This paper explores the potential of Eye Movement Miscue Analysis (EMMA) as a method to evaluate the complexity of picturebooks as reading material for primary school children. While EMMA has been applied to examine reading processes and strategies, this paper reports on the first study using EMMA to examine classroom picturebook complexity and its implications for developing readers. This research found EMMA method revealed specific nuances for understanding children’s reading practices in response to the complexity of the text at hand. Drawing together an internationally established reading teaching resource, the text complexity guide (Pinnell & Fountas, 2007) with miscue analysis reading assessment and eye movement technology, this research sought to gain insights into potential areas of complexity or challenge in picturebooks commonly available in Australian school libraries and classrooms. The method shared here examines text complexity ratings, children’s reading performance, and eye movements, as they read in natural classroom settings. Analysis of children’s reading miscues revealed that readers encountered challenges not anticipated through the use of the text complexity guide. Argued in this paper is that EMMA methodologies could extend understandings about text complexity beyond established frameworks and hence guide future assessments.

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.

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.

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.  

This study applies explainable machine learning to identify which vocal attributes in a lecturer’s speech influence students’ views of a lecturer’s charisma, a key contributor to teaching quality. It further explores whether vocal qualities differ between male and female lecturers and how students of different genders respond to these differences, offering insights into voice-related factors that influence the impact of educators. Speech segments from YouTube videos featuring 200 native-English lecturers were evaluated by 900 students using charisma rating scales. A set of attributes related to three primary prosodic dimensions of voice - pitch, rhythm, and loudness - was computed. A random forest classifier was employed to predict the charisma level based on the speech attributes and to list and rank the attributes that contributed most to the prediction. The findings revealed prominent vocal attributes that achieved higher charisma scores in the students' ratings. Same-gender evaluations of charisma were mainly based on pitch, while cross-gender evaluations rely mostly on loudness or rhythm. The automated, interpretable method provides a reliable and efficient way to measure vocal charisma in academic lecturers. It can be adapted to examine additional individual factors that influence the perception of a lecturer’s charismatic presence. It may also be integrated into practice-based tools, designed to support instructors in improving their presentation skills. Our research bridges the fields of applied psychology and computer science to contribute to the development of educational technology.

Within the context of investigating belief systems, this work exemplifies a mixed-method approach. Two approaches are utilized to explore the philosophical, ontological, and epistemological assumptions that university students foster regarding the relationships between knowledge and reality. In the first step, written materials that elaborated on the matter at hand were subjected to content analysis with the assistance of Leximancer, a software that recognizes themes and concepts and turns textual data into concept maps that express networks of meaning. The second step involved conducting a cluster analysis on the data obtained from the questionnaire to identify distinct groups of participants who shared consistent epistemological viewpoints. The results obtained from the two approaches are in agreement and shed light on the prevalent epistemic inclination that favors a constructivist viewpoint. Discussion on the ramifications of the findings, as well as the methodological issues that are pertinent to the present illustration, is provided.

These days, many schools are reviewing their curricula, and Science, Technology, Engineering, Arts, and Mathematics (STEAM) education is one area where these changes are being applied. Because STEAM education integrates five subjects, it requires an approach in which teachers from these subjects work collaboratively. However, applying traditional assessment methods in STEAM education is challenging, as it requires teachers to jointly decide on appropriate assessment strategies. At present, no clear framework exists to support this process. This study examined the potential of the ordinal priority approach (OPA), a recently introduced method for multi-criteria decision-making, to facilitate teachers’ collaborative selection of assessment methods for STEAM education. It further explored the extent to which subject differences affect collaboration by comparing the decision-making of two groups: a homogeneous group (teachers of the same subject) and a heterogeneous group (teachers of different subjects). Pre- and post-questionnaires were administered to both groups to determine how the OPA can assist teachers in jointly developing a STEAM assessment method. Analyses of the responses identified differences in each group’s consensus-building process. The study revealed three key contributions of OPA to teacher collaboration in STEAM education: 1) it ensures that teachers from diverse subjects have their opinions considered; 2) its transparent decision-making process helps mitigate distrust during discussions; and 3) it promotes fair decision-making, unaffected by social power differences within the group. Based on these findings, OPA appears effective in converging diverse expert opinions through a clear decision-making process.

Vocational education plays a pivotal role in nurturing talent and supporting national development. However, challenges such as outdated talent development concepts, insufficient teacher training, and a lack of attention to soft skills cultivation from both schools and students have hindered the comprehensive development of secondary vocational students. This study aims to explore the direct effect of perceived teachers’ transformational leadership on the soft skills of 324 secondary vocational students in China and to examine the mediating role of students’ self-efficacy in this relationship. Using Structural Equation Modeling (SEM), the results show that teachers’ transformational leadership has a significant positive effect on students’ soft skills (β = 0.33, p < .01). Moreover, self-efficacy partially mediates this relationship (indirect effect β = 0.07, p < .05), accounting for 22.6% of the total effect. These findings suggest that teachers’ inspirational motivation, individualized consideration, and intellectual stimulation directly foster students’ communication, teamwork, and problem-solving skills, while also indirectly strengthening them by enhancing students’ confidence. Practically, the study underscores the need for teacher training in transformational leadership and for policy initiatives that integrate soft skills into vocational curricula.

The introduction of evolution in post-apartheid South Africa in 2008 presented significant challenges for teachers, due to both their own and their students' faith-based biases. This study investigates South African teachers' attitudes and understanding of evolution, utilizing Lemkian sociocultural theory and Vygotskian ZPD scaffolding. A mixed-methods approach was employed, including a Likert-scale questionnaire from 91 life science teachers and qualitative insights from open-ended questions. Results reveal a lack of enthusiasm for teaching evolution, influenced by personal religious beliefs and doubts about its scientific validity. Teachers often call for equal representation of evolution and creationism in classrooms. The preparation of teachers must address the stagnant discussion of evolution, while the life sciences curriculum emphasizes the Nature of Science, scientific literacy, and connections between science and society is compromised.

Team-based learning (TBL) is a popular form of collaborative learning designed to increase student engagement and motivate students to learn. A growing body of research, particularly in the health sciences, has demonstrated that TBL has positive impacts on student performance and classroom dynamics. However, much less is known about the student outcomes associated with TBL courses in undergraduate science, technology, engineering, and mathematics (STEM) education, fields in which active learning is especially important for student success and retention. To address this gap, we conducted a systematic review of the student outcomes associated with TBL in undergraduate STEM education. Using the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) method, we identified 55 empirical and qualitative research articles published between 2005 and 2024 that reported on TBL implementation practices and student outcomes. Importantly, we found that most studies described increased student performance and improved measures of classroom dynamics when TBL was compared to lecture-based teaching approaches. These findings provide further evidence that TBL is an effective instructional method and suggest that TBL can be implemented successfully across a wide range of student populations and undergraduate STEM disciplines.

Teacher-targeted victimization remains an under-integrated dimension of school violence research. This systematic review follows PRISMA 2020 guidelines and synthesizes 56 empirical studies (2015–2026) examining how teacher-targeted victimization is conceptualized and analyzed. The review maps patterns in geographic distribution, methodology, behavioral aggression forms, perpetrator framing, and the integration of institutional variables. Findings reveal the predominance of quantitative cross-sectional designs (75.9%). Physical (n = 28) and verbal aggression (n = 26) are the most frequently examined forms, with over half of the studies conceptualizing aggression as exclusively student-perpetrated. Institutional and governance variables remain limited: 84.8% of studies include no institutional variables beyond exposure or rely solely on general school climate indicators, while governance-level constructs appear in only one study. Drawing on Organizational Justice Theory and Institutional Theory, the review advances a Multilevel Institutional Accountability Model that conceptualizes teacher-directed aggression across behavioral exposure, institutional processing, and governance architecture. The findings highlight the need for greater integration of institutional and governance variables in future research.