This study sought to examine the influence of transcription skills, evaluated using graphonomic measures, on the proficiency of text generation in students attending primary schools in Spain. A longitudinal design was employed involving 278 Spanish students distributed across three cohorts (cohort 1: 1st-2nd-4th grade; cohort 2: 2nd-3rd-5th grade; and cohort 3: 3rd-4th-6th grade). Two data collection points were used to administer the graphonomic measures, and a composition letter task was conducted at the conclusion of the study. Four multigroup structural equation models were employed, examining the direct pathways from graphonomic measures (i.e., pressure, speed, pauses, and road length) on text generation (i.e., length, fluency, planning, revision, and organization). The models demonstrated a good fit to the data. The findings from the four models, analyzed within the three cohorts, indicated that the significant effect of transcription (i.e., handwriting) on text production was primarily observed in Cohort 1 (early grades), while no significant effects were found in Cohort 2 (intermediate grades). This suggests that the importance of handwriting in text production in a transparent orthography may be more pronounced during the initial stages of writing development when students are acquiring foundational writing skills.

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.

Evaluation of child-friendly school (CFS) policies is essential to determine the achievements of school efforts in reducing violence cases. This research aims to proving the reliability and validity of CFS policy evaluation instruments in elementary schools with different locations. This investigation uses the Context Input Process Product (CIPP) evaluation model to confirm the factor structure or dimensions of several observed variables (items) to evaluate the reliability and validity of the CFS policy evaluation tool in elementary schools. The validity and reliability of previously created instruments are evaluated quantitatively, but this study utilises different subjects and study sites. There were 320 respondents, with 145 school principals and 175 teachers taken randomly. Confirmatory factors analysis (CFA) results show goodness of fit (GOF), and the model is acceptable. The CFS evaluation instrument can be accepted after eliminating several question items and modifying them. All items of the teal instrument meet the goodness of fit criteria in terms of chi-square and root mean square error of approximation (RMSEA). The instrument for evaluating CFS policies in primary schools using the CIPP model has met a valid and reliable psychometric property test so that it can be applied.

The role of artificial intelligence (AI) in education remains incompletely understood, demanding further evaluation and the creation of robust assessment tools. Despite previous attempts to measure AI's impact in education, existing studies have limitations. This research aimed to develop and validate an assessment instrument for gauging AI effects in higher education. Employing various analytical methods, including Exploratory Factor Analysis, Confirmatory Factor Analysis, and Rasch Analysis, the initial 70-item instrument covered seven constructs. Administered to 635 students at Nueva Ecija University of Science and Technology – Gabaldon campus, content validity was assessed using the Lawshe method. After eliminating 19 items through EFA and CFA, Rasch analysis confirmed the construct validity and led to the removal of three more items. The final 48-item instrument, categorized into learning experiences, academic performance, career guidance, motivation, self-reliance, social interactions, and AI dependency, emerged as a valid and reliable tool for assessing AI's impact on higher education, especially among college students.

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 article investigates the adoption, simplification, and usage recommendations of the Indonesian Index of Learning Style Short Form (ILS-SF). The aim is to refine the initial Indonesian ILS, compare the suitability between engineering/non-engineering and high school/university, and assess their learning styles. The participants were 678 students (413 females), with an average age of 19.4±1.92 years. The methods used in this study were adopting the existing Indonesian version of ILS, simplifying–reducing the number of items, empirical verification (validity and reliability), and Indonesia data assessment. The results show that the original ILS could be simplified without sacrificing the quality of the model. On the contrary, validity and reliability measures have increased. Confirmatory Factor Analysis (CFA) supports a reduction from 44 to 15 items. It confirms the validity with favorable indices such as CFI (0.972), TLI (0.966), RMSEA (0.021), SRMR (0.049), and GFI (0.999)—Active-Reflective Cronbach's alpha at 0.507, Sensing-Intuitive at 0.590, and Visual-Verbal at 0.553. Indonesian ILS-SF is faster, simpler, more suitable for engineering than non-engineering, and more ideal for undergraduate than high school students. The analysis revealed that sensory (40.2%), active (18%), and visual (10.2%) preferences dominate among Indonesian students. This study highlights assessment tools tailored to diverse educational contexts.

There are studies in the learning management literature examining the measure of system usage, but few explore how users apply the software tools to achieve specific work tasks, which in turn leads to perceived benefits. In the context of distance education, this study focuses on how Learning Management Systems (LMS) are fully used by faculty for their instructional needs. It extends existing research on LMS adoption by investigating how faculty members or instructors use the LMS tools for effective class teaching to achieve educational outcomes. Four usage patterns were identified: communication, content management, assessment, and class management. A model is presented to examine how these usage patterns interplay to achieve the perceived benefits. Data were collected from 544 instructors using LMS, such as Blackboard Learn, etc. Structural equation modeling using LISREL was employed to assess the research model. The results suggest that the usage for communication, content, and assessment activities positively impacts the usage for class management. In turn, the usage for class management influences the net benefits perceived by the instructors, and the usage for content also impacts perceived net benefits directly. These results provide practical guidelines for LMS developers’ design improvements and institutions’ policies, such as training instructors to fully utilize LMS features to achieve the maximum benefits of distance education.