Generative artificial intelligence (GenAI) has taken educational settings by storm in the past year due to its transformative ability to impact school education. It is crucial to investigate pre-service teachers’ viewpoints to effectively incorporate GenAI tools into their instructional practices. Data gathered from 606 pre-service teachers were analyzed to explore the predictors of behavioral intention to design Gen AI-assisted teaching. Based on the Unified Theory of Acceptance and Use of Technology (UTAUT) model, this research integrates multiple variables such as Technological Pedagogical Content Knowledge (TPACK), GenAI anxiety, and technology self-efficacy. Our findings revealed that GenAI anxiety, social influence, and performance expectancy significantly predicted pre-service teachers’ behavioral intention to design GenAI-assisted teaching. However, effort expectancy and facilitating conditions were not statistically associated with pre-service teachers’ behavioral intentions. These findings offer significant insights into the intricate relationships between predictors that influence pre-service teachers’ perspectives and intentions regarding GenAI technology.

Numerous studies have been conducted to investigate the potential effect of educational robots, but what appears to be missing is an up-to-date and thorough review of the learning effectiveness of educational robots and the various influencing factors. In this study, a meta-analysis was conducted to systematically synthesize studies’ findings on the effects of educational robots on students’ learning outcomes. After searching for randomized studies describing educational robots interventions to improve learning outcomes, 34 effect sizes described in 17 articles met the selection criteria. The results of our work evidence a moderate but significantly positive effect of educational robots on learning outcomes (g = 0.57, 95% CI [0.49, 0.65], p < 0.00001). Moreover, moderator analyses were conducted to investigate important factors relating to the variation of the impact, including educational level and assessment type. Based on the findings of this study, we provide researchers and practitioners with insights into what characteristics of educational robot interventions appear to benefit students’ learning outcomes and how pedagogical approaches can be applied in various educational settings to guide the design of future educational robot interventions.

Although parental involvement is among the most crucial aspects of social support for students’ school engagement and achievement, current review work on the relationship between parental involvement and student engagement is largely missing. Therefore, we conducted a systematic literature review on such topics from the perspectives of landscapes, methodology characteristics (e.g., conceptualisation and measurement), and study patterns from 2000–2022. Following PRISMA guidelines, 33 articles involving 47,307 students and 3391 parents were reviewed. The results yielded several interesting facts. First, studies on this topic were primarily conducted in the United States during the first decade, but publications increased during emergency remote teaching (ERT) and China produced most of the publications. Studies were primarily cross-sectional (72.7%) and used secondary school Caucasian or Asian samples. In addition, although studies varied greatly on the conceptualisation and measurement of parental involvement and student engagement, they seem to embrace the idea of measuring parental involvement via school and home subtypes (85%) and student engagement via ABC dimensions (i.e., affective, behavioural, and cognitive; 57.4%). Moreover, in terms of patterns, studies often (82%) investigated its relations with student engagement or how it mediated the connections between parental involvement and learning achievement (e.g., success at school, dropout). They, however, often failed to provide concrete/practical parental involvement strategies. This pattern of results indicated an urgent need for more studies on specific parental involvement practices that could promote student engagement from multiple stakeholders. Limitations and suggestions for future studies were provided accordingly.

Artificial intelligence (AI) technologies have profoundly influenced both professional environments and personal lives. In the rapidly developing sector of AI education, fostering essential AI literacy among university students has become vital. Nevertheless, the factors that determine AI literacy remain insufficiently defined. This research, grounded in self-determination theory (SDT), seeks to investigate the relationships among three components: the fulfillment of university students’ three psychological needs, self-regulated learning strategies (SRLSs), and AI literacy. The aim is to enhance human capital efficiency and prepare students to tackle future workplace challenges effectively. To examine these connections, a cross-sectional survey was administered to 1056 university students. The findings reveal that satisfying the three psychological needs—perceived autonomy, competence, and relatedness—plays a pivotal role in advancing AI literacy among university students. Additionally, four SRLSs—cognitive engagement, metacognitive knowledge, resource management, and motivational beliefs—acted as mediators between these psychological needs and AI literacy. Consequently, this study not only enhances our understanding of the psychological and behavioral development of university students during their engagement with AI education but also provides theoretical support and practical guidance for fostering their AI literacy.

Autonomy support is one of the most crucial determinants of teaching practice for student engagement. No literature review on the relations between autonomy support and student engagement existed to the best of our knowledge. Therefore, this study presents a systematic literature review from perspectives of landscapes, methodology characters, patterns of identified studies, and autonomy-supportive strategies. Overall, 31 articles were reviewed. Followed by PRISMA guidelines, the results yielded several interesting facts: First, studies on such topics surged starting from 2015 and were mostly conducted in the United States (32%) and Korea (16%). Publications were scattered but heavily gathered around psychological and educational journals such as the Journal of Educational Psychology (9.7%); Learning and Instruction (9.7%). Most often, studies recruited participants from upper secondary schools (58%). Data were collected using solely questionnaires (93.5%) following a two-wave design (51.6%) and were analyzed by applying structural equation models (48.4%). Moreover, most of the studies failed to provide concrete autonomy-supportive teaching strategies. Instead, quite often studies (93%) investigated its relations with student engagement from a macro perspective. Within mentioned strategies, they were mostly related to the teaching process, there is a limited investigation of autonomy-supportive teaching practice used before and after instruction. This pattern of results suggested an urgent need for more longitudinal studies on specific teaching strategies that hold the potential to maximize student engagement. Limitations and suggestions for future studies were provided accordingly.