This study aimed to explore the relationships among peer and teacher support, emotional intelligence, and creative thinking. A total of 335 middle school students in grade seven were surveyed in China, including boys 187 (55.8%) and girls 148 (44.2%), aged from 11 to 14 years (M = 12.5; SD = 0.5). Results of the partial least square structural equation modeling showed that emotional intelligence was a positive mediator in the processes from peer and teacher support to middle school students’ creative thinking, and emotion regulation strategies moderated these processes from emotional intelligence to creative thinking. Specifically, both peer and teacher support had an indirect effect on creative thinking through emotional intelligence. Moreover, the four dimensions of emotional intelligence bore different mediating powers. Among them, emotion regulation exhibited the greatest mediating power, and self-emotion appraisal is the least. In addition, both reappraisal and suppression positively moderated the impact of emotional intelligence on creative thinking. Moreover, reappraisal had stronger moderating power than that of suppression. Interestingly, the direct effects of both peer and teacher support on creative thinking were not observed. This study offers knowledge about the mechanisms of peer and teacher support and students’ creative thinking, and implications for practitioners were also discussed in this study.

As a technology-enhanced student-centered learning environment, smart classrooms are becoming increasingly popular in higher education. It is undoubtedly important to understand how seating and motivational factors affect situational engagement and satisfaction in smart classrooms. Pre-survey, experience sampling method, and post-survey were used in this study to conduct a longitudinal survey of 113 pre-service teachers in three courses at a university in central China. Descriptive statistics, bivariate correlations, hierarchical linear modeling, and hierarchical linear regression were used to investigate the effects of seating factors and motivational factors on engagement and satisfaction in smart classrooms. We found: (1) for the seating factor, the distance of the seat from the center point predicted student situational engagement in the smart classroom; (2) for motivational factors, needs of competence and competence during the activity predicted student situational engagement, while autonomous motivation at the beginning of a course strongly predicted student situational engagement in subsequent activities; and (3) of all the factors, situational engagement was a significant predictor of students’ final course satisfaction and fully mediated the relationship between autonomous motivation and satisfaction. Finally, some practice implications are discussed to improve engagement and satisfaction in technology-enhanced environments.

Learning through making enhances the learning experience and effectively develops learners’ creativity. In this regard, maker education has been extensively incorporated into school education as a vital learning environment. However, less is known about how making advances students’ creativity in maker education. Therefore, this study aimed to explore relationships among making, tinkering, and creating. A total of 372 middle school students enrolled in maker courses through the 2021–2022 school year were surveyed. They completed a questionnaire concerning learning engagement, individual creativity, collective creativity, and learning motivation. Structural equation modeling (SEM) was employed to test the hypotheses proposed in this study. The results revealed significant relationships among learning engagement, individual creativity, and collective creativity. Specifically, behavioral engagement positively predicted emotional and cognitive engagement. Moreover, both emotional and cognitive engagement positively related to collective creativity, while only the effect of cognitive engagement on individual creativity was observed. The direct effects of behavioral engagement on individual and collective creativity were not significant. Furthermore, emotional and cognitive engagement mediated the association between behavioral engagement and collective creativity, while only cognitive engagement played a mediating role between behavioral engagement and individual creativity. In addition, the moderating analysis showed that learning motivation moderated the association between behavioral engagement and emotional engagement in school-maker education. Some implications for integrating maker education into school education and cultivating students’ creativity were discussed.

Self-regulated learning (SRL) is crucial for academic success in online learning. Previous studies have employed a variable-centered approach to examine the relationship between students’ SRL and a variety of determinants and consequences. However, few studies employ a person-centered approach to categorize students’ self-regulated learning and examine its predictors and outcomes, especially the non-academic outcomes. Therefore, this study employed a person-centered approach to identify profiles of self-regulated learners and investigate how SRL profile membership is predicted by factors in an online learning environment as well as the differences in learning engagement and well-being across SRL profiles. This study surveyed 385 college students from China. Four SRL profiles were identified using latent profile analysis (LPA), namely: low, below average with high ES, average, and high SRL profiles. Results indicated that the four profiles differed in the extent to which students employed SRL strategies. Additionally, we ran the three-step (R3STEP) command to examine the predictive role of online learning environments (OLE). Finally, the Block-Croon-Hagenaars approach (BCH) was conducted to reveal the differences in learning engagement and well-being across SRL profiles. The multinomial logistic regression results indicated that SRL profile membership is significantly predicted by contextual factors, including pedagogical, social, and technical affordances. The behavioral, cognitive, emotional engagement, and well-being differed significantly among the four profiles. More specifically, the factors of OLE are antecedents of SRL profile membership, and SRL could enhance learning engagement and well-being. The findings contribute to a deeper understanding of students’ self-regulated learning profiles and the underlying mechanisms of online learning engagement and well-being, offering practical implications for both educators and researchers in higher education. Moreover, this study provides theoretical and empirical implications for subsequent studies.