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Image and Media Understanding Lab
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The lab uses AI to analyze learning data, images, and time series.
AboutAbout the lab
Understanding and supporting people and society through data and AI.
The Image and Media Understanding Lab works on research into the analysis and use of learning and educational data, time-series data analysis, and image and media understanding.
Through data analysis and AI technology, the lab aims to create new methods that contribute to understanding and supporting people and society.
The research page introduces the lab's work by field: learning analytics, time-series forecasting, AI that supports people, and image processing.
Key terms
- Learning Analytics
- A research field that analyzes data on learning and education and uses it to improve teaching and learning
- Metacognition
- The function of self-awareness regarding how accurately one recognizes one's own state of understanding
- LLM
- Short for large language model. A type of AI that understands and generates text
NewsLab news
View More ↗ResearchResearch themes
The lab studies methods for supporting people's learning and behavior by analyzing learning logs, video, and time-series data with AI. The research page presents the work by field: learning analytics, time-series forecasting, AI that supports people, and image processing.
*Illustrative imageAnalyzing Learning Behavior in Connection with Course Content
The lab studies a method that links differences in learning behavior to the context of which part of the course content they relate to, and presents them in a form that is easy for instructors to understand. LLMs are used only to generate explanations, aiming for feedback that preserves the grounds of the analysis.
*Illustrative imageAdaptive Learning Support Based on Metacognition
The lab studies methods for capturing how accurately learners recognize their own state of understanding and using this in learning support. It estimates knowledge awareness from written reflections and test results, aiming for individualized feedback that responds to overconfidence or lack of confidence.
*Illustrative imageVisualizing Learning Behavior in Agricultural Practical Training
This research captures learners' activities during agricultural practical training so that instructors can use them for reflection and for improving their teaching. Using 360-degree cameras and wearable cameras, it estimates and visualizes learners' positions, work time, and work state.
*Illustrative imageAnalysis for an Overview of the Entire Curriculum
This research grasps the connections and progress of learning across the entire curriculum, not only in individual classes. It overlays relationships between courses and individual learning status on a curriculum map for visualization, aiming for an environment that can be used for study planning and reflection.
MembersFaculty
The members of the Image and Media Understanding Lab consist of faculty members, technical staff, collaborators, and doctoral, master's, and undergraduate students.As of 2026
- ProfessorAtsushi Shimada
- Associate ProfessorFumiya Okubo
- Assistant ProfessorGen Li
VoicesStudent voices
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Report an errorAbout the images
The top and research theme images are illustrative and were not taken at the lab. They are cropped from Wikimedia Commons images. Cropped CC BY-SA images are provided under the same CC BY-SA license as the original (version shown on each line).
- Top image: “Moskovskaya” Artyom Svetlov / CC BY-SA 4.0 (cropped)
- Analyzing Learning Behavior in Connection with Course Content: “E-learning and Virtual Learning Environment (VCL), blended learning framework and model” Khanb / CC BY-SA 3.0 (cropped)
- Adaptive Learning Support Based on Metacognition: “Learning Engineering is Multidisciplinary” Jgoodell2 / CC BY-SA 4.0 (cropped)
- Visualizing Learning Behavior in Agricultural Practical Training: “Australian Horse Training, Risebridge Farm, Goudhurst - geograph.org.uk - 3953980” Danny P Robinson / CC BY-SA 2.0 (cropped)
- Analysis for an Overview of the Entire Curriculum: “Learning Analytics -oucel15 keynote by @houshuang ( )” Giulia Forsythe / CC0 (cropped)
- Related lab (AI Education Lab): “Online learning img” Oconnoras / CC BY-SA 4.0 (cropped)
- Related lab (Human Data Interaction Lab): “School of Data Science - University of Virginia - terrace” School of Data Science at the University of Virginia / CC BY 4.0 (cropped)
- Related lab (Computer Vision, Graphics, and VR Lab): “Einsatz von Augmented Reality im Service von HAHN Automation” HAHN Group / CC BY-SA 4.0 (cropped)
- Related lab (Behavior Informatics Lab): “The scope of embodied cognition fr” John J. Madrid / CC BY 4.0 (cropped)
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