Just like a detective following the trail of clues, teachers can now use eye-tracking devices to visualize where students’ gaze goes during online lectures. By analyzing this gaze data, teachers can gain insights into students’ level of comprehension and engagement with the lecture material. Two studies were conducted to explore the relationship between gaze measures and comprehension. In the first study, 36 students were eye-tracked while watching a lecture, and their gaze patterns correlated with their comprehension scores. The second study involved 50 participants who viewed visualizations of students’ gaze data and successfully predicted learners’ comprehension levels. The findings suggest that even non-experts in eye-tracking can utilize these visualizations to predict student understanding. Different visualization techniques were also examined, showcasing minor variations in accuracy. Future research should focus on evaluating how teachers can leverage this information to enhance student learning. To dive deeper into this fascinating research, don’t forget to check out the full article!

Abstract
In online lectures, unlike in face-to-face lectures, teachers lack access to (nonverbal) cues to check if their students are still “with them” and comprehend the lecture. The increasing availability of low-cost eye-trackers provides a promising solution. These devices measure unobtrusively where students look and can visualize these data to teachers. These visualizations might inform teachers about students’ level of “with-me-ness” (i.e., do students look at the information that the teacher is currently talking about) and comprehension of the lecture, provided that (1) gaze measures of “with-me-ness” are related to comprehension, (2) people not trained in eye-tracking can predict students’ comprehension from gaze visualizations, (3) we understand how different visualization techniques impact this prediction. We addressed these issues in two studies. In Study 1, 36 students watched a video lecture while being eye-tracked. The extent to which students looked at relevant information and the extent to which they looked at the same location as the teacher both correlated with students’ comprehension (score on an open question) of the lecture. In Study 2, 50 participants watched visualizations of students’ gaze (from Study 1), using six visualization techniques (dynamic and static versions of scanpaths, heatmaps, and focus maps) and were asked to predict students’ posttest performance and to rate their ease of prediction. We found that people can use gaze visualizations to predict learners’ comprehension above chance level, with minor differences between visualization techniques. Further research should investigate if teachers can act on the information provided by gaze visualizations and thereby improve students’ learning.

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