The purpose of this systematic literature review (SLR) is to identify: (a) the topic of the study, (b) the research methods used, and (c) the results of research on Mathematics education in Malaysia. This study discusses the use of teaching aid (TA) in the field of syllabus and geometry for Form 2 students. The use of TA is considered highly successful and relevant for educators to improve the quality of the teacher’s instructions and students’ understanding. Therefore, using the rules of optional reporting items for systematic review and meta-analysis (PRISMA), a review system was carried out to determine the appropriate strategies and variables for the field. Four stages constitute the PRISMA paradigm used in this study: identification, screening, qualification, and admission. Using criteria opted by researchers from multiple searches, including Google Scholar, ResearchGate, Scopus, and Emerald, over 20 papers were identified for additional investigation. The data were then analysed quantitatively to describe the research's findings. From the results, two main research themes were found, namely (a) learning to use TA; and (b) the field of measurement and geometry of Mathematics. The results of the article analysis indicate that Mathematics education in Malaysia is currently at a moderate level and is ineffective at fostering students' understanding and interest. These results are anticipated to serve as the foundation for teachers, students, schools, and the Ministry of Education to undertake more engaging and interactive learning, particularly in the subject areas of mathematics and geometry.

The purpose of this study was to examine the potential impact of integrating the Smart Sender platform to gamify and automate L2 e-classes on students’ motivation, English language proficiency in reading and language use, engagement, and attitudes towards the platform. This experimental research employed a quasi-experimental design, specifically a non-equivalent control group design of a pre-test-post-test type. The study found that the use of chatbot-driven e-classes on the Smart Sender platform increased student motivation, improved their English language proficiency in reading and language usage, and enhanced their engagement within L2 e-classes. Students expressed their appreciation for the ease of use and usefulness of this chatbot-based tool for improving their English language skills. The findings showed that the scores for motivation, engagement, and English language proficiency increased for both the experimental and control groups from pre-test to post-test, with a large effect size observed for the experimental group and a medium effect size observed for the control group. The statistically significant difference in the mean scores between the experimental and control groups indicates the positive impact of incorporating gamified chatbot-driven sessions within L2 e-classes on the Smart Sender platform.

The 21st century marks a world where scientific, humanistic, technological, and societal issues are integrated. The complexity caused by the reciprocal effects among technology, engineering, cultural, and social values raises new ethical problems. This study addresses recent increased attention to the relationship between ethical awareness and engineering identity factors. Participants in this study were 246 undergraduate engineering students enrolled in a research university located in the northeast U.S. Bivariate correlation and ordinary least squares regression were conducted. Bivariate correlations showed that ethical awareness was positively correlated to engineering interest, engineering recognition, and engineering performance/competence, which are the three factors of engineering identity. The OLS regression showed the r2 value for the computed regression equation indicated that there was a non-zero relationship between the set of all independent variables (engineering identity factors, gender, ethnicity, years in school, and first-generation status) and the dependent (ethical awareness) and that the final set of independent variables accounted for approximately 22% of the variation in the dependent variable, Ethical Awareness. Undergraduate engineering education is a key to ensuring engineers will uphold the ethical values of the profession. This study contributes to the practical value of engineering ethics awareness by affirming that engineering identity is sound and should be applied in practice.

This article is aimed at integrating the Technological Pedagogical Content Knowledge (TPACK) system with the Didactic Suitability Criteria (DSC) of the Didactic-Mathematical Knowledge and Competences (DMKC) system to improve the reflection of prospective mathematics teachers on online classes. Thirteen prospective teachers, divided into two subgroups, participated in a training cycle that addressed both models. Each participant used and created indicators of reflection of the assigned model to analyze an online class on functions, and subgroups exchanged reflections to examine the class from the other model’s perspective. It was noted that the DMKC model allows for a broad analysis of the class but has limitations in assessing technology and the teacher's technological knowledge, while TPACK’s emphasis is on technology and teacher knowledge but does not explicitly address mathematical interaction or affective aspects. It is concluded that combining the TPACK model and the DSC of the DMKC model can generate more complete tools to reflect on online math classes and consequently allow for a comprehensive evaluation that covers both the mathematical content and the technological and pedagogical skills of the teacher.

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.

Developing efficient and reliable tools for assessing early mathematical skills remains a critical priority in educational research. This study aimed to develop and validate a brief version of the Prueba Uruguaya de Matemática (Uruguayan Mathematics Test, PUMa), a digital tool to assess mathematical abilities in children aged 5 to 6. The original test included 144 items covering both symbolic (66%) and non-symbolic (34%) tasks, such as approximate number system, counting, numerical ordering (forward and backward), math fluency, composition and decomposition of numbers, and transcoding auditory-verbal stimuli into Arabic-visual symbols. Unlike most existing tools that require individual administration by trained professionals and lack cultural adaptation for Latin American contexts, PUMa is self-administered, culturally grounded, and suitable for large-scale assessments using tablets. Using a sample of 443 participants and applying parametric and non-parametric models within the framework of Item Response Theory (IRT), along with correlations with TEMA-3, preliminary evidence was generated showing that the brief version retained precision and validity. The resulting shortened tests included 69 and 73 items for the parametric and non-parametric versions, yielding a balanced representation of symbolic (56%) and non-symbolic (44%) tasks. Despite item reduction, ability scores remained highly correlated between original and brief versions (r > .90), and both brief versions demonstrated strong internal consistency (α = .94). PUMa improves upon existing assessments by combining cultural relevance, group-based digital administration, and real-time data collection, offering a scalable solution for early identification and intervention. These features support personalized educational strategies that foster cognitive and academic development from the earliest stages.

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 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.

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.