This was quite a surprise, but our Yamada Lab student, Chen, was selected for one of the Best Paper Awards at the international conference CELDA 2020. There were three awards given, and this was one of them. Chen seemed surprised as well… and honestly, so was I. I never expected us to win. I would like to thank all the reviewers and committee members. The award-winning paper is…

Chen, L., Lu, M., Goda, Y., Shimada, A., and Yamada, M. (2020). Factors of the use of learning analytics dashboard that affect metacognition, Proceedings of CELDA 2020, pp.295-302

This is a result of the AIP Acceleration Research (selected in FY2019) project, led by Professor Shimada of our university’s Graduate School of Information Science and Electrical Engineering, with me serving as the primary co-researcher. It summarizes the formative evaluation of the “Reading path” feature of Metaboard, which is designed, developed, and evaluated by the education team I lead. We developed this feature to help students compare their own learning activities with those of the entire class, identify what they are missing, and use the learning behaviors of others to improve their own studies.

Due to the COVID-19 pandemic, many educational institutions, regardless of school type, were forced to conduct classes online. In face-to-face classes, students could consult with each other, asking things like, “Did you understand this course material? What does this part mean?”, “Where did you find that item?”, or “Did we cover this point on the slide before?”, and learn through such interactions. While “Reading path” cannot fully replicate that face-to-face environment (laughs), at least in a synchronous remote environment, it allows students taking the same class to see how others are reading the materials, which slides they are focusing on, and what points everyone is paying attention to, enabling them to compare these with their own and use them as a reference for their learning. It has been very well received, and unexpectedly, we even received feedback that it provided a “sense of security.” Of course, this system cannot cover everything, and we position it strictly as a support feature. There are still many challenges ahead. However, aside from the research aspect, I am very happy that it has been of help to students who were feeling anxious about online learning, and I would like to continue developing support systems based on Learning Analytics.

In addition to receiving feedback from students that it was useful for their classes, receiving the Best Paper Award is a great honor, as it means our research has been recognized internationally. The AIP Acceleration Research project is being conducted in collaboration between the information science team led by Professor Shimada, the library team (Professor Uchiyama) involved in learning resource management research, and my education team. We will continue to develop high-quality systems, advance our research, and create tools that can support students’ learning.

Thank you for your continued support.