相关论文: edBB-Demo: Biometrics and Behavior Analysis for On…
We present a platform for student monitoring in remote education consisting of a collection of sensors and software that capture biometric and behavioral data. We define a collection of tasks to acquire behavioral data that can be useful…
In this study we estimate the heart rate from face videos for student assessment. This information could be very valuable to track their status along time and also to estimate other data such as their attention level or the presence of…
This paper presents a two-year research project focused on developing AI-driven measures to analyze classroom dynamics, with particular emphasis on teacher actions captured through multimodal sensor data. We applied real-time data from…
With the increase of distance learning, in general, and e-learning, in particular, having a system capable of determining the engagement of students is of primordial importance, and one of the biggest challenges, both for teachers,…
In modern online learning, understanding and predicting student behavior is crucial for enhancing engagement and optimizing educational outcomes. This systematic review explores the integration of biosensors and Multimodal Learning…
Over the last decade, e-learning has revolutionized how students learn by providing them access to quality education whenever and wherever they want. However, students often get distracted because of various reasons, which affect the…
Engagement, which links to attentional, emotional, and cognitive dimensions, plays an important role in learning. In online and video-based learning environments, learners often need to regulate their own interactions with instructional…
Student disengagement in online learning has become a critical challenge, particularly post-pandemic. This review explores deep learning techniques used to detect disengagement, emphasizing computer vision and affective computing as…
This work introduces an innovative method for estimating attention levels (cognitive load) using an ensemble of facial analysis techniques applied to webcam videos. Our method is particularly useful, among others, in e-learning…
This work introduces SMARTe-VR, a platform for student monitoring in an immersive virtual reality environment designed for online education. SMARTe-VR aims to collect data for adaptive learning, focusing on facial biometrics and learning…
This study presents high-throughput, real-time multi-agent affective computing framework designed to enhance classroom learning through emotional state monitoring. As large classroom sizes and limited teacher student interaction…
This work presents the IMPROVE dataset, a multimodal resource designed to evaluate the effects of mobile phone usage on learners during online education. It includes behavioral, biometric, physiological, and academic performance data…
Investigating children's embodied learning in mixed-reality environments, where they collaboratively simulate scientific processes, requires analyzing complex multimodal data to interpret their learning and coordination behaviors. Learning…
In this paper, a novel dataset is introduced, designed to assess student attention within in-person classroom settings. This dataset encompasses RGB camera data, featuring multiple cameras per student to capture both posture and facial…
This work presents a new multimodal system for remote attention level estimation based on multimodal face analysis. Our multimodal approach uses different parameters and signals obtained from the behavior and physiological processes that…
User experience research often uses surveys and interviews, which may miss subconscious user interactions. This study explores eye-tracking and biometric feedback as tools to assess user engagement and cognitive load in digital interfaces.…
In this paper, we propose a novel technique for measuring behavioral engagement through students' actions recognition. The proposed approach recognizes student actions then predicts the student behavioral engagement level. For student…
In this article, we present a Web-based System called M2LADS, which supports the integration and visualization of multimodal data recorded in learning sessions in a MOOC in the form of Web-based Dashboards. Based on the edBB platform, the…
This work investigates the use of multimodal biometrics to detect distractions caused by smartphone use during tasks that require sustained attention, with a focus on computer-based online learning. Although the methods are applicable to…
The significance of emotion detection is increasing in education, entertainment, and various other domains. We are developing a system that can identify and transform facial expressions into emojis to provide immediate feedback.The project…