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Siyu Yuan, Kaitao Song, Jiangjie Chen, Xu Tan, Yongliang Shen, Kan Ren, Dongsheng Li, Deqing Yang. Proceedings of the 2025 Conference of the Nations of the Americas Chapter of the Association for Computational Linguistics: Human Language Technologies (Volume 1: Long Papers). 2025.

In recent years, several researchers have introduced spherical video-based virtual reality (SVVR) into classroom teaching to help students learn different subjects. In SVVR learning, learners are typically presented with great autonomy over their learning process. Therefore, learners should engage in self-regulated strategy (SRS) learning in order to successfully study in SVVR. However, learners often struggle to self-regulate their learning. Therefore, we implemented a SRS intervention in SVVR. In this study, a SVVR environment was developed to situate students in art history contexts; moreover, the SRS was employed to guide students to improve their performance and to make reflections on their own performance. In order to evaluate the proposed approach’s effectiveness, we carried out an experiment in a university art history class. The experiment results reveal more positive effects of the SRS-based SVVR approach compared with the non-SRS-based SVVR approach in terms of the learners’ learning achievements, self-regulation, meta-cognitive awareness, as well as self-efficacy. In addition, this study specified that this approach would not have an effect on students’ cognitive load. As a result, the SRS-based SVVR approach proposed in the current study was effective in art history education.

The application of generative artificial intelligence in the field of education has been receiving increasing attention, with the performance of chatbot ChatGPT being particularly prominent. This study aims to explore in depth the performance impact on higher education students utilizing ChatGPT. To this end, we conducted a survey on 448 university students and employed the partial-least squares (PLS) method of structural equation modeling for data analysis. The results indicate that all eight hypothetical paths posited in this study were supported, and surprisingly, the hypothesis that technology characteristics have a direct effect on performance impact was supported. Moreover, the study found that overall quality is a crucial factor determining performance impact. Overall quality indirectly affects performance impact through task-technology fit, technology characteristics, and compatibility, among which the mediating effect of compatibility is most significant, followed by technology characteristics. This study offers practical recommendations for students on the proper use of ChatGPT during the learning process and assists developers in enhancing the services of the ChatGPT system.

During the COVID-19 pandemic, campuses are closed, and many schools are forced to transition to online instruction. There are many problems in landscape architecture education during the pandemic such as students’ decreased attention, poor self-regulation, low proactivity, and difficulty in grading. In addition, situational effects are required for landscape architecture education, but online education lacks the necessary case scenarios for courses during the pandemic. In order to solve these problems, the present study adopted a more accessible, and interactive spherical video-based immersive virtual reality (SV-IVR) approach, developed a landscape architecture SV-IVR learning system, and conducted a quasi-experimental study to examine its effectiveness. The results indicated that the experimental group students showed more positive results in their learning achievements, learning attitudes, and self-regulation than the control group. Besides, it was found that students required more time to develop their self-efficacy and that this system would not have an effect on students’ cognitive load.

While digitalization offers new opportunities for small- and medium-sized enterprises (SMEs), it also introduces the phenomenon of the “digitalization paradox”. This paper develops a theoretical model comprising digitalization, digital technology–business alignment, external social capital, and SMEs’ performance, rooted in strategic alignment theory (SAT) and social capital theory (SCT). The necessary data for the study were obtained by distributing questionnaires to 352 small and medium-sized enterprises engaged in digital practices in China, and hierarchical regression analysis was employed to investigate the impact of digitalization on the performance of SMEs and its boundaries of influence. The results indicate an inverted U-shaped relationship between digitalization and SME performance, with both digital technology–business alignment and external social capital serving as positive moderators. Specifically, digital technology–business alignment and external social capital both enhance the positive impact of digitalization on the performance of SMEs and mitigate its negative effects. The findings enhance comprehension of the “digitalization paradox” and offer new insights and solutions for SMEs to navigate the opportunities and challenges of digitalization.