This pioneering study explored the eye movement classifications among expert and novice anatomists in a gross anatomy cadaver lab. Participants wore eye-tracking glasses while identifying tagged anatomical structures in a prosected donor body. As expected, our initial findings indicated that participants with greater expertise had shorter completion times. Also, the normalized fixation features of participants showed that as expertise levels increased, there were fewer fixations with shorter durations. This suggests that participants with greater expertise employed distinctive visual attention strategies. We navigated several challenges related to the authentic environment, highlighting the need to explore further improving methodological and data analysis techniques. These preliminary findings have implications for informing pedagogical approaches leveraging digitization without sacrificing the 3D environment.

In this study, we utilize a concurrent mixed methods design to explore the attention patterns and processing strategies of young people as they evaluate socioscientific information on social media. We utilized the screen-based Tobii eye tracker to capture ten 8th and twenty 9th grade student's fixations while they evaluated if climate change information was believable or not. The students then completed a retrospective think aloud to explain their process. We find that it is possible to categorize young people's gaze patterns into heuristic and systematic processing categories, and the think aloud data converges with these categories. Further, while most studies are done with adults in a laboratory, we demonstrate that using an eye tracker with a relatively low sampling frequency makes it possible to capture valid and reliable eye tracking in an ecologically valid setting.

This study presents a novel framework to evaluate the usability and user experience of e-learning platforms, focusing on the Duolingo language learning app. By integrating advanced Natural Language Processing (NLP) techniques such as Large Language Models (LLMs), Latent Dirichlet Allocation (LDA), and sentence embedding models, we identified thirteen key usability and user experience topics from a large dataset of user reviews. Our findings reveal that Duolingo is highly rated since users value its enjoyable learning experiences and effectiveness. However, technical issues, lack of explanations, and frustrating features were identified as areas for improvement. The study demonstrates the effectiveness of our framework in analyzing user feedback at scale, offering valuable insights for improving user experience in e-learning platforms and other domains.

This paper investigates how a virtual human's persuasion attempts influence the user's intentions to perform the recommended behaviors using the Theory of Planned Behavior. The Theory of Planned Behavior suggests that users' attitudes towards the behavior, subjective norms, and perceived behavior control determine user intentions to perform behaviors. Using the Theory of Planned Behavior, we identify the underlying mechanisms of how users' attitudes, subjective norms, and perceived behavior control influence the effectiveness of virtual human's persuasive attempts on user's intentions to perform the behavior. To identify the underlying mechanisms, we conducted an online study with 202 college students. In a between-subjects study, a virtual human persuaded students to use a mental health coping skill using six different persuasion strategies. We present evidence that persuasion strategies influenced the students' perceived behavior control, which further influenced the user intentions to perform the behavior. Additionally, the paper also shows that user personality influenced the effect of persuasion strategies on students' perceived behavior control. This knowledge of underlying mechanisms of how virtual human's persuasion attempts to influence users' intentions to perform the recommended behavior can help in designing effective intelligent virtual humans for persuasion.

It is well established that children's touch and gesture interactions on touchscreen devices are different from those of adults, with much prior work showing that children's input is recognized more poorly than adults? input. In addition, researchers have shown that recognition of touchscreen input is poorest for young children and improves for older children when simply considering their age; however, individual differences in cognitive and motor development could also affect children's input. An understanding of how cognitive and motor skill influence touchscreen interactions, as opposed to only coarser measurements like age and grade level, could help in developing personalized and tailored touchscreen interfaces for each child. To investigate how cognitive and motor development may be related to children's touchscreen interactions, we conducted a study of 28 participants ages 4 to 7 that included validated assessments of the children's motor and cognitive skills as well as typical touchscreen target acquisition and gesture tasks. We correlated participants? touchscreen behaviors to their cognitive development level, including both fine motor skills and executive function. We compare our analysis of touchscreen interactions based on cognitive and motor development to prior work based on children's age. We show that all four factors (age, grade level, motor skill, and executive function) show similar correlations with target miss rates and gesture recognition rates. Thus, we conclude that age and grade level are sufficiently sensitive when considering children's touchscreen behaviors.

This study explored the relationships between eye tracking and traditional usability testing data in the context of analyzing the usability of Algebra Nation™, an online system for learning mathematics used by hundreds of thousands of students. Thirty-five undergraduate students (20 females) completed seven usability tasks in the Algebra Nation™ online learning environment. The participants were asked to log in, select an instructor for the instructional video, post a question on the collaborative wall, search for an explanation of a mathematics concept on the wall, find information relating to Karma Points (an incentive for engagement and learning), and watch two instructional videos of varied content difficulty. Participants’ eye movements (fixations and saccades) were simultaneously recorded by an eye tracker. Usability testing software was used to capture all participants’ interactions with the system, task completion time, and task difficulty ratings. Upon finishing the usability tasks, participants completed the System Usability Scale. Important relationships were identified between the eye movement metrics and traditional usability testing metrics such as task difficulty rating and completion time. Eye tracking data were investigated quantitatively using aggregated fixation maps, and qualitative examination was performed on video replay of participants’ fixation behavior. Augmenting the traditional usability testing methods, eye movement analysis provided additional insights regarding revisions to the interface elements associated with these usability tasks.

Despite the rapidly increasing numbers of informational websites and learners using the World Wide Web to research topics, empirical evidence on the relationships between website design elements and website trustworthiness is scarce. This study used self-reported and behavioral screen-capture data to investigate the impact of Don Norman's (2003) emotional design levels and metacognitive awareness on website trustworthiness during an information search learning task. The results suggest that the interaction effects of website visual appeal (visceral level) and website usability (behavioral level) can override the effects of the quality or relevance of the information (reflective level) on website evaluation. In addition, in the context of limited time to find the answers, these effects on the evaluation of website trustworthiness are not moderated by users’ metacognitive awareness.