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The main purpose of the study was to explore how different augmented 3D visualizations may affect the learning of complex science concepts using the eye tracking method. An Augmented Reality (AR) learning system incorporated with different 3D visualizations was developed to assist conceptual learning in the topic of "molecular shapes." Learners' visual attention during the AR learning was recorded using a mobile eye tracking system. Participants were 32 10th grade students. Pre- and post-tests were used to assess students' learning achievements. Learners were grouped into low and high achievers according to the posttest result. To analyze the associations between learners' visual attentions and learning achievements, correlation, t -test, correlation, and regression analyses were applied. Additionally, we conducted lag sequential analysis (LSA) to compare the visual transitions of different groups of achievers. The results showed that learners' conceptual understanding was improved after the AR learning activity. Among the different 3D visualizations, learners attended more to the static and dynamic types in the basic learning stage and to the static and interactive types in the advanced learning stage. Attention to the 3D static model was found to associate more to the attention to the interactive type. The correlation and regression analyses found that the cognitive effort to integrate information about the static 3D model was the key predictor for the learning achievement. LSA showed that high achievers displayed a higher chance of looking back to the static 3D model from other AOIs. The visual pattern analysis suggested that a guidance to connect information delivered by the static and the animated visual representations is necessary for complex conceptual learning. • Visual attention to the augmented 3D static objects predicted learning achievement. • Visual attentions to the 3D static and interactive models were highly correlated. • Low achievers attended more to the interactive 3D objects. • High achievers looked back to the static 3D object from other AOIs more frequently. • High achievers made more sequential transitions between text and 3D objects. [ABSTRACT FROM AUTHOR]

The purpose of the study was to investigate university learners' visual attention during a PowerPoint (PPT) presentation on the topic of “Dinosaurs” in a real classroom. The presentation, which lasted for about 12–15 min, consisted of 12 slides with various text and graphic formats. An instructor gave the presentation to 21 students whose eye movements were recorded by the eye tracking system. Participants came from various science departments in a national university in Taiwan, of which ten were earth-science majors (ES) and the other 11 were assigned to the non-earth-science group (NES). Eye movement indicators, such as total time spent on the interest zone, fixation count, total fixation duration, percent time spent in zone, etc., were abstracted to indicate their visual attention. One-way ANOVA as well as t-test analysis was applied to find the associations between the eye movement data and the students' background as well as different formats of PPT slides. The results showed that the students attended significantly more to the text zones on the PPT slides and the narrations delivered by the instruction. Nevertheless, the average fixation duration, indicating the average information processing time, was longer on the picture zones. In general, the ES students displayed higher visual attention than the NES students to the text zones, but few differences were found for the picture zones. When the students viewed those slides containing scientific hypotheses, the difference in attention distributions between the text and pictures reduced. Further analyses of fixation densities and saccade paths showed that the ES students were better at information decoding and integration. [Copyright &y& Elsevier]

This study employed an eye-tracking technique to examine students’ visual attention when solving a multiple-choice science problem. Six university students participated in a problem-solving task to predict occurrences of landslide hazards from four images representing four combinations of four factors. Participants’ responses and visual attention were recorded by an eye tracker. Participants were asked to think aloud during the entire task. A 4 (options) × 4 (factors) repeated measures design, two paired t-tests and effect sizes analyses were conducted to compare the fixation duration between chosen and rejected options and between relevant and irrelevant factors. Content analyses were performed to analyze participants’ responses and think aloud protocols and to examine individual’s Hot Zone image. Finally, sequential analysis on fixated LookZones was further utilized to compare the scan patterns between successful and unsuccessful problem solvers. The results showed that, while solving an image-based multiple-choice science problem, students, in general, paid more attention to chosen options than rejected alternatives, and spent more time inspecting relevant factors than irrelevant ones. Additionally, successful problem solvers focused more on relevant factors, while unsuccessful problem solvers experienced difficulties in decoding the problem, in recognizing the relevant factors, and in self-regulating of concentration. Future study can be done to examine the reliability and the usability of providing adaptive instructional scaffoldings for problem solving according to students’ visual attention allocations and transformations in a larger scale. Eye-tracking techniques are suggested to be used to deeply explore the cognitive process during e-learning and be applied to future online assessment systems. [Copyright &y& Elsevier]