Work

Real-time assessment of educational effectiveness using computer vision: A methodological framework demonstrated in a case study in Yerevan State University

Year: 2025

Type: article

Abstract: This article presents a novel approach to measuring the effectiveness of learning processes in real time, based on computer vision emotion detection, thereby dispelling the need for traditional student feedback systems. Conventional evaluations conducted at the end of coursework often provide delayed and subjective feedback that does not accurately represent the learning process as it unfolds. Distinctly, our approach continuously captures and analyzes students' affective reactions during instruction and provides a real-time understanding of their level of engagement. With the DeepFace library, we processed facial expression data collected from 36 students of Yerevan State University attending a video-based e-course on general psychology. Classification of expressions was largely based on Ekman's (2014) theory, with the addition of the neutral emotional state to represent the model's special characteristics, which had been conceived as the absence of emotion (represented by a neutral facial expression). This model enables educators to identify concrete pedagogical examples that are linked with various affective responses, thus informing a more subtle and empirically based assessment of teaching effectiveness. Although the methodology is framed as a case study at Yerevan State University, its usefulness extends well beyond this specific setting. By making some technical modifications, the suggested approach can be economically applied in varied learning environments, such as conventional face-to-face and non-computerized classrooms. The results provide a foundation for adaptive instructional design and promote the creation of learning environments that are not just emotionally supportive but also pedagogically sound.

Source: Social Sciences & Humanities Open

DOI: 10.1016/j.ssaho.2025.102014

Authors: Elina Asriyan, Ruben Gevorgyan, Hasmik Sargsyan, Alber Makaryan, Sevada Aghasyan

Institution: Yerevan State University

Language: English

Topic: Emotion and Mood Recognition

Subfield: Experimental and Cognitive Psychology

Field: Psychology

Domain: Social Sciences

SDG: Quality education

Open Access status: gold

Estimated APC paid: $1,180