Program for Interaction-based Initiative Team Studies Grant (5,830,000 円)

    • project number: SPIRITS2020

  • Title: GOAL Project: Developing Technology Support for Acquisition of Self Direction Skill

    • funding: 2018 - 2020 JSPS Grant-in-Aid for Research Activity start-up (2,990,000 円) 

    • project number: (2018) 18H05746 and (2019) 19K20942 

As Co-Principle Investigator (Co-PI)

• • Title: Extraction and Use of Highly Explainable and Transferable Indicators for AI in Education

    • funding: 2023-2026 JSPS Grant-in-Aid for Scientific Research (B) (18,850,000 円)

    • project number: 23H01001

  • Title: Knowledge-Aware Learning Analytics Infrastructure to Support Smart Education and Learning

    • funding: 2018-2021 JSPS Grant-in-Aid for Scientific Research (B) (17,940,000円)

    • project number: 20H01722

  • Title: 「学習者の自己説明とAIの説明生成の共進化による教育学習支援環境EXAITの研究開発」
    Title in English: “Research and development of an education and learning support environment EXAIT by co-evolution of learner’s self-explanation and AI explanation generation”

    • funding: 2020-2022 NEDO

    • project number: JPNP20006 

Awards

• • APSCE Early Career Researcher Award, 2023

  • IEEE TCLT Early Career Researcher Award in Learning Technologies, 2023

  • ICT innovation Award, Kyoto University, 2020

  • Mashruwala Award for Educational Innovation, 2017

  • MHRD Postgraduate Assistantship, 2013-2017

  • Diagrams Graduate Symposium travel funding, 2016

  • APSCE merit scholarship, 2015 

Discussions and Teaching

I am interested in discussions related to  Educational Technology, Learning Analytics, Data Visualisation and HCI.

• • Spring 2021, 2022 - Educational Data Analytics and Visualisation

  • Fall 2020, 2021, 2022 - Educational Informatics, lecture on Supporting Teaching & Learning Practices through Analytics

  • Fall 2020, 2021, 2022 - Human Interface, lecture on Supporting Teaching Practices through Interactive Platforms

  • Open-Course Ware Material - Supporting Evidence-based Teaching-learning practices with Technology