Factors influencing microgame adoption among secondary school mathematics teachers supported by structural equation modelling-based research

Exploring the factors affecting elementary mathematics teachers' innovative behavior: an integration of social cognitive theory

Teacher innovative behavior is one of the vital factors, affecting student engagement, addresses diverse needs, promotes critical thinking, fosters lifelong learning, and contributes to educational research and development. By encouraging and supporting teacher innovation, we may can ensure that education remains relevant, effective, and impactful in preparing students for the future. Teacher innovative behavior is also needed to improve the mathematics skills of elementary school students, and it is important to determine the predictors that significantly affecting Teacher innovative behavior. Therefore, this study aimed to develop a model that predicted possible factors affecting mathematics teachers' innovative behavior based on Social Cognitive Theory (SCT). Data were collected from 132 elementary school teachers in China to verify the model, and the analysis was conducted using a structural equation modelling approach. Theoretically, 10 of the 15 hypotheses were found to be significant. The results showed that facilitating conditions and self-efficacy significantly affect mathematics teachers' innovative behavior. Meanwhile, Technological, Pedagogical and Content Knowledge (TPACK) knowledge, Social Influences, Rewards, Work engagement and anxiety did not show any effect. The contribution developed a model and provided new knowledge about the factors affecting elementary school teachers' innovative behavior. Practically, this could be used to improve teachers' innovative behavior.

A structural equation model of online learning: investigating self-efficacy, informal digital learning, self-regulated learning, and course satisfaction

Introduction

English as a Foreign Language (EFL) education increasingly relies on online learning, necessitating a nuanced understanding of crucial factors impacting learning experiences. This research investigates the intricate relationships among online learning self-efficacy, online self-regulated learning, informal digital learning of English (IDLE), and online course satisfaction within the unique context of EFL learners.

Methods

The study involved 563 intermediate college students from various national universities in China. Structural Equation Modeling (SEM) was employed to analyze the data, providing comprehensive insights into the relationships among the identified variables.

Results

The results revealed significant insights. Both online learning self-efficacy and IDLE exhibited direct and positive influences on online course satisfaction. Furthermore, the study uncovered that online self-regulated learning acted as a partial mediator in the connection between online learning self-efficacy and IDLE with online course satisfaction. This mediation implies that learners' self-regulatory behaviors significantly affect how self-efficacy and informal digital language learning experiences impact overall satisfaction with online courses.

Discussion

The findings highlight the pivotal role of nurturing learners' self-efficacy beliefs, fostering IDLE, and promoting effective self-regulated learning strategies in the realm of online language learning. These initiatives are instrumental in enhancing learners' satisfaction and success in online courses.

Conclusion

The implications of these findings for EFL instruction are substantial. By emphasizing the importance of self-efficacy, IDLE, and self-regulated learning strategies, educators can significantly contribute to creating more satisfying and successful online learning experiences for EFL students.

The impact of self-directed learning experience and course experience on learning satisfaction of university students in blended learning environments: the mediating role of deep and surface learning approach

Introduction

With the rapid development of technology and the evolution of educational ideas, the blended learning model has become the new norm in higher education. Therefore, based on Biggs' learning process theory, this study aims to investigate the relationships between learning experience, learning approaches, and learning satisfaction of university students within the Chinese blended learning context to explore the dynamic process and mechanism of blended learning.

Methods

The Chinese modified versions of the Self-Rating Scale of Self-Directed Learning, the Course Experience Questionnaire, and the Revised Study Process Questionnaire were administered to 939 Chinese university first-grade students (444 men, 495 women). The data were analyzed by using the covariance-based structural equation modeling (CB-SEM) technique.

Results

The results demonstrated that, among Chinese university students, there were significant correlations between the self-directed learning experience, the course experience, the deep learning approach, the surface learning approach, and learning satisfaction. Additionally, the learning approaches mediated the association between the self-directed learning experience and learning satisfaction and between the course experience and learning satisfaction.

Conclusion

This study provides insight into the facilitative effect of university students' self-directed learning experience and course experience on their learning satisfaction and how this effect is triggered through the mediating role of different learning approaches with the blended learning context. This study shows the learning behaviors and psychology in a blended learning environment, thus revealing the new learning characteristics of university students by integrating the self-learning characteristics of blended learning into the framework of learning process theory. The findings contribute to assisting blended learning providers in delivering targeted interventions to enhance students' learning satisfaction.

Examining the effectiveness of gamification as a tool promoting teaching and learning in educational settings: a meta-analysis

The integration of gamification into educational settings has gained recognition for its potential to boost student motivation, engagement, interest, and learning outcomes. Despite its popularity, research on gamification has produced mixed results regarding student learning outcomes. This meta-analysis aims to synthesize the existing empirical evidence on the effectiveness of gamification as a tool for promoting teaching and learning in educational settings. Forty-one studies with 49 independent samples involving more than 5,071 participants were included in our analysis. Results from random effects models showed an overall significant large effect size (g = 0.822 [0.567 to 1.078]). The research performed the moderator analysis to scrutinize the effects of a number of factors on the relationship between gamification and student learning outcomes. The study uncovered significant moderating effects for user type, educational discipline, design principles for educational gamification, duration of "gameful" experience, and learning environment. However, measurement of student outcomes and publication type did not appear to have any significant moderating effect. Those findings hold important implications for improving and implementing gamification to promote teaching and learning in future research.

Analysis of Factors Affecting Academic Performance of Mathematics Education Doctoral Students: A Structural Equation Modeling Approach

Student academic performance is an important indicator of doctoral education quality, but limited research has focused on how multiple influential factors of doctoral students' academic performance work together. This study aims to explore the factors significantly affecting the academic performance of mathematics education doctoral students in Indonesia. Several factors were recognized from prior studies, such as the fear of delay, student engagement, parental support, teacher support, facilitating conditions, stress level, and well-being. An online questionnaire was designed and answered by a total of 147 mathematics education doctoral students. The partial least squares structural equation modeling (PLS-SEM) approach was adopted to analyze the questionnaire data. The results suggested that teacher support had the strongest positive effects on mathematics education doctoral students' academic performance in Indonesia. Student engagement was the most significant positive factor in improving doctoral students' well-being, while parental support could most significantly reduce their stress levels. Practically, these results are expected to provide implications to universities and supervisors regarding the improvement of doctoral students' well-being to promote their academic success and further the quality of doctoral programs in education. Theoretically, these results can also contribute to building an empirical model that can be used to explore and explain how multiple factors could affect doctoral students' academic performance in other contexts.

Key Factors Affecting Mathematics Teachers' Well-Being and Stress Levels: An Extended Engagement Theory

The mathematics teachers' profession often has many challenges. It also occupies important positions at the K-12 education level, in which mathematics knowledge is the basis of all scientific fields. This tends to cause high-stress levels and a negative effect on well-being. Mathematics teachers' well-being has been less examined, and therefore this study aims to determine the factors affecting mathematics teachers' well-being and stress levels. The 210 data points collected from Chinese mathematics teachers using a web-based questionnaire were analyzed for reliability and validity, then model fit and SEM were applied for model validation after removing 3 invalid data points and incomplete responses. The results showed that behavioral and cognitive engagements significantly affect teachers' well-being, while the affective engagement was insignificant. The TPMK was the strongest significant predictor that had a positive impact on improving well-being and reducing stress levels. In addition, the stress level of mathematics teachers was influenced by gender and age. Finally, it was proven that teachers' well-being significantly reduced stress levels. This study's implication was to provide information on how to reduce stress levels.

Self-regulated learning, online mathematics learning engagement, and perceived academic control among Chinese junior high school students during the COVID-19 pandemic: A latent profile analysis and mediation analysis

Objectives

Under the COVID-19 prevention and control policy, online learning has been widely used. The current study aimed to identify latent profiles of self-regulated learning in the context of online mathematics learning during the recurrent outbreak of COVID-19, and examine the mechanisms underlying the relationship between self-regulated learning and online mathematics learning engagement among Chinese junior high school students using variable-and person-centered approaches.

Methods

A sample of 428 Chinese junior high school students (47.66% female) completed questionnaires on self-regulated learning, perceived academic control, and learning engagement. Mplus7.0 was used to analyze the latent classes of self-regulated learning. A mediation model was conducted using the software SPSS PROCESS macro.

Results

Three profiles of self-regulated learning were identified and named as low self-regulated learning (16.12%), medium self-regulated learning (43.23%), and high self-regulated learning (40.65%). In the mediating analysis, results of the variable-centered approach showed that perceived academic control mediated the effects of self-regulated learning on learning engagement. For the person-centered approach, we selected the low self-regulated learning type as the reference profile, and the analysis revealed that compared with the reference profile, perceived academic control partially mediated the link between the medium self-regulated learning profile and learning engagement; perceived academic control partially mediated the relationship between the high self-regulated learning profile and learning engagement.

Conclusion

This study showed the heterogeneity in the online mathematics self-regulated learning patterns of Chinese junior high school students during the COVID-19 pandemic, revealing the internal mechanisms of Chinese junior high school students’ online mathematics learning engagement using variable-and person-centered approaches. Furthermore, the findings of the study have important implications for promoting online mathematics learning engagement among junior high students during the pandemic.