Research on Multimodal Data Collection and Analysis for Learning Activities

In educational settings, we classify and predict learners by utilizing multimodal data such as voice and images. Using various log data, we analyze student engagement, focus, and emotions, and evaluate teaching and learning activities through artificial intelligence.

Development of Competency Assessment Methods Based on Learning Data and Long-Term Data Collection Research

We develop methods and tools for assessing future competencies in cognitive, affective areas, and behavioral agency using multimodal data. We also collect and analyze teaching and learning activity data over the long term.

Research on Cognitive Diagnostic Assessment System

Centered around MathCoDi, we develop a student detailed diagnostic system using cognitive diagnostic assessment algorithms. We also develop and operate a formative assessment platform based on cognitive diagnosis that can be utilized in classroom activities.

Development of Learning Data Collection Platform and Support for Data Analysis Research

We design and operate online and offline data collection pipelines that can be used for collecting learning data.