As most practitioners (including teachers) do not know how AI functions and cannot make full use of AI in education, there is an urgent need to investigate teachers’ intentions to learn AI and related determinants so as to promote their AI learning. This study collected survey data from a total of 318 K-12 teachers from sixteen provinces or municipalities in China. A two-step structural equation modeling approach was performed to analyze the data. Our findings show that K-12 teachers’ perceptions of the use of AI for social good and self-efficacy in learning AI are two direct determinants of behavioral intentions to learn AI, while awareness of AI ethics and AI literacy are two indirect ones. AI literacy has a direct impact on perceptions of the use of AI for social good, self-efficacy in learning AI and awareness of AI ethics and has an indirect impact on behavioral intentions to learn AI. This study represents one of the earliest attempts to empirically examine the power of AI literacy and explore the determinants of behavioral intentions to learn AI among K-12 teachers. Our findings can theoretically and practically contribute to the virgin field of K-12 teachers’ AI learning.

As virtual reality (VR) and augmented reality (AR) continue to become popular, there remains a noticeable gap in understanding their potential for enriching science, technology, engineering, and mathematics (STEM) learning among K-12 students. To address this knowledge gap, this study systematically reviewed 117 articles published from 2010 to 2022 on the basis of the technology-based learning model. Following the PRISMA systematic review method, research methods, research participants, learning devices, learning strategies, advantages and challenges of each article were coded and analyzed. In the last six years (i.e., 2017–2022), the overall number of studies experienced rapid growth. The largest number of articles focused on VR/AR-supported K-12 science learning, followed by mathematics and integrated STEM learning. Smartphone/tablet-based AR was the most widely used technology, while very few studies used dedicated immersive AR devices. Most studies focused on the elementary school stage, while VR/AR-supported STEM learning at senior high schools was underexplored. Studies tended to measure the effectiveness of VR/AR by quantitative methods. Situated learning, task-based learning, and game-based learning were the most widely used learning strategies in VR/AR-supported K-12 STEM learning. The advantages of VR/AR in K-12 STEM learning include a positive impact on individual learners and on learning and teaching processes. In contrast, VR/AR also poses a series of challenges to learners, teachers, and schools. The challenges learners face include distractions, decreased efficiency and effectiveness, diminished inquiry and imagination, operational issues, and discomfort. Teachers encounter difficulties maintaining classroom control, designing activities, acquiring technical competence, and adapting to the new role of facilitating student-centered learning. Schools grapple with high costs, inadequate infrastructure, a lack of private virtual spaces, and privacy concerns. Based on our findings, we propose six research agendas to enrich studies on VR/AR-supported K-12 STEM learning, along with a series of significant implications for practitioners to effectively address the intricate challenges of VR/AR implementation and fully harness its potential.

Background: Teacher emotions are sometimes underplayed in the research field of teaching and teacher education. Also, teachers often undergo transformations in their professional identities during education reforms. However, very few studies explore the connections between teacher emotions and their professional identities against the background of education reforms, especially in Asian contexts. There is an increasing emphasis on STEM as an education reform in China and the world, and a deep understanding of STEM teacher emotions and professional identities is necessary in the fast development of STEM education. This study examined how a STEM teacher emotionally constructed her professional identities under the STEM education reform. Methods: This is a 3-year longitudinal case study employing a narrative inquiry approach with one STEM teacher in China. Data collection included one in-depth, semi-structured interview, three conversations, personal emotional diaries, and correspondence records. A four-step data analysis was conducted. Results: Three major themes reflecting the participant’s emotional professional identities emerged, including “an interested but confused learner”, “an enthusiastic but nervous explorer”, and “an excited but unsatisfied mentor”. In the participant’s experiences as a learner, explorer, and mentor, positive and negative emotions were always intertwined. These helped construct and shape her professional identities and encouraged her to be the best STEM teacher that she could be. Conclusion: This study provides a series of vivid and dynamic pictures of a STEM teacher’s emotions and professional identities against the background of STEM education reform in China from a 3-year longitudinal perspective. It also indicates the personal, social, cultural, and contextual factors that could have strong effects on teachers’ emotional experiences and the construction of professional identities. Furthermore, this study reveals that three processes (i.e., the process of education changes, the process of creating new or multiple professional identities, and the generation process of teacher emotions) could be intertwined and developed together.

This study investigates the creators, effects, and inhibitors of technostress among STEM teachers, addressing a critical yet underexplored issue in the digitalization of education. Grounded in the technostress model and the job demands–resources (JD-R) model, the study examines the relationships among technostress creators, burnout, organizational effects (job satisfaction, organizational commitment, and work performance), and technostress inhibitors. A cross-sectional survey was conducted with 378 STEM teachers from Zhejiang Province, China. Structural equation modeling (SEM) was employed to test the hypothesized paths. The results revealed that technostress creators significantly increased teacher burnout and negatively affected organizational commitment and work performance. Burnout mediated the impact of technostress creators on job satisfaction and organizational commitment. Technostress inhibitors were found to alleviate burnout, mitigate technostress creators, and enhance STEM teachers’ commitment. These findings validate the applicability of the technostress model in the context of K–12 STEM education in China and highlight the importance of organizational mechanisms for supporting teacher well-being and performance. The study contributes to both theory and practice by proposing an integrative model of technostress and offering actionable recommendations for school leadership to effectively manage technostress.

The problem motivating this study is the fact that almost 19.70 million university students in China have been required to engage in e-learning under the government’s initiative of “Classes are Suspended, yet Learning is still Ongoing” during the COVID-19 epidemic, coupled with varied responses, uneven adoption of e-learning platforms and varying degrees of satisfaction toward them. Using the online database adoption and satisfaction (ODAS) model, this study examines the determinants which impact university students’ adoption of and satisfaction with e-learning platforms at this particular time in China. The ODAS model was also cross-validated using gender as a moderating variable. A purposive sampling procedure was used to survey a total of 1,136 students from six universities in five provinces or municipalities of China. The data for this survey were estimated using the Rasch model and structural equation modeling. Results exhibit that students’ adoption of and satisfaction with e-learning platforms were significantly measured by their computer self-efficacy, their intention to use e-learning platforms, and their perceived ease of use and perceived usefulness of these platforms, while the relationships among these components were moderated by gender differences. This empirically-based cross-validation of the ODAS provides recommendations for future studies, including practical implications for e-learning. This current study contributes to the body of knowledge in evaluating e-learning platforms during the COVID-19 epidemic.