Yuki Kitamura, Tomonari Kishimoto, Hiroyuki Nagataki, Susumu Kanemune, and Shizuka Shirai. 2026. Enhancing Computer Network Education for High School Students with an Educational Simulator Visualizing Packet Retransmission and Routing. In Proceedings of the 57th ACM Technical Symposium on Computer Science Education V.1 (SIGCSE TS 2026), February 18–21, 2026, St. Louis, MO, USA. ACM, New York, NY, USA, pp. 575–581. https://doi.org/10.1145/3770762.3772590

With recent advances in information and communication technologies, Hybrid meetings, where local attendees are physically present and remote participants join virtually, have become increasingly common. However, remote participants often experience reduced contextual awareness and a sense of isolation. To address these issues, we propose HybridSphere, a hybrid meeting system that reconstructs a shared virtual reality environment for remote participants. The system employs a 360-degree camera and pose estimation to generate real-time avatar representations of local attendees to allow remote users with head-mounted displays to experience the meeting as if all participants are in the same virtual space. We conducted a user study comparing HybridSphere to a baseline condition in which remote participants viewed an unmodified 360-degree video. Although the avatars were rated lower in perceived trustworthiness and likability due to limited visual fidelity, participants appreciated the seated-6DoF function. These results suggest that immersive and spatially flexible VR representations can enhance remote engagement in hybrid meetings.

This study explores the potential functionalities of Learning Analytics Dashboards (LADs) aimed at supporting both self-regulated learning and career planning. While previous research on LADs has primarily focused on visualizing learning outcomes to support self-regulated learning, there remains a gap in providing actionable guidance that integrates career planning. To address this issue, we adopted Participatory Design Research (PDR), engaging university students with diverse career aspirations in the design process. Participants identified desired dashboard features from the dual perspectives of learning support and career development. Analysis results revealed that students without clearly defined career goals sought functionalities that allow them to reflect on their objectives by referencing the experiences of peers with a similar major. In contrast, students with specific career plans desired features that provide insights into the academic and professional paths of alumni in related fields. This study contributes novel insights into dashboard design, emphasizing the importance of aligning learning analytics with university students' career goals and aspirations. Future work will involve developing and evaluating a prototype to assess the efficacy of these integrated support functionalities in enhancing both self-regulated learning and career planning among students.

Mobile robot navigation systems are increasingly relied upon in dynamic and complex environments, yet they often struggle with map inaccuracies and the resulting inefficient path planning. This paper presents MRHaD, a Mixed Reality-based Hand-drawn Map Editing Interface that enables intuitive, real-time map modifications through natural hand gestures. By integrating the MR head-mounted display with the robotic navigation system, operators can directly create hand-drawn restricted zones (HRZ), thereby bridging the gap between 2D map representations and the real-world environment. Comparative experiments against conventional 2D editing methods demonstrate that MRHaD significantly improves editing efficiency, map accuracy, and overall usability, contributing to safer and more efficient mobile robot operations. The proposed approach provides a robust technical foundation for advancing human-robot collaboration and establishing innovative interaction models that enhance the hybrid future of robotics and human society. For additional material, please check: https://mertcookimg.github.io/mrhad/

Virtual reality (VR) video games that are played on a VR headset are becoming increasingly common in households, and though many games require players to navigate vast virtual spaces, most homes cannot provide a large enough physical space to encompass the entire virtual space. Thus, VR video games that require locomotion often provide users with alternative locomotion techniques. While teleportation or steering is typically used as a standard, new techniques can overcome remaining problems, such as motion sickness. However, a holistic perspective of user needs and issues regarding these techniques in practical situations has not been studied on a broad basis. To address this gap in the literature and contribute to future VR video game development and research, we conducted 16 semi-structured interviews and surveyed 88 participants to help explore issues regarding existing locomotion techniques. Our results revealed preferences related to teleportation versus steering and the postures that users adopt while playing VR video games, along with user needs for locomotion techniques in each posture.

Head tracking allows users of Virtual Reality (VR) to freely rotate their heads 360 degrees while exploring virtual environments. When using VR in a limited space, the ability to physically rotate one's head is limited to a specific range. To address this issue, previous studies have proposed methods to employ distinct rotation factors for real and imaginary rotations. However, its primary usage lies in redirected walking; thus, it is unsuitable for seated VR. In this article, we propose CaliView, which consistently adjusts the user's perspective to always face an optimal direction in VR, all while ensuring a comfortable posture. CaliView continuously controls the rotation gain to ensure that the disparity between the present body orientation and the optimal orientation is reduced to zero, encouraging the user to assume a forward-facing position with the target orientation. To assess the suggested approach, CaliView, we experimented to compare three conditions: CaliView, snap turning only (SnapTurn), and hybrid of CaliView and snap turning (Hybrid). The research findings suggest that CaliView functions as a useful reorientation technique, enabling implicit reorientation without sacrificing the user experience. Additionally, this study showcases its compatibility with various other techniques, such as the traditional snap-turn, thus emphasizing its versatility.

In on-demand e-learning environments, the lack of direct intervention can lead to a decline in learners' engagement. To address this issue, systems that estimate the learners' attitudes and provide feedback have been proposed. However, the acceptability of such systems has not been sufficiently researched. In this study, we investigated the acceptability by people to an e-learning system with internal state feedback, for future personalized learning support. To this end, we developed a system that estimates and visualizes the learner's internal state in real-time. The system was exhibited in a public space for free use, and users' impressions were analyzed. To estimate the learners' internal state, we developed a machine-learning model that recognizes learners' alertness from facial videos. The system was deployed in an exhibition space, and 131 responses were collected. These responses were coded and analyzed using a co-occurrence network. The result indicated that learners tend to dislike the system due to feelings of being observed by supervisors. In contrast, instructors expressed favorable options toward the introduction of the system.

The COVID-19 pandemic has catalyzed a rapid transformation in higher education, prompting institutions to embrace online learning and e-learning as essential mechanisms for academic continuity. In this context, Interactive Learning Environments (ILEs), augmented with generative AI chatbots, represent a promising approach to enhancing the effectiveness of virtual education and interactive learning. This paper investigates the efficacy of an ILE integrated with ChatGPT in the context of computer networking education. A pilot experiment was conducted with three graduate students with basic IT networking background. The study examined the impact of integrating ChatGPT within the ILE on students’ engagement, comprehension, and overall learning outcomes. Methodological details, including learning program design, learning outcomes assessment, ILE settings, and ChatGPT integration are presented. Results from pre- and post-assessment tests, quizzes, and students’ feedback on ChatGPT’s utility as a learning aid are discussed. The findings suggest a significant improvement in students’ comprehension and performance following their engagement with the ILE while using ChatGPT as a support tool. Despite a few drawbacks reported by the students in terms of the interfaces’ ease of use, and the timely response and appropriate content delivered by ChatGPT, they were overall satisfied with the experience. The students would recommend ChatGPT for learning purposes under certain controlled environments. This study contributes to the growing body of literature on interactive learning technologies and highlights the potential of generative AI chatbots such as ChatGPT to revolutionize computer networking education in the digital age.

This poster introduces a case study of redesigning an introductory CS course into fully online and its evaluation. The course redesigned is an introductory computer science course aiming to enhance non-CS major students' engagement. We applied flipped learning and active learning approach to the course design, utilizing interactive learning platforms. The proposed course offered a more immersive and satisfactory experience, even in a fully online course. The questionnaire results after the practice in the 2020 term showed that students rated significantly higher than that of 2019 in terms of difficulty level, amount of content, manner of delivery, course materials, consideration of course design, the structure according to the syllabus, learning outcomes, and satisfaction.