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E‐learning, also known as online learning or technology enhanced learning, needs to provide more heterogeneous learning including not only Web‐based courses and virtual classrooms but also remote labs with an affective recognition system. These latter allow students to interact with real experiments conducted from a distance with real‐time facial expression recognition using a webcam. However, multiple systems do not include this kind of learning. Thus, students' motivation, interest, and learning might be negatively affected since there can be no emotional interaction without “on demand” learning. This work analyzes the impact of students' emotions to enhance the learning experience in two aspects: (i) filling the existing gaps of students and (ii) improving the usability and readability of the platform. The overall goal of our research is to build a novel intelligent tutoring system, called “LabTutor,” adapted to the profile of every student. It aims to serve as an experienced teacher for students who access and perform experiments on real laboratory equipment in the field of engineering education.

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