This paper investigates how virtual reality (VR) can foster empathy and ecological literacy for urban herpetofauna—reptiles and amphibians often overlooked in conservation. We present The Wetland Quest (TWQ), an immersive VR experience set in a Shanghai wetland that employs embodiment and scale-shift mechanics to situate users in the world of local species. In a mixed-methods study with 62 participants, TWQ significantly improved species literacy and attitudes toward herpetofauna, supported by large quantitative gains and qualitative themes of immersion, empathy, and reduced aversion. This work contributes to HCI and environmental communication by: (1) introducing TWQ as a design case of VR for underrepresented species; (2) providing empirical evidence that immersive perspective-taking can enhance literacy and pro-environmental attitudes; and (3) demonstrating a methodological protocol that combines knowledge tests, validated attitude scales, observations, and interviews, offering a transferable approach for future VR conservation research.

Ensuring consistent persona in interactive AI systems presents a significant challenge, especially in diverse application scenarios ranging from virtual assistants to customer service bots. Such capability is often constrained by the system's understanding of direct and explicit persona conflicts. Traditional approaches primarily focus on detecting discrepancies between machine responses and its predefined profile, or the contextual inconsistencies between the responses at the semantic level rather than the persona level. Due to the lack of a comprehensive persona-specific Commonsense Knowledge Graph, some indirect and implicit persona inconsistencies between machine responses can hardly be identified. In this paper, we build the first persona commonsense knowledge graph (PersonaKG), based on which we then construct a large-scale persona consistency dialogue dataset (PersonaCOM) containing both explicit and implicit persona conflicts between machine responses. With the guidance of the persona commonsense knowledge, we propose a Recognize-Rewrite framework (R2) which first recognizes the responses that are inconsistent in persona with the previous responses, and then rewrites them into consistent ones. The empirical study demonstrates that utilizing R2 method on PersonaCOM with PersonaKG results in a significant improvement of 12.20% in automatic metrics and 10.09% in manual evaluation compared to not using the R2 method and PersonaKG.

Large Language Models (LLMs) exhibit remarkable capabilities across various downstream tasks, including empathetic dialogues. However, a non-trivial question arises: Do they possess high-context empathy and can they generate emotional interactions with humans? High-context empathy, which tends to be more indirect and concise like Chinese-style empathy, differs from the current empathy capabilities of LLMs. These capabilities are predominantly low-context empathy, which is often direct and lengthy, resembling English-style empathy. In this paper, We first construct a comprehensive Chinese High-context Empathy Dialogue dataset (HED), which consists of emotional, role-based emotional, personality-based emotional, and role-personality-based emotional dialogues. Next, we explore whether LLMs have high-context empathy in conversations. After that, we propose an innovative High-context Empathy Network (HEN) to improve LLMs' capabilities in generating high-context empathetic responses. Our empirical study demonstrates that there is much room for LLMs in generating high-context empathetic responses, and the proposed HEN can not only significantly improve LLMs' capabilities in generating high-context empathetic responses, but also has positive effects for LLMs in solving similar sentiment-related tasks.

This innovation practice explores whether using spatial computing technologies in the form of the Apple Vision Pro and Nomad Sculpt in a mixed-reality environment affects student outcomes on learning goals and creative expression in the context of a chair design project in design education. The primary hypothesis of the study is that, even though students are provided with the exact project specifications, goals, and assessment rubrics, student design outcomes on learning goals and creative expression in the chair design project will improve when using the Apple Vision Pro and Nomad Sculpt as opposed to traditional digital design technologies (the control group using iPads and Nomad Sculpt). In the chair design project, learning goals and course outcomes were framed around projects that included mass, support, openings, shape expression, technical articulation, conversation, structure, sustainability, form, and fulfillment. On average, the subset of students using the Apple Vision Pro and Nomad Sculpt reported more intuitive, immersive, and creative experiences in the design process and the resulting chair designs in reflective essays. These findings are mainly based on quantitative measures of flexibility, idea originality, idea execution, depth of conceptual understanding, engagement, and qualitative measures of experiences through surveys and interviews. Developing an understanding of these tools to provide rich, relevant feedback and enabling productive critique and implementation on the device seems almost insurmountable hurdles due to access, new technologies' learning curve, and the inefficiency of integrating spatial computing tools into pedagogical frameworks. Overall, the research highlights the critical pedagogical advantages of using spatial computing technologies such as the Apple Vision Pro in design education, particularly in design fields requiring high visual-spatial aptitude levels. Furthermore, it provides guidelines for future research into the educational merits of immersive technologies and argues that we need to move beyond the predominantly uni-directional pedagogical models that have characterized the field for more than half a century. This study illustrates the potential of spatial-computing tools to enhance creative problem-solving and the substantial merits for future research into its broader educational applications.

Embodied theories of language propose that the way we communicate verbally is grounded in our body. Nevertheless, the way a second language is conventionally taught does not capitalize on kinesthetic modalities. The tracking capabilities of room-scale virtual reality systems afford a way to incorporate kinesthetic learning in language education. We present Words in Motion, a virtual reality language learning system that reinforces associations between word-action pairs by recognizing a student's movements and presenting the corresponding name of the performed action in the target language. Results from a user study involving 57 participants suggest that the kinesthetic approach in virtual reality has less immediate learning gain in comparison to a text-only condition and no immediate difference with participants in a non-kinesthetic virtual reality condition. However, virtual kinesthetic learners showed significantly higher retention rates after a week of exposure than all other conditions and higher performance than non-kinesthetic virtual reality learners. Positive correlation between the times a word-action pair was executed and the times a word was remembered by the subjects, supports that virtual reality can impact language learning by leveraging kinesthetic elements.