Effective teaching of science requires not only a broad spectrum of knowledge, but also the ability to attract students’ attention and stimulate their learning interest. Since the beginning of 21st century, VR/AR have been increasingly used in education to promote student learning and improve their motivation. This paper presents the results of a systematic review of 61 empirical studies that used VR/AR to improve K-12 science teaching or learning. Major findings included that there has been a growing number of research projects on VR/AR integration in K-12 science education, but studies pinpointed the technical affordances rather than the deep integration of AR/VR with science subject content. Also, while inquiry-based learning was most frequently adopted in reviewed studies, students were mainly guided to acquire scientific knowledge, instead of cultivating more advanced cognitive skills, such as critical thinking. Moreover, there were more low-end technologies used than high-end ones, demanding more affordable yet advanced solutions. Finally, the use of theoretical framework was not only diverse but also inconsistent, indicating a need to ground VR/AR-based science instruction upon solid theoretical paradigms that cater to this particular context.

Despite the increasing number of studies indicating that generative artificial intelligence is conducive to cultivating college students’ critical thinking skills, research on the impact of college students’ use of generative artificial intelligence on their critical thinking skills in an open learning environment is still scarce. This study aims to investigate whether the use of generative artificial intelligence by college students in an open learning environment can effectively enhance their critical thinking skills. The study is centered around the following questions: Does the use of generative artificial intelligence in an open learning environment enhance college students’ critical thinking skills (what)? What is the mechanism by which the use of generative artificial intelligence affects college students’ critical thinking (how)? From the perspective of self-regulated learning theory and learning motivation theory, what are the reasons for the impact of generative artificial intelligence on college students’ critical thinking skills (why)? To this end, the study employs questionnaires and interviews to collect data. The questionnaire data are subjected to descriptive statistical analysis, correlation analysis, multiple stepwise regression analysis, and mediation effect analysis. Based on the analysis of interview materials and survey questionnaire data, the study reveals the impacts and mechanisms of college students’ use of generative artificial intelligence tools on their critical thinking skills. The findings of the study are as follows. First, the frequency of artificial intelligence use is unrelated to critical thinking skills, but using it for reflective thinking helps to develop critical thinking skills. Second, students with strong self-regulated learning skills are more likely to use generative artificial intelligence for reflective thinking and achieve better development in critical thinking skills. Third, students with strong intrinsic learning motivation are more likely to use generative artificial intelligence for reflective thinking and achieve better development in critical thinking skills. Consequently, the article analyzes the reasons from the perspectives of self-regulated learning theory and learning motivation theory and offers insights into how to properly use generative artificial intelligence to promote the development of critical thinking skills from the perspectives of higher education institutions, college teachers, and college students.

The application of information technology provides technical support for achieving the requirements of reducing burden and improving quality in the Chinese “Double Reduction” Policy. Based on the analysis of the mechanism and path of “Smart Homework” (an educational tool that applies artificial intelligence technology) to reduce the burden and improve the quality of Chinese Jiangxi Province by using the literature, this paper investigates 78 counties and cities of this province and finds that this tool can reduce the burden of primary and secondary school students’ homework, improve the completion of homework, reduce the willingness to participate in after-school tutoring, and improve the self-efficacy and learning investment, so as to achieve the goal of the Chinese “Double Reduction” Policy, but at the same time, the lack of convenience in using intelligent products has caused psychological anxiety for a small number of students. The psychological mechanism of reducing burden and improving quality is in line with the principle revealed by the Yerkes–Dodson law; that is, as learning anxiety decreases, the impact of psychological stress on learning efficiency increases. The appropriate psychological stress enhanced the impact of psychological pressure on learning efficacy and engagement, and improved learning efficiency. The article believes that, first, based on the principle of a three-layer structure of homework burden, the use of “Smart Homework” achieves the reduction of homework burden from three aspects: surface layer, inner layer, and core layer. Second, “Smart Homework” reduces the willingness to participate in extracurricular tutoring and, to some extent, reduces the burden of extracurricular tutoring. Third, “Smart Homework” can help students better complete homework and improve learning efficiency.

Cloning and Expression Analysis of PAP1 in Brassica juncea