相关论文: Detecting Behavioral Engagement of Students in the…
We propose a multimodal approach for detection of students' behavioral engagement states (i.e., On-Task vs. Off-Task), based on three unobtrusive modalities: Appearance, Context-Performance, and Mouse. Final behavioral engagement states are…
In this paper, we introduce a new dataset for student engagement detection and localization. Digital revolution has transformed the traditional teaching procedure and a result analysis of the student engagement in an e-learning environment…
Understanding student behavior in the classroom is essential to improve both pedagogical quality and student engagement. Existing methods for predicting student engagement typically require substantial annotated data to model the diversity…
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…
The study of student engagement has attracted growing interests to address problems such as low academic performance, disaffection, and high dropout rates. Existing approaches to measuring student engagement typically rely on survey-based…
Considering learner engagement has a mutual benefit for both learners and instructors. Instructors can help learners increase their attention, involvement, motivation, and interest. On the other hand, instructors can improve their…
This study examines whether including more contextual information in data analysis could improve our ability to identify the relation between students' online learning behavior and overall performance in an introductory physics course. We…
Student engagement is a key construct for learning and teaching. While most of the literature explored the student engagement analysis on computer-based settings, this paper extends that focus to classroom instruction. To best examine…
Understanding and enhancing student engagement through digital platforms is critical in higher education. This study introduces a methodology for quantifying engagement across an entire module using virtual learning environment (VLE)…
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,…
Many studies in educational data mining address specific learner groups, such as first-in-family to attend Higher Education, or focus on differences in characteristics such as gender or ethnicity, with the aim of predicting performance and…
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…
Measuring online behavioural student engagement often relies on simple count indicators or retrospective, predictive methods, which present challenges for real-time application. To address these limitations, we reconceptualise an existing…
Understanding reader behaviors such as skimming, deep reading, and scanning is essential for improving educational instruction. While prior eye-tracking studies have trained models to recognize reading behaviors, they often rely on…
Student engagement is an important factor in meeting the goals of virtual learning programs. Automatic measurement of student engagement provides helpful information for instructors to meet learning program objectives and individualize…
In the context of higher education's evolving dynamics post-COVID-19, this paper assesses the impact of new pedagogical incentives implemented in a first-year undergraduate computing module at University College London. We employ a mixed…
In this study, we investigate the combination of indicators, including performance, behavioral engagement, and emotional engagement, to identify students experiencing difficulties. We analyzed data from two primary sources: digital traces…
Analyzing human affect is vital for human-computer interaction systems. Most methods are developed in restricted scenarios which are not practical for in-the-wild settings. The Affective Behavior Analysis in-the-wild (ABAW) 2021 Contest…
The paper develops datasets and methods to assess student participation in real-life collaborative learning environments. In collaborative learning environments, students are organized into small groups where they are free to interact…
In-person instruction for professional development or other types of workplace training provides a social environment and immediate feedback mechanisms that typically ensure all participants are successful. Online, self-paced instruction…