Increasing the number of entrepreneurs is not just a school task, it requires joint work between educational institutions and the community. Using structural equation modeling, this research aims to investigate the role of community in promoting entrepreneurial careers for students, by adding achievement motivation, entrepreneurial attitudes, and entrepreneurial intentions as predictor variables. The population of this research was high school students in urban areas, and the sample was taken based on convenience sampling, with a total of 300 students participating. Data were analyzed using EFA, CFA, and structural model evaluation using SPSS 24.0 and AMOS 24.0. The research results show that all hypotheses are accepted, meaning that community support influences students' entrepreneurial career choices, as do other predictor variables. This study can provide guidance for developing educational strategies and policies that support the development of young entrepreneurs in the future, through predictor variables.

Teachers' classroom practice encompasses diverse facets of teacher behavior. Understanding teachers’ classroom practice is important as the literature has been well documented its association with student, teacher, and classroom outcomes. Positive teacher-student relationships and proper classroom management, both are important aspects of teachers’ classroom practices, have been empirically linked to increasing student academic performance and reducing problem behaviors. This study explored patterns of teacher classroom practices across teacher-student relationships and classroom management and validated them using a person-oriented approach, k-means clustering, on three sets of data with over 600 participants. Using indicators of classroom assessment scoring system (CLASS), three distinct teacher profiles were identified: supportive, intermediate, and detached. Supportive teachers demonstrated high levels of teacher-student relationships and classroom management, while detached teachers showed low levels of both. Intermediate teachers fell between these two groups. The study also compared these profiles based on teacher self-efficacy, work stress, and classroom climate. Supportive teachers had the highest classroom climate scores, followed by intermediate and detached. Work stress was comparable for intermediate and supportive teachers, but both were lower than detached. No group differences were found for self-efficacy. This study contributes to the understanding of teacher behaviors with students in the lower grades.

Mathematical modeling offers a promising approach to improving mathematics education. This study aims to determine if the concept of metacognitive awareness in the learning process is associated with mathematical modeling. This study also considers the interaction effect of sex and academic year level on both variables. Focusing the study on preservice elementary teachers might address potential issues and targeted intervention in their preparation program concerning their ability to teach and guide young learners in modeling activities. The research sample includes 140 preservice elementary teachers at Central Luzon State University, Philippines. Data collection used an adapted metacognitive awareness inventory and a validated researcher-made mathematical modeling competency test aligned with the K-12 mathematics curriculum in the Philippines. Results revealed that the preservice elementary teachers had a high metacognitive awareness and mathematical modeling competency, ranging from 22 to 31 out of 36 points. Besides, Factorial ANOVA indicates that academic year level positively affects both variables regardless of sex, and stepwise regression analysis unveiled that information management, declarative knowledge, and planning significantly predict 41.4% of the mathematical modeling competency variance. This suggests that developing metacognitive awareness supports preservice elementary teachers in performing modeling tasks that improve their competency level in mathematics.

This study is designed to illuminate the role of four key constructs—teacher-student relationships, peer networks, satisfaction with support services, and employability trust—in shaping the social capital within universities. Utilising a sample of 1902 working students derived from the Eurostudent VII survey data, this research applies both exploratory and confirmatory factor analysis to validate the proposed model. The findings indicate that all four constructs demonstrate statistically significant and positive associations with university social capital. Crucially, the measures of reliability and validity are within an acceptable range, lending credibility to the findings. The teacher-student relationship was found to be the most influential factor, highlighting its crucial value in the functioning of social capital inside universities. Along with providing a framework for future studies on the ever-changing nature of social capital in universities, the results highlight the significance of cultivating an interconnected academic community, which enriches the educational organisation as a whole.

This paper explores information related to misconceptions and conceptual change during the last thirty years 1992-2022 to be used as a preliminary study in science education. This study used bibliometric analysis with the help of the Scopus database. This paper used a bibliometric analysis study with the Scopus database and the help of MS Excel, VosViewer, and Rpackage software to visualize the data obtained. The results of this research found that Indonesian researchers have contributed the most in terms of the number of documents published in Australia and the United States. Additionally, research on these two topics has decreased since 2019 due to the Covid-19 pandemic. In addition, these findings present trends in the areas of misconceptions and conceptual change that can be used as baseline data for future research. Studies related to misconceptions will continue to develop because they cannot be separated from the inside of education, whether at any level of elementary school, middle school, or college. This is an opportunity that must be taken advantage of by institutions and policies in an effort to improve and create quality of education, teacher resources, and students.

The computing and creative skills of students in Indonesia are still low since the government has not focused on student creativity and computational empowerment programs. This research aims to develop a science, technology, engineering, art, mathematics, and reflection (STEAMER) hybrid learning project model for teachers' creative and computational thinking abilities, as well as analyze elementary school teacher candidates' perceptions of the use of STEAMER hybrid learning model to improve teachers' creative and computational thinking abilities. This research is development research with an analysis, design, development, implementation, and evaluation (ADDIE) model. The instruments used in this study were questionnaires and interviews with experts, lecturers, and elementary school teacher candidates. The research was conducted at eight universities in Indonesia with a total sample of 100 elementary school teacher candidates. Through quantitative and qualitative data analysis, the research results have developed the STEAMER hybrid learning project model based on learning theory, syntax, social systems, support systems, and the instructional impact of learning models. The results of the validation show that the developed learning model is feasible in terms of model, material, media, and language experts. The model is suitable for elementary school teacher education. Furthermore, based on the perceptions of the teacher candidates, it is stated that the STEAMER hybrid learning project can develop the ability of the teacher candidates to think creatively and computationally.

Although research on ethnomathematics has been widely carried out, there is still little empirical evidence reporting the mapping and trends of ethnomathematical research in Scopus-indexed journals. The purpose of writing this article is to map trends in ethnomathematical research in Scopus-indexed journals in the range from 1986 to 2022. The fundamental tenet of ethnomathematics is to study, appreciate, and exclusively take into account the application of mathematics by ethnic groups. In other words, in understanding mathematics to look attractive, it is necessary to make a connection between everyday life and the realm of abstract mathematics. Scopus is a resource for further research, identifying scientific uniqueness and gaps. This study uses bibliometric analysis methods using VOSviewer, article searches using Publish or Perish (version 8), and SEforRA applications. Bibliometric research provides a reliable and impartial way to gauge the contribution of an article to knowledge advancement and is a tool that is often used to analyze trends and performance on certain subjects. These findings reveal an increasing trend in ethnomathematical research and identify some topics or keywords that could form the basis for additional studies. In conclusion, for future studies, bibliometric analysis will provide information and knowledge about the evolution of ethnomathematical research.

The main thrust of the study was to explore the third-year English student’s sentiments on the application of the artificial intelligence (AI)-integrated paraphrasing tools. Specifically, it aimed to investigate the benefits and drawbacks brought by AI paraphrasing tools towards the writing skills of the students. The investigation utilized a semi-structured interviews with an open-ended questionnaire using an audio-video recorder. The data gathered were interpreted using the Thematic Analysis of Braun and Clarke. The study was carried out at one of the campuses of a state university located at Candijay, Bohol, Philippines. Using the Purposive sampling technique, twelve (12) respondents provided information on the research endeavor. The findings revealed that students had a positive opinion of AI-integrated paraphrase tools: they saw them as helpful resources that significantly improve their academic writing process; it includes plagiarism reduction, efficiency, and timesaving, and aids in rephrasing text. The findings also revealed the risks and issues of using AI-integrated paraphrasing tools, such as Prone to plagiarism, automated suggestions dependency, and loss of original meaning and context. With that, the students showed how they deal with those risks and issues, including as responsible users and thorough editing and reviewing. In accordance with the study, students are encouraged not to rely excessively on AI-integrated paraphrase tools, even though they can improve their writing abilities. This research emphasizes that students play a pivotal role in ensuring the appropriateness of texts generated by AI-integrated paraphrasing tools by mastering the art of proper paraphrasing.

The study investigated the effects of utilising English as the primary teaching language on the academic development of Grade 4 (Gr4) learners, specifically focusing on the Life and Living (L&L) component of Natural Sciences (NS). Gr4 learners commonly transition to English as the Language of Learning and Teaching (LoLT), relegating native languages such as Sesotho to mere study subjects. This shift often results in comprehension and retention challenges, hindering students' academic achievements. By employing a quasi-experimental research design, the study used a purposefully selected sample of 80 Gr4 students from two primary schools. The control group (45 learners) received English instruction from Grade R to Grade 7, while the experimental group (35 learners) switched from Sesotho to English in Gr4. Both groups underwent pre-tests and post-tests, revealing statistically significant differences favouring the experimental group. These findings support the research hypothesis that introducing English as the LoLT as early as Grade R has a significant impact on learners' performance, particularly in NS. It is recommended that English be adopted as a medium of instruction for NS, as this better prepares students for future academic challenges.

Formal publications in the area of educational leadership and management (EDLM) can be traced back more than a century. The 1950s saw the emergence of reviews of these EDLM works. Unfortunately, these reviews were limited because they were not systematic. Sometime after the establishment of the Campbell Collaboration as the standard for systematic reviews in the social sciences in 2000, scholars began conducting systematic reviews of the EDLM literature, including the African EDLM literature. However, little is known about the quality of this latter corpus of systematic reviews. Therefore, in this article, a systematic review of systematic reviews — a meta-systematic review — was conducted on the African EDLM literature. This meta-systematic review revealed 42 systematic reviews. The quality of these reviews was assessed using Hallinger’s analytical rubric for conducting systematic reviews, which led to the identification of strengths and weaknesses of these reviews, as well as a set of exemplary reviews. These findings offer actionable insights for policymakers and practitioners by highlighting the need for targeted training and resources to improve systematic reviews' conceptual, methodological, and reporting quality, thereby enhancing their utility for evidence-based decision-making and educational policy development.

Recent studies identified that faculty research productivity increased when they felt competent in conducting research. Faculty level of research competency varies due to academic training, context, country, discipline, and experiences; however, what is faculty research competency? The core competencies of faculty research are unclear; thus, the current study systematically reviewed the literature. Researchers used Boolean searches of four popular databases to identify 553 articles for first-level screening. These yielded 46 peer-reviewed journal articles for full-text analysis, six of which focused on faculty populations (40 on non-faculty). Six core components of faculty research proficiency were identified: finding and reviewing literature, planning a study, collecting and analyzing data, writing research, disseminating research findings, and managing research projects. Compared to non-faculty populations, faculty are uniquely more engaged in research project management. Researchers also identified 18 sub-competencies that will help to measure faculty research competency more reliably in the future. Finally, as the identified studies relied on self-reported measurements that may carry self-representation bias, an aspirational implication is to develop a competency-based diagnostic test for measuring faculty research competence.

This study examines the impact of digital tools on fraction comprehension among 5th-grade students with learning difficulties in mathematics. It assesses the effectiveness of three teaching methods: educational software, video tutorials, and their combination. The research involved 252 students from 8 state-funded elementary schools, employing a quantitative experimental design with pre- and post-test assessments. Grounded in Constructivist Learning Theory and Technological Pedagogical Content Knowledge (TPACK), this research explored how technology can enhance mathematical understanding. Results indicated that the combined method achieved the highest improvement (58%, p < .001, Cohen’s d = 3.03), significantly outperforming educational software alone (33%, p = .015, Cohen’s d = 2.52) and video tutorials alone (7%, p = .987, Cohen’s d = 0.14). These findings highlight the substantial benefits of integrating diverse digital tools to effectively support mathematics learning among students facing additional educational challenges.

In primary and middle schools in China, banzhuren is the teacher responsible for managing and overseeing a specific class of students. The lower job satisfaction of banzhurens has been a longstanding issue. This study employs a quantitative method to investigate the impact of banzhurens' self-efficacy and burnout on their job satisfaction. A total of 624 primary school banzhurens from G City (in Henan province, China) participated in an online survey assessing their perceived job satisfaction, self-efficacy, and burnout. The data were analysed using structural equation modelling analysis. The results revealed that (a) banzhurens' burnout negatively influenced their self-efficacy and job satisfaction; (b) banzhurens' job satisfaction was positively influenced by self-efficacy; (c) banzhurens' self-efficacy could mediate the adverse effects of burnout on job satisfaction. Therefore, we suggest that banzhurens' job satisfaction can be enhanced by increasing their self-efficacy, particularly in terms of communication with leaders, and by reducing their burnout.

This PRISMA-based systematic review analyzes how artificial intelligence (AI) and Machine Learning (ML) are integrated into educational institutions, examining the challenges and opportunities associated with their adoption. Through a structured selection process, 27 relevant studies published between 2019 and 2023 were analyzed. The results indicate that AI adoption in education remains uneven, with significant barriers such as limited teacher training, technological accessibility gaps, and ethical concerns. However, findings also highlight promising applications, including AI-driven adaptive learning systems, intelligent tutoring, and automated assessment tools that enhance personalized education. The geographical analysis reveals that most research on AI in education originates from North America, Europe, and East Asia, while developing regions remain underrepresented. Without strategic integration, the uneven implementation of AI in education may widen social inequalities, limiting access to innovative learning opportunities for disadvantaged populations. Consequently, this study underscores the urgent need for policies and teacher training programs to ensure equitable AI adoption in education, fostering an inclusive and technologically prepared learning environment.

Students are among the most vulnerable populations during periods of crisis, including war, economic collapse, and pandemics. These events extend beyond academic disruption, significantly affecting students' emotional and social well-being. Mental health challenges such as anxiety, depression, and behavioural changes are commonly reported, particularly among youth living in conflict-affected areas or economically disadvantaged households. This review examines the consequences of crises on school-aged students across both local and global contexts. A structured search strategy was employed to retrieve peer-reviewed articles published between 2005 and 2024 from databases including PubMed, ERIC, Scopus, and Google Scholar. The selected studies were thematically categorized into three primary domains: pandemics, economic hardship, and war-related trauma. The review emphasizes the identification of common psychological outcomes, contributing factors, and resilience strategies implemented at the school and community levels. The findings highlight the urgent need for early interventions, trauma-informed pedagogical approaches, mental health support programs, coping strategies, and emotional regulation skills. By examining the interplay between crisis-induced stress and student support mechanisms, this review seeks to inform educators, policymakers, and practitioners in their efforts to foster resilience and promote academic recovery.

This study delved into Terry Borton’s reflective model and 7E instructional model to produce comprehensive and guided tools that fit as observation and reflective tools for enhancing learners’ engagement and outcomes in Mathematics lessons. The aim was to gather insights that can inform strategies to adapt Borton’s model to produce tools to be used to observe and analyse 7E model-based Mathematics lessons to contribute to improved student outcomes. Literature information was used to explore, analyse, and synthesise the study’s related existing theories and models to provide a deeper understanding of constraints and prompt question descriptors to produce 21st-century tools to observe and reflect on a Mathematics lesson. After comparing different prompt question descriptors from different literature and Borton’s model, concise descriptors were retained for educational purposes to be analysed, considering the 7E model phases, to produce the guided tools. As a result, two products. “Classroom Observation-Guided Tool”, which includes a guided tool table with a last column for the observer to write comments during class. This column is used to identify gaps in student engagement and learning practices across the 7E phases, which may have been misused. The “Post-Lesson Discussion Guided Tool”, to make a positive post-lesson discussion session, enabling teachers to identify areas for improvement in student engagement to achieve better outcomes next time. Other researchers can study the applicability of 21st-century observation and reflection-guided tools to other subjects, exploring their long-term impact on teacher professional development to improve overall student achievement across all school subjects.

Self-report surveys are extensively utilized in educational research to understand students’ perceptions and experiences. However, younger children, particularly those in elementary school, may exhibit a tendency to provide socially desirable responses, potentially compromising the data quality. This study examined the prevalence and impact of socially desirable responses in self-report surveys administered to elementary school students. A total of 1,024 students from grades 4 and 5 in five elementary schools participated in the study. Socially desirable responses were measured using detection items embedded within questionnaires. The findings indicate that (a) more than 20% of elementary school students demonstrated socially desirable responses; (b) female students and those with higher academic achievement were more likely to provide socially desirable responses; (c) socially desirable responses skewed the sample distribution by inflating mean scores and reducing standard deviations; and (d) while internal correlations within scales remained relatively stable, external validity, as reflected in correlations between self-reports and academic performance metrics, was significantly affected after adjusting for socially desirable responses. These results underscore the importance of addressing socially desirable responses when interpreting self-report data from young students. The study concludes with practical recommendations for improving the validity of self-report surveys in educational research.

This study aimed to develop and validate a comprehensive core competency assessment instrument specifically designed for undergraduate students at a research-focused university. Despite growing emphasis on competency-based education (CBE), there are limited psychometrically sound tools tailored to evaluate students’ level of core competencies in research-intensive universities. The current study proceeded in three phases: (a) development of a conceptual framework comprising six core competencies: Integrated Thinking, Knowledge Inquiry, Creative Integration, Global Citizenship, Communication & Collaboration, and Self-Management; (b) item generation and expert validation; and (c) validation through exploratory and confirmatory factor analyses. The final instrument included 77 items across the six competencies. CFA confirmed adequate model fit (CFI = .934–.957; RMSEA = .057–.088). The results showed that the validated instrument can provide a reliable and comprehensive assessment for students' core competencies in research-oriented university settings. This instrument can provide guidelines for developing competency-based education (CBE) curricula in higher education, as well as criteria for evaluating and refining existing CBE programs. This instrument functions as both a psychometrically robust assessment tool and a practical guide for institutional enhancement. It enables precise measurement of students’ core competencies, offering evidence that can inform curriculum design, academic advising, and policy development. In addition, the validated framework lays a strong groundwork for future research to investigate the long-term effects of competency-based education on student achievement, career readiness, and personal development across various higher education settings.

Analysis of student grades and demographic data to understand the effects of modality and Covid-19 on academic performance is important for universities to understand the impact these factors may have on course grades. This study analyzes all the 615,964 complete undergraduate student-course records from Kennesaw State University (KSU) spanning from 2015 to 2024 to examine the impact of course modality and the Covid-19 pandemic on academic performance. The population dataset includes student demographics (e.g., sex, age, ethnicity), prior GPA, and course characteristics (e.g., department, modality). Descriptive statistics and trend analyses were employed to evaluate grade outcomes across in-person, online, and hybrid modalities over the 9-year period. Results indicate a temporary increase in mean course grades during the Covid-19 period, followed by a return to the pre-pandemic upward trend. Hybrid courses consistently exhibited the highest mean grades throughout the study period. However, consistent patterns across modalities, demographics, and academic units suggest that these factors have limited influence on grade outcomes. These findings raise questions about the reliability of GPA and course grades as indicators of learning success across different instructional contexts and student populations.