[Cheonan (South Chungcheong Province) = E-Daily Reporter Cho Min-Jung ] As soon as the professor began his lecture, a large digital information display (DID) installed at the back of the classroom started showing analysis results indicating that the professor was speaking at a rate of 46.7 words per minute. About halfway through the lecture, a graph generated by artificial intelligence (AI) began to rise sharply, alerting the professor that the students’ concentration was waning.

This “AI Learning Analytics Lab,” established at the Korea University of Technology and Education, uses AI to analyze not only the professor’s behavior but also the students’ movements in real time. Located on the university’s First Campus in Cheonan, South Chungcheong Province, it is a futuristic educational facility and one of the most advanced hybrid classrooms among four-year universities in South Korea. To move away from traditional rote-learning lectures and enhance the professor’s teaching effectiveness, the lab makes full use of high-performance computer vision and speech-to-text (STT) technologies.

During an E-Daily visit to the AI Learning Analysis Lab at Korea University of Technology and Education on the 17th, large dashboards were installed at the front and back of the classroom, allowing for real-time viewing of AI analysis results. These results are generated by six cameras mounted on the classroom ceiling that analyze behavioral and audio data. For example, if a student’s gaze frequently shifts from side to side, a graph indicates that their concentration has waned. Professors can then adjust their teaching strategies in real time.

Toward the end of the lecture, the AI synthesizes the entire lecture content to identify 6–7 key terms and clearly summarizes how many times the professor mentioned each one. When students select a keyword through the app, a quiz corresponding to that term is automatically generated; if they answer incorrectly, the AI provides a refresher on the concept. If students frequently get a particular quiz question wrong, the AI identifies the confusing points and explains them again. Students can also ask questions using the chatbot built into the app while the lecture is in progress.

In the second semester of 2024, Hanbat National University piloted the AI Learning Analytics Lab for four courses, including “Introduction to Big Data” and “Data Visualization.” The program has now expanded to cover about 10 fields in engineering, the humanities, and general education, and the scope of application continues to grow. A university official explained, “We enhanced the effectiveness of classes by utilizing data on students’ learning patterns based on their majors and class formats (theory, lab, and interdisciplinary discussion),” adding, “We have built a data-driven educational model by providing professors with objective metrics for improving their courses and students with personalized learning feedback.”

Professor Byun Hae-won of the School of Future Convergence, who has been conducting classes in the AI Learning Analytics Lab since last year, explained, “Real-time data analysis and AI-powered interactive engagement have made it possible to provide close, personalized guidance tailored to each individual student.” She added, “Student satisfaction with the classes has increased by about 20% compared to traditional classes, and we can now immediately incorporate student achievement and activity log data into the design of future classes.”

This year, Korea University of Technology and Education will significantly expand its facilities by establishing seven additional AI Learning Analytics Labs, bringing the total to 10. The university plans to validate the effectiveness of the AI Learning Analytics Labs as test beds and eventually expand them into a lifelong vocational skills development training system.

Yoo Gil-sang, President of Korea University of Technology and Education, stated, “The AI Learning Analytics Labs represent the highest level of cutting-edge infrastructure among four-year universities in Korea that have proven the effectiveness of data-driven educational innovation.” He added, “Serving as a data compass for professors to independently improve course quality and as an educational innovation that supports seamless, personalized growth for students, we will take the lead in cultivating national AI talent for undergraduates and working professionals alike.”