Film is ubiquitous, but the processes that guide viewers’ attention while viewing film narratives are poorly understood. In fact, many film theorists and practitioners disagree on whether the film stimulus (bottom-up) or the viewer (top-down) is more important in determining how we watch movies. Reading research has shown a strong connection between eye movements and comprehension, and scene perception studies have shown strong effects of viewing tasks on eye movements, but such idiosyncratic top-down control of gaze in film would be anathema to the universal control mainstream filmmakers typically aim for. Thus, in two experiments we tested whether the eye movements and comprehension relationship similarly held in a classic film example, the famous opening scene of Orson Welles’ Touch of Evil (Welles & Zugsmith, Touch of Evil, 1958). Comprehension differences were compared with more volitionally controlled task-based effects on eye movements. To investigate the effects of comprehension on eye movements during film viewing, we manipulated viewers’ comprehension by starting participants at different points in a film, and then tracked their eyes. Overall, the manipulation created large differences in comprehension, but only produced modest differences in eye movements. To amplify top-down effects on eye movements, a task manipulation was designed to prioritize peripheral scene features: a map task. This task manipulation created large differences in eye movements when compared to participants freely viewing the clip for comprehension. Thus, to allow for strong, volitional top-down control of eye movements in film, task manipulations need to make features that are important to narrative comprehension irrelevant to the viewing task. The evidence provided by this experimental case study suggests that filmmakers’ belief in their ability to create systematic gaze behavior across viewers is confirmed, but that this does not indicate universally similar comprehension of the film narrative.Electronic supplementary materialThe online version of this article (doi:10.1186/s41235-017-0080-5) contains supplementary material, which is available to authorized users.

What role do moment‐to‐moment comprehension processes play in visual attentional selection in picture stories? The current work uniquely tested the role of bridging inference generation processes on eye movements while participants viewed picture stories. Specific components of the Scene Perception and Event Comprehension Theory ( SPECT ) were tested. Bridging inference generation was induced by manipulating the presence of highly inferable actions embedded in picture stories. When inferable actions are missing, participants have increased viewing times for the immediately following critical image (Magliano, Larson, Higgs, & Loschky, 2016 ). This study used eye‐tracking to test competing hypotheses about the increased viewing time: (a) Computational Load : inference generation processes increase overall computational load, producing longer fixation durations; (b) Visual Search : inference generation processes guide eye‐movements to pick up inference‐relevant information, producing more fixations. Participants had similar fixation durations, but they made more fixations while generating inferences, with that process starting from the fifth fixation. A follow‐up hypothesis predicted that when generating inferences, participants fixate scene regions important for generating the inference. A separate group of participants rated the inferential‐relevance of regions in the critical images, and results showed that these inferentially relevant regions predicted differences in other viewers’ eye movements. Thus, viewers’ event models in working memory affect visual attentional selection while viewing visual narratives.

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In a previous study, DeLeeuw and Mayer (2008) found support for the triarchic model of cognitive load (Sweller, Van Merriënboer, & Paas, 1998, 2019) by showing that three different metrics could be used to independently measure 3 hypothesized types of cognitive load: intrinsic, extraneous, and germane. However, 2 of the 3 metrics that the authors used were intrusive in nature because learning had to be stopped momentarily to complete the measures. The current study extends the design of DeLeeuw and Mayer (2008) by investigating whether learners’ eye movement behavior can be used to measure the three proposed types of cognitive load without interrupting learning. During a 1-hr experiment, we presented a multimedia lesson explaining the mechanism of electric motors to participants who had low prior knowledge of this topic. First, we replicated the main results of DeLeeuw and Mayer (2008), providing further support for the triarchic structure of cognitive load. Second, we identified eye movement measures that differentiated the three types of cognitive load. These findings were independent of participants’ working memory capacity. Together, these results provide further evidence for the triarchic nature of cognitive load (Sweller et al., 1998, 2019), and are a first step toward online measures of cognitive load that could potentially be implemented into computer assisted learning technologies.

Cognitive load theory (CLT) provides us guiding principles in the design of learning materials. CLT differentiates three different kinds of cognitive load --intrinsic, extraneous and germane load. Intrinsic load is related to the learning goal, extraneous load costs cognitive resources but does not contribute to learning. Germane load can foster learning. Objective methods, such as eye movement measures and EEG have been used measure the total cognitive load. Very few research studies, if any, have been completed to measure the three kinds of load separately with physiological methods in a continuous manner. In this current study, we will show how several eye-tracking based parameters are related to the three kinds of load by having explicit manipulation of the three loads independently. Participants having low prior knowledge regarding the learning material participated in the study. Working memory capacity was also measured by an operation memory span task.

Viewers' attentional selection while looking at scenes is affected by both top-down and bottom-up factors. However, when watching film, viewers typically attend to the movie similarly irrespective of top-down factors-a phenomenon we call the tyranny of film. A key difference between still pictures and film is that film contains motion, which is a strong attractor of attention and highly predictive of gaze during film viewing. The goal of the present study was to test if the tyranny of film is driven by motion. To do this, we created a slideshow presentation of the opening scene of Touch of Evil. Context condition participants watched the full slideshow. No-context condition participants did not see the opening portion of the scene, which showed someone placing a time bomb into the trunk of a car. In prior research, we showed that despite producing very different understandings of the clip, this manipulation did not affect viewers' attention (i.e., the tyranny of film), as both context and no-context participants were equally likely to fixate on the car with the bomb when the scene was presented as a film. The current study found that when the scene was shown as a slideshow, the context manipulation produced differences in attentional selection (i.e., it attenuated attentional synchrony). We discuss these results in the context of the Scene Perception and Event Comprehension Theory, which specifies the relationship between event comprehension and attentional selection in the context of visual narratives.

Research has shown that students' responses to conceptual questions correlate with their eye movements. However, to what extent is it possible to predict whether a particular learner might answer a question correctly by monitoring their eye movements in real time? To answer this question, we used spatialtemporal eye-movement data from about 400 participants, as well as their responses to four conceptual physics questions with diagrams. Half of these data were used as a training set for a machine learning algorithm (MLA) that would predict the correctness of students' responses to these questions. The other half of the data were used as a test set to determine the performance of the MLA in terms of the accuracy of the prediction. We will discuss the results of our study with specific attention to the prediction accuracy of the MLA under different conditions.

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