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, researchers and policy makers. Here, we present a system to detect the engagement level of the students. It uses only information provided by the typical built-in web-camera present in a laptop computer, and was designed to work in real time. We combine information about the movements of the eyes and head, and facial emotions to produce a concentration index with three classes of engagement: "very engaged", "nominally engaged" and "not engaged at all". The system was tested in a typical e-learning scenario, and the results show that it correctly identifies each period of time where students were "very engaged", "nominally engaged" and "not engaged at all". Additionally, the results also show that the students with best scores also have higher concentration indexes.

翻译：随着远程学习（尤其是电子学习）的普及，构建能够判定学生投入度的系统至关重要，这已成为教师、研究人员及政策制定者面临的最大挑战之一。本文提出一种用于检测学生学习投入度水平的系统。该系统仅利用笔记本电脑内置标准摄像头提供的视觉信息，并设计为实时运行。我们将眼动、头部运动以及面部情绪信息进行融合，生成一个包含"高度投入"、"基本投入"和"完全不投入"三类投入度的专注度指标。系统在典型电子学习场景中完成测试，结果显示其能准确识别学生处于"高度投入"、"基本投入"和"完全不投入"状态的时间段。此外，研究结果还表明，成绩最优学生对应的专注度指标也相对更高。