Related Experiment Video
Updated: Jul 30, 2025

Author Spotlight: Addressing Technical and Subjective Challenges in Measuring Classroom Attention
Published on: December 15, 2023
A Real-Time Learning Analytics Dashboard for Automatic Detection of Online Learners' Affective States
Mohammad Nehal Hasnine1, Ho Tan Nguyen1, Thuy Thi Thu Tran1
1Research Center for Computing and Multimedia Studies, Hosei University, Tokyo 102-8160, Japan.
Abstract:
Students' affective states describe their engagement, concentration, attitude, motivation, happiness, sadness, frustration, off-task behavior, and confusion level in learning. In online learning, students' affective states are determinative of the learning quality. However, measuring various affective states and what influences them is exceedingly challenging for the lecturer without having real interaction with the students. Existing studies primarily use self-reported data to understand students' affective states, while this paper presents a novel learning analytics system called MOEMO (Motion and Emotion) that could measure online learners' affective states of engagement and concentration using emotion data. Therefore, the novelty of this research is to visualize online learners' affective states on lecturers' screens in real-time using an automated emotion detection process. In real-time and offline, the system extracts emotion data by analyzing facial features from the lecture videos captured by the typical built-in web camera of a laptop computer. The system determines online learners' five types of engagement ("strong engagement", "high engagement", "medium engagement", "low engagement", and "disengagement") and two types of concentration levels ("focused" and "distracted"). Furthermore, the dashboard is designed to provide insight into students' emotional states, the clusters of engaged and disengaged students', assistance with intervention, create an after-class summary report, and configure the automation parameters to adapt to the study environment.
More Related Videos
12:55Multimodal Protocol for Assessing Metacognition and Self-Regulation in Adults with Learning Difficulties
Published on: September 27, 2020
10:43Eye-tracking Technology and Data-mining Techniques used for a Behavioral Analysis of Adults engaged in Learning Processes
Published on: June 10, 2021
Related Concept Videos
Cognitive Learning
E. C. Tolman's theory of purposive behavior emphasizes that much behavior is goal-directed. He argued that to understand behavior, we must look at the entire sequence of actions leading to a goal. For instance, high school students study hard, not just due to past reinforcement but also to achieve the goal of getting into a good college.
Tolman introduced the idea that behavior is influenced by...
Metacognition
Observational Learning
Associative Learning
Classical conditioning, also known...
Self-Presentation: Self-Monitoring and Self-Handicapping
Labeling Emotion