I am really surprised! We are very grateful to all the professors who reviewed our proposal. I think that the reviewers were very busy at the end of the year and the beginning of the new year. I will do my best to contribute to solving problems in the field of education, and to actively disseminate the results both domestically and internationally, so that we do not fall short of their judgment. Thank you very much.
The research selected this time is in the field of learning analytics, and I thought that in order to understand learning behavior, we need to review the logs in the first place. This research is to develop and evaluate a learning analytics infrastructure that will lead to improvements in learning by recapturing the learning logs and utilizing the recaptured logs.
Fundamental Research A: Development and evaluation of a learning analytics infrastructure based on a model for improving learning behavior (2022 – 2025)
I have felt empirically through my long experience in learning analytics research that although dashboard research is a major field in learning analytics research, it is not enough to just create a dashboard, evaluate it, and improve the practice by using various algorithms. In the past year or two, I have finally come to realize that. A dashboard is only a thing when there is a platform or content delivery infrastructure, such as a learning management system, where the original learning action takes place, and it is merely a visualization of the action within that main system. What I am saying is that there are many things that can’t be done without considering the way the original learning management system, content delivery infrastructure, and other platforms are designed, and after proceeding with learning analytics, key learning behaviors become visible, and the platforms themselves need to be reviewed. There are many cases where we need to review the platform itself. However, it is not easy to revise the platform since learning analytics is often done with the platform.
The point of this project is to focus on this point and to think about the opposite, rather than conducting unidirectional research to simply create a dashboard that visualizes learning behavior on the platform. We want to create an infrastructure that allows us to turn the cycle of improving learning analytics by thinking about how the infrastructure should be designed and improved based on the learning analytics-related results representing dashboard development and evaluation.
We are pleased to have Prof. Goda of Kumamoto University, who specializes in instructional design and evaluation, and Prof. Yuta Taniguchi of Kyushu Unibersity, who specializes in machine learning with a focus on natural language processing, continue to participate in the project from Infrastructure B. In addition, Dr. Lu Min, who specializes in spatial informatics and has contributed to the development of our university’s learning analytics infrastructure, and Dr. Fumiya Okubo, who specializes in neural networks, have newly joined us, and we will proceed with our research plan for four years. We had hoped to have Dr. Shimada, who has always been a great help to us, join us, but he has decided to join us as a research collaborator because of his lack of availability.
I would like to promote good system design, development, and evaluation with my co-researchers and collaborators, and to advance research that can contribute to solving educational issues from the perspective of learning analytics. I will also make sure to produce research results that meet the expectations of the judges and everyone else.
Thank you for your continuous support.