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Debugging process plays a crucial role in helping students pinpoint their specific learning weaknesses, allowing them to modify their strategies for enhanced academic performance. Notably, changes in pupil dilation serve as an indicator of arousal associated with confronting learning challenges. This physiological response acts as a “physiological footprint” that reflects cognitive engagement, facilitating internally focused cognitive processes such as insight generation and mind-wandering. In this study, we proposed that pupil dilation could be a valuable predictor of students’ metacognitive awareness throughout the debugging process, specifically within an augmented reality (AR) learning environment. The findings revealed significant differences in pupil dilation among students categorized by their varying levels of debugging, which represents a specific dimension of the Metacognitive Awareness Inventory. 

This study explores the application of slouching scores to assess ergonomic posture in augmented reality (AR) environments. Employing Microsoft HoloLens 2 with Xsens motion capture technology, participants engaged in interactive biomechanics tasks, including a practical luggage-lifting exercise. Real-time feedback guided users towards safe posture, emphasizing spinal alignment and reducing physical strain. Slouching scores functioned as quantitative measures of posture quality, establishing a connection between unsafe postures and the requisite postural adjustments. The results illustrate how AR-integrated systems can enhance posture awareness, improve user ergonomics, and promote active learning in both educational and professional settings. 

In the context of student learning, investigating effective feedback mechanisms within augmented reality (AR) learning systems is crucial for better understanding and optimizing study behaviors. This study examines the influence of metacognitive monitoring feedback within an AR setting. Our hypothesis suggests that regularly providing students with feedback on their metacognitive monitoring within an AR learning environment has a beneficial effect on their metacognitive state. The results of the study confirm that frequent exposure to such feedback significantly improves scores on the Metacognitive Awareness Inventory. Essentially, there was a marked increase in the inventory scores of participants who received ongoing feedback, compared to those who only received metacognitive monitoring feedback once after the lecture, particularly in the areas of planning, monitoring comprehension, and debugging strategies. This enhancement is achieved by influencing student calibration by directly impacting their metacognitive state. 

With the growing need for augmented reality (AR) technology, understanding and optimizing study behaviors in AR learning environments has become crucial. However, one major drawback of AR learning is the absence of effective feedback mechanisms for students. To overcome this challenge, we introduced metacognitive monitoring feedback. Additionally, we created a location-based AR learning environment utilizing a real-time indoor tracking system to further enhance student learning. This study focuses on the positive impact of metacognitive monitoring feedback in a location-based AR learning environment. Our hypothesis posits that regularly providing students with feedback on their metacognitive monitoring within this new AR learning system positively influences their metacognitive awareness. The study's findings confirm that frequent exposure to such feedback significantly enhances the Metacognitive Awareness Inventory (MAI) scores. Participants who received continuous feedback demonstrated a significant increase in MAI scores compared to those who received feedback only once after the lecture. This improvement is achieved by influencing student calibration and directly enhancing their metacognitive awareness. 

This study investigates the method for measuring cognitive workload in augmented reality-based biomechanics lectures by analyzing pupil dilation. Using Dikablis Glasses 3 and Microsoft HoloLens, we recorded physiological and subjective data across learning and problem-solving phases. Pupil dilation was normalized and segmented, enabling a comparison of cognitive demands between phases. The results indicated significant correlations between pupil dilation and NASA TLX cognitive demand, particularly in lectures that primarily involved procedural knowledge. These findings suggest that instructional design and content complexity have a significant impact on cognitive load, providing valuable insights for optimizing AR-based learning environments to support cognitive efficiency and student engagement. 

There is an increasing demand for developing new metrics that can effectively measure the physical demand experienced by users in augmented reality (AR) environments. In this study, we evaluated one of the recent metrics, called “slouching score,” in an AR-based biomechanics lecture. This study aims to uncover the correlation between the AR interaction and the physical demand of users in a different setup compared to the earlier study. The slouching score, which evaluates posture changes that may indicate fatigue during AR interactions, is measured using Xsens motion capture equipment. These calculated scores are compared with responses to physical demand assessments surveyed using NASA-TLX questionnaires. One of the key differences between the current study and earlier ones is that participants had to physically move to access the next AR module in earlier studies. In contrast, this time, participants simply needed to click a virtual arrow button to view the next AR modules, eliminating the need for physical movement. Our preliminary findings show correlations between the slouching score from some modules and the NASA-TLX physical demand ratings. 

In this digital learning era, Augmented Reality (AR) has become a significant driver of innovative user experience. However, the ergonomic implications of AR, particularly regarding the postural fatigue dynamics, have not been comprehensively addressed. This study investigates the correlation between prolonged AR engagement and the onset of postural fatigue, characterized by a backward shift in the center of mass (COM). Employing motion capture technology alongside cognitive load assessment tools such as the NASA Task Load Index and HoloLens eye-tracking, we seek to quantify the relationship between user posture, engagement duration, and perceived workload. We hypothesize that an observable rearward displacement of COM signifies escalating fatigue levels. The methodology integrates ergonomic analysis, biomechanics, and predictive modeling. Preliminary findings indicate a decline in postural stability with increased AR exposure, reinforcing the need for ergonomics interventions. This study underscores the necessity of ergonomic consideration in the design and use of AR systems to safeguard user well-being in educational settings. 

In the digital learning landscape, Augmented Reality (AR) is revolutionizing instructional methodologies. This study shifts focus to explore the impact of AR-based lectures on pupil dilation as a biomarker of mental demand. By analyzing pupil dilation with cognitive load assessment tools like the NASA Task Load Index, we aim to understand the cognitive implications of prolonged exposure to AR in educational settings. We hypothesize that variations in pupil size can be indicative of cognitive load, correlating with the mental demands imposed by AR lectures. Preliminary findings suggest a significant relationship between increased pupil dilation and heightened mental workload during AR engagements. This study highlights a new way to measure cognitive workload in AR environments using pupil dilation data. 

In this study, we explore the impact of incorporating a virtual instructor with realistic lip-syncing in an augmented reality (AR) learning environment. The study is particularly focused on understanding if this enhancement can reduce students’ mental workload and improve system usability and performance in AR learning. The research stems from previous feedback indicating that a virtual instructor without facial movements was perceived as “creepy” and “distracting.” The updated virtual instructor includes facial animations, such as blinking and synchronized lip movements, especially during lecture explanations. The study aims to determine if there are significant changes in mental workload and usability differences between the AR systems with and without the enhanced virtual instructor. The study found significant differences in the usability scores in some questions. However, there was no significant difference in the mental workload between them. 

Augmented Reality (AR) technology offers the possibility of experiencing virtual images with physical objects and provides high quality hands-on experiences in an engineering lab environment. However, students still need help navigating the educational content in AR environments due to a mismatch problem between computer-generated 3D images and actual physical objects. This limitation could significantly influence their learning processes and workload in AR learning. In addition, a lack of student awareness of their learning process in AR environments could negatively impact their performance improvement. To overcome those challenges, we introduced a virtual instructor in each AR module and asked a metacognitive question to improve students’ metacognitive skills. The results showed that student workload was significantly reduced when a virtual instructor guided students during AR learning. Also, there is a significant correlation between student learning performance and workload when they are overconfident. The outcome of this study will provide knowledge to improve the AR learning environment in higher education settings.