Teacher well-being has gained significant prominence in academic publications indexed by Scopus in recent years. This study employs rigorous bibliometric analysis to trace the evolution of teacher well-being literature, examining 326 relevant publications from 1995 to 2022. Our findings reveal two crucial inflexion points in 2013, driven by the global economic downturn, and 2020, propelled by the widespread repercussions of the COVID-19 pandemic, including teacher unemployment. These inflexion points underscore the real-world events' profound impact on academic discourse in teacher well-being. Traditionally, authors from the United States, Australia, and the United Kingdom have shaped this discourse. Dutch scholars have also gained recognition, accumulating substantial citations. This paradigm shift is paramount as emerging nations like Iran, Ireland, China, and Austria increasingly contribute, challenging the dominance of Western authors. This shift underscores the evolving dynamics of scholarly contributions in teacher well-being research, emphasizing the need for a more diverse and inclusive academic dialogue. This study provides a panoramic view of the trajectory of teacher well-being research, shedding light on the interplay between global events and scholarly responses. It highlights nations' evolving roles in shaping this discourse, acknowledging established influences while recognizing the contributions emerging from voices in the field. These findings enrich the global dialogue surrounding teacher well-being and offer insights into the dynamic forces shaping this vital field of study, compelling the academic community to adapt, diversify, and foster a more inclusive conversation on teacher well-being.

Students in mathematics classes do not understand the importance of sociomathematical norms in learning mathematics. This causes sociomathematical norms not to be teachers' focus when learning mathematics. Besides, there is no standardized instrument for assessing this norm, so developing this instrument is necessary to measure socio-mathematical norms in learning mathematics. This study aims to create and verify the psychometric validity of the sociomathematical norm scale. This research used a survey method with 505 senior high school students from Jakarta and West Java as respondents. The results showed that 25 items had convergent validity, with a loading factor value of > 0.700, meaning they could be declared valid. Concurrent validity indicates that each sociomathematical norms indicator is valid as a whole. Discriminant validity shows that the average variance extracted value on the diagonal is higher than the other values, so each item is declared valid. It was concluded that each item of the sociomathematical norms instrument has accuracy in its measurement function. The reliability test shows that each sociomathematical norms item is declared reliable. The reliability value of the sociomathematical norm item is .99, and the person's reliability is .86. Thus, the instruments developed can measure sociomathematical norms in learning mathematics.

This study investigated the extent to which demographic variables, principal support and teacher self-efficacy contribute to the collective teacher efficacy. In the study, a non-probability purposive sample was used, which included 761 teachers working in compulsory primary schools in all parts of the Republic of Croatia. The first part of the administered online questionnaire provided data on sociodemographic characteristics of the respondents, while in the second part, the following scales were used: The Principal Support Scale, The Teacher Sense of Teacher Efficacy Scale and The Collective Teacher Efficacy Scale. The results of the performed regression analyses show that: 1) the demographic variables - workplace, promotion to a higher rank and principal support have a predictive value in explaining teachers’ self-efficacy; 2) an average number of students per class, promotion to a higher rank, principal support, teacher engagement and teaching strategies have a predictive value in explaining collective teacher efficacy. The findings of this study will be discussed in terms of their potential impact and future research.

In the early stages of adopting online learning, both learners and teachers displayed resistance, but the COVID-19 pandemic has forced a widespread shift to digital learning. To facilitate this transition, there is a growing focus on highlighting the effectiveness of online learning, which directly impacts learning outcomes. This study investigates online learning effectiveness through an integrated framework that considers online assessment practices and online course design as independent variables, with online learning support as a moderating variable. Understanding the effectiveness of online learning is crucial as hybrid learning becomes the "new norm" in education, combining online and offline methods for teaching the digital generation. Using a quantitative research design involving 232 students at Universiti Kebangsaan Malaysia, the study found that online assessment practices and course design significantly influence students perceived learning outcomes in an online learning environment. Additionally, online learning support positively moderates this relationship. These findings offer a comprehensive perspective on how online assessment practices, course design, and support systems contribute to the quality of higher education in Malaysia amidst evolving educational practices.

The wide use of the Internet of Things (IoT) in all spheres of life has led to a surge of cyberbullying among learners worldwide. That is why it cannot be denied that underlying factors, manifestations, consequences, and preventive measures of cyberbullying improve the welfare and overall mental development of students. This systematic literature review examines the causes, effects, and preventive measures of cyberbullying based on empirical studies conducted on learners in various situations. The review will focus on existing material published between 2015 and April 2024. For the inclusion and exclusion of literature, the Scopus online database was employed, along with the guidelines of the PRISMA model. Of 1004 studies, 51 were closely reviewed to determine the responses to the objectives of this study. NVIVO-12 was used for both thematic and content analysis in this study. The results show that there are 29 causes, 12 forms, 31 effects, and 41 different preventives for cyberbullying. The results of this study will not only enhance the comprehension of various concerns for parents, guardians, policymakers, educators, and governments but also provide valuable insights to researchers for addressing this issue.

This research investigated the validity of measurement and causal model of online scam protection behavior (OSPB) among at risk Thai students. The sample comprised 286 high school students from three demonstration schools under the University. Data were analyzed using descriptive statistics, confirmatory factor analysis (CFA), and structural equation modeling (SEM). The factor loadings for all items satisfied the standard criteria with scores ranging from .40 to .80, item-total correlations ranging from .405 to .718, and Cronbach’s alpha coefficients ranging from .773 to .928. The modified model demonstrated a better fit with the empirical data (χ² = 47.62, df = 37, p = .113,  χ²/df = 1.287, RMSEA = .032, SRMR = .028, GFI = .97, CFI = 1.00, NFI = .99). All factors: a) awareness of online risks, b) inhibitory control, c) game-based learning, d) social support, and e) motivation to prevent online scams can predict 81% of OSPB. The motivation to prevent online scams strongly influenced OSPB, with an effect size of .60. Additionally, all factors can predict 88% of the motivation for online scam prevention, suggesting that Protection Motivation Theory (PMT) is a suitable framework for understanding and evaluating Thai students' preventive behaviors in online deception scenarios. This newly developed instrument is highly reliable and can be effectively used by researchers and educators to assess the risk of online fraud victimization among high school students.

Artificial intelligence (AI) has revolutionized higher education. The rapid adoption of artificial intelligence in education (AIED) tools has significantly transformed educational management, specifically in self-directed learning (SDL). This study examines the factors influencing Indonesian higher education students' intention to adopt AIED tools for self-directed learning using a combination of the Theory of Planned Behavior (TPB) with additional theories. A total of 322 university students from diverse academic backgrounds participated in the structured survey. This study utilized machine learning it was Artificial Neural Networks (ANN) to analyze nine factors, including attitude (AT), subjective norms (SN), perceived behavioral control (PBC), optimism (OP), user innovativeness (UI), perceived usefulness (PUF), facilitating conditions (FC), perception towards ai (PTA), and intention (IT) with a total of 41 items in the questionnaire. The model demonstrated high predictive accuracy, with SN emerging as the most significant factor to IT, followed by AT, PBC, PUF, FC, OP, and PTA. User innovativeness was the least influential factor due to the lowest accuracy. This study provides actionable insights for educators, policymakers, and technology developers by highlighting the critical roles of social influence, supportive infrastructure, and student beliefs in shaping AIED adoption for self-directed learning (SDL). This research not only fills an important gap in the literature but also offers a roadmap for designing inclusive, student-centered AI learning environments that empower learners and support the future of SDL in digital education.

This study examines teachers’ perceptions of assessment and their relationship with instructional practice in primary education. It examines whether teachers perceive assessment as a tool to support student learning and development or as a mechanism for ensuring educational quality through teaching evaluation and exam preparation. The research is based on a survey conducted with 396 primary school teachers in Croatia, including both lower and upper grades. Descriptive statistics, Pearson’s correlation coefficients, multiple regression analysis, and one-way ANOVA were employed to analyze the data. The findings indicate a statistically significant correlation between teachers’ perceptions of assessment and the assessment strategies they implement in the classroom. Formative assessment is widely supported, yet summative methods remain prevalent. Lower primary teachers apply formative strategy more frequently than their upper primary counterparts. Teachers with mentor status demonstrate a stronger inclination toward student-centered assessment practices and report applying them more consistently. The results highlight the prevalence of a hybrid assessment model in which teachers balance formative and summative approaches, seeking to meet institutional requirements while simultaneously supporting student development. The findings underscore the need for continuous professional development and systemic support to empower teachers in adopting assessment practices that effectively enhance student learning and elevate educational quality. Training programs should be designed to address the specific needs of primary teachers, recognizing differences between lower and upper levels, as well as subject-specific requirements in grades 5 through 8. A targeted approach would facilitate the effective integration of contemporary assessment strategies into everyday teaching, supporting student progress and educational improvement.

This study aims to develop and validate the Teachers' Spiritual Leadership Questionnaire (TSLQ) to assess teachers' spiritual leadership from students' perspectives. Grounded in the principles of spiritual leadership—Vision, Hope/Faith, and Altruistic Love—the TSLQ explores how teachers inspire, influence, and guide students toward both academic and holistic development. The study addresses the lack of assessment tools in educational settings and introduces a structured validation process to ensure the instrument's accuracy and reliability. The questionnaire was developed and refined through several stages using expert input, literature review, and statistical validation methods. A total of 402 students participated, and their responses were analyzed using factor analysis to examine the tool's structure and effectiveness. Findings confirmed that the TSLQ is valid and reliable, with strong alignment between items and the three key dimensions of spiritual leadership. The results supported the model's overall strength, indicating that the questionnaire effectively captures the intended constructs. The study concludes that the TSLQ is a sound instrument for understanding spiritual leadership in the classroom and can help educators and researchers better assess its impact on students' academic and personal growth. Further research is recommended to test the tool in different cultural and educational settings and to explore additional dimensions of spiritual leadership. This new tool offers valuable insights for enhancing teaching practices and promoting a supportive and values-driven learning environment.

The rapid integration of artificial intelligence (AI) technologies into the field of higher education is causing widespread public discourse. However, existing research is fragmented and lacks systematic synthesis, which limits understanding of how college and university students adopt artificial intelligence technologies. To address this gap, we conducted a systematic review following the guidelines of the PRISMA statement, including studies from ScienceDirect, Web of Science, Scopus, PsycARTICLES, SOC INDEX, and Embase databases. A total of 5594 articles were identified in the database search; 112 articles were included in the review. The criteria for inclusion in the review were: (i) publication date; (ii) language; (iii) participants; (iv) object of research. The results of the study showed: (a) The Technology Acceptance Model and the Unified Theory of Technology Acceptance and Use are most often used to explain the AI acceptance; (b) quantitative research methods prevail; (c) AI is mainly used by students to search and process information; (d) technological factors are the most significant factors of AI acceptance; (e) gender, specialty, and country of residence influence the AI acceptance. Finally, several problems and opportunities for future research are highlighted, including problems of psychological well-being, students’ personal and academic development, and the importance of financial, educational, and social support for students in the context of widespread artificial intelligence.