This study examines the transition challenges faced by students with learning disabilities (LD) from primary to secondary school, focusing on emotional, behavioral, and social aspects. Using a sample of 168 special education teachers, the study employs the Strengths and Difficulties Questionnaire (SDQ-Hel) to assess emotional symptoms, conduct problems, hyperactivity/inattention, peer relationship difficulties, and prosocial behavior before and after the COVID-19 pandemic. Statistical analyses, including t-tests and repeated measures ANOVA, reveal significant increases in emotional and behavioral challenges post-pandemic. Effect sizes (Cohen’s d) indicate moderate to strong impacts in key areas, with emotional symptoms (η² = .06) and hyperactivity/inattention (η² = .05) exhibiting notable changes. The findings highlight the necessity for targeted interventions, such as teacher training on emotional regulation strategies and structured transition programs. Implications for educators and policymakers include the implementation of inclusive practices and specialized transition support structures to mitigate these challenges and enhance the overall well-being of students with LD.

Artificial Intelligence (AI) is reshaping education across the Asia-Pacific, yet its integration depends on teachers’ readiness and perspectives. This study explores AI adoption among Vietnamese teachers, a critical lens for the region’s digital education reforms, using the Unified Theory of Acceptance and Use of Technology (UTAUT). Through Structural Equation Modeling (SEM) and Latent Dirichlet Allocation (LDA), we analyzed responses from 246 teachers nationwide. Results show attitude strongly predicts adoption intention, with privacy and ethical concerns shaping acceptance, though fears of AI dependence hinder uptake. Uniform challenges across urban-rural and STEM-non-STEM contexts suggest systemic barriers in Vietnam’s education system. Teachers foresee AI as a pedagogical assistant but highlight insufficient training and privacy risks as key obstacles. These findings underscore the need for Asia-Pacific-relevant policies—AI literacy programs, ethical governance, and equitable access—to foster sustainable integration. This research informs regional educational policy by offering a Vietnam-centric model for balancing technological innovation with pedagogical integrity, addressing shared challenges in the Asia-Pacific’s digital transformation.

This qualitative study explored the implementation of Differentiated Instruction (DI) in Philippine multigrade classrooms with the aim of understanding teachers’ experiences, strategies, and challenges, as well as developing a performance appraisal tool. Guided by its specific objectives, the research examined how teachers plan, deliver, and manage differentiated lessons while addressing the diverse learning needs of students across multiple grade levels. Findings revealed that effective DI is rooted in intentional instructional planning, including learner profiling, curriculum mapping, and flexible pacing. Instructional delivery was enriched through the use of thematic and multimodal strategies, ability-based groupings, and contextually relevant teaching aids, although technological access and training remained persistent barriers. Classroom management practices emphasized inclusive routines, peer collaboration, and adaptive learning spaces. Teachers also highlighted the importance of assessment tools and reflective teaching practices in continuously improving instruction. In response to these findings, the study developed the Multigrade Differentiated Instruction Performance Appraisal Tool (MDI-PAT), which synthesizes theoretical frameworks with authentic classroom practices. The MDI-PAT serves as both a self-assessment and professional development guide for multigrade educators, promoting ongoing improvement in DI competencies. The study concludes that enhancing teacher capacities in planning, delivery, assessment, classroom management, and reflective practice is essential for fostering inclusive and effective learning environments in multigrade contexts. The insights and tools presented provide a practical framework for educational stakeholders seeking to enhance multigrade instruction in resource-constrained settings.

Teachers’ self-efficacy in classroom management is essential to their professional identity and teaching quality. While contextual factors shape these beliefs, the role of pre-service teachers’ perceptions of teacher education courses in influencing self-efficacy through their classroom management beliefs remains underexplored. This study expands self-efficacy theory by proposing an integrated model in which beliefs serve as both a mediator and a moderator between course perceptions and classroom management self-efficacy, particularly in inclusive classrooms. It builds on previous evidence that pre-service teachers’ beliefs about proactive strategies partially mediate the relationship between their course perceptions and capability beliefs in proactive management practices. This leads to the proposal of a moderated mediation model to explore a more nuanced relationship by investigating whether pre-service teachers’ punishment-oriented classroom management beliefs alter the strength and direction of this partial mediation effect. Data collected online from 480 pre-service teachers enrolled in State University and National Colleges of Education in Sri Lanka, which were used in the previous study, were analyzed using SmartPLS4 structural equation modeling. The findings indicate that punishment-based beliefs negatively moderated the indirect partial effect of pre-service teachers’ perceptions of classroom management training on their self-efficacy for inclusive classroom management, mediated by preventative beliefs. This positive indirect effect was significant only when reactive punishment-based beliefs were at low to moderate levels. These findings suggest that an overreliance on reactive strategies diminishes the beneficial influence of teacher education on self-efficacy in implementing preventive measures for inclusive classroom management. The results emphasize the importance of fostering proactive beliefs through targeted training within initial teacher education programs, supported by dedicated engagement from teacher educators and policymakers.  

Educational researchers, as well as researchers in other disciplines, often work with ordinal data, such as Likert item responses and test item scores. Critical questions arise when researchers attempt to implement statistical models to analyse ordinal data, given that many statistical techniques assume the data analysed to be continuous. Could ordinal data be treated as continuous data, that is, assuming the ordinal data to be continuous and then applying statistical techniques as if analysing continuous data? Why and why not? Focusing on structural equation models (SEMs), particularly confirmatory factor analysis (CFA), this article discusses an ongoing debate on the treatment of ordinal data and reports a short review on the practices of conducting and reporting SEMs, in the context of mathematics education research. The author reviewed 70 publications in mathematics education research that reported a study involving SEMs to analyse ordinal data, but less than half discussed how data were treated or guided readers through the analysis; it is therefore harder to repeat such an analysis and evaluate the results. This article invites methodological discussions on SEMs with ordinal variables in the practices of educational research. Subsequently, a standard for reporting SEMs with ordinal data is proposed, followed by an example. This standard contributes to educational research by enabling researchers (self and others) to evaluate SEMs reported. The example demonstrates, using real-life research data, how two different approaches for analysing ordinal data (as continuous or as a product of discretisation from some continuous distributions) can lead to results that disagree.