I am rwito
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 they operate 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 about the teaching and learning process when supported by technology. 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 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.
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
As Principal Investigator (PI)
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
As Co-Principle Investigator (Co-PI)
Title: Extraction and Use of Highly Explainable and Transferable Indicators for AI in Education
funding: 2023-2025 JSPS Grant-in-Aid for Scientific Research (B) (currently allocating 円)
project number: pending
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 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
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