As digital materials proliferate in higher education, e-book interaction logs provide a scalable lens on how students study. However, most existing research analyzes these logs in a one-dimensional manner, which limits the ability to capture students’ study approaches comprehensively. Moreover, the relationship between students’ study approaches, metacognition, and performance remains unclear. To address these challenges, we propose a three-dimensional framework that incorporates engagement, navigation pattern, and context, combining theory-driven and data-driven perspectives to define behavior-based features and group students with similar patterns. We apply this approach to data from a real-world class in which students used an e-book system to study course materials and complete comprehension quizzes. Our analysis identified three distinct groups of students with different study approaches, and revealed that engagement investment alone does not guarantee achievement. We further examined how these approaches relate to students’ metacognitive awareness and academic performance.

Augmented reality (AR) is shifting language learning to more authentic and interactive. However, the complex and multitasking nature of AR creates challenges for learners in monitoring their progress. While Learning Analytics Dashboards (LADs) support assessment, they rarely address learning strategies in AR environments. This study first identified effective AR language learning strategies using combined Lag Sequential Analysis and Ordered Network Analysis, then developed a LAD with integrated learning prompts based on these findings. Formative evaluation confirmed the prompts of LAD effectively supported learners in monitoring and reflecting on their learning processes. This research contributes an analytical approach for identifying effective strategies and incorporating them into LAD design.

This study investigates the potential of using virtual reality (VR) technology to induce emotions that correspond to Japanese psych-mimetic words. Considering the complexities of learning these words, previous work [1] has developed a VR system tailored for psych-mimetic word education. By crafting immersive scenes that evoke specific emotions, the system is designed to help learners internalize the feelings associated with these words. Therefore, it is vital to confirm the system’s effectiveness in eliciting emotional responses from learners, through formative evaluation combining eye-tracking data analysis from VR headsets with semi-structured interviews conducted in the VR scenes. From both objective and subjective perspectives, this study investigates whether participants can experience emotions that align with the psych-mimetic words portrayed in the VR scenes. The results suggest that participants can generate the intended emotions within these VR scenes. This study intends to conduct future studies further examine the system’s impact on the educational outcomes of Japanese psychmimetic words. The current findings offer robust empirical evidence supporting the use of VR technology in language education.

As information technology advanced, accuracy of technology-driven assessment is being improved. In order to assess learning performance and awareness, assessment of metacognition level with technology can be useful to understand learner’s learning comprehension and awareness. Metacognition is one of the most important elements for successful learning. However, current way to evaluate metacognition level focuses on psychological method such as questionnaire and interview. The recent growth of learning analytics research has demonstrated the relationships between metacognition, learning awareness, and learning behaviors. This study aims to investigate metacognitive learning behaviors using small grain data on eBook and learning analytics dashboard (LAD) over eight weeks in a university course. To do so, we determined high and low metacognitive learner groups using the Metacognitive Awareness Inventory and investigated the differences between the two groups in eBook and LAD. The findings suggest that four learning behaviors eBook and LAD were detected as metacognitive learning behaviors, and contribute to the improvement of technology-driven assessment.

Summer vacation is considered a cause of loss in students' learning performance. In this study, we investigated the differences in learning behaviors in reading learning materials and time-related behavior patterns regarding summer assignments among three classes under different instructional styles. The results showed that students' learning behaviors in summer were correlated with instructional styles in school.

Previous research has established that motivation has a positive impact on the learning processes and behaviors [1] [2]. Learning analytics (LA) can play an important role in addressing the issue of collecting learning behaviors. In this study, we observed the teaching activities of three classes and examined the relationships among learning motivation, learning performance, and learning behaviors of students in digital learning material readers.