This research article focuses on the design and validation of a questionnaire to analyse future teachers' perceptions of professional skills through the use of Augmented Reality (AR) in higher education, specifically for students in the field of Educational Sciences. The sample consisted of 575 students of Early Childhood Education, Primary Education and Pedagogy during the academic year (2021/2022). The focus of this study is to authenticate a questionnaire that measures the influence of Augmented Reality (AR) on aspects such as situated learning, motivation, and the necessary instructional preparations for the successful integration of AR within classroom educational encounters. The questionnaire is an online Likert-type scale developed based on three dimensions: situated learning, motivation and training. The data were analysed using the Statistical Package for the Social Sciences (SPSS) version 25 and JASP 0.17.1. The questionnaire met the standards recommended for validation. However, improvements to the instrument are suggested. In conclusion, validation of instruments is necessary to gain a rigorous understanding of the impact of new learning environments.

Education systems worldwide have been significantly disrupted due to the COVID-19 pandemic, creating an immediate need for a revamp of conventional teaching and learning techniques. To explore how this has affected the educational landscape, a scoping review was conducted. This scoping review aimed to examine the changes that occurred in the education field and to explore how it has transformed the educational landscape review. Using Arksey and O'Malley's methodology, 51 articles were selected for analysis from two leading databases: Scopus and Web of Science. All chosen articles were then subjected to thematic analysis. Three main aspects impacted by this global event were uncovered, which are technological advancements and digital transformation, changes in pedagogy and teaching methods, and mental health and well-being issues. This scoping review provides valuable insights into one of the most critical sectors affected by COVID-19, which can assist with planning future strategies for similar crises.

Pre-service science teachers need to be aware of eco-literacy and biotechnology as they will teach science subjects to students from the perspectives of 21st-century skills. This study aimed to develop a web-based module on biotechnology and examine preservice science teachers’ eco-literacy skills after using the developed module. The study used a research and development design adopting Molenda’s product development model (Analysis, Design, Development, Implementation, and Evaluation/ADDIE). There were 60 students majoring in science education as the research participants. The data were collected using a needs analysis questionnaire, a curriculum analysis form, a validation sheet, tests, and a response questionnaire. The obtained quantitative data were analyzed using IBM SPSS 25 with descriptive statistical tests with Swanson’s quantifications. Results showed that the web-based module on biotechnology could be developed through ADDIE stages with experts’ high validity results (M = 4.59, valid with revision). The module significantly improved the teachers’ eco-literacy skills on biotechnology topics (F = 14.053, p = .000, N = 60). This result implies that the web-based module on biotechnology can assist preservice science teachers in improving their eco-literacy skills.

The objective of this research was to assess the efficacy of project-based learning in enhancing the analysis of student worksheets in the domains of Science, Technology, Engineering, Arts, and Mathematics (STEAM) with the integration of the ecoprint technique, focusing on its influence on student motivation and creativity. This investigation was conducted as a quasi-experiment involving a sample size of 150 students selected through cluster sampling. Data collection was executed using standardized tests, with instrument validity ascertained through the Aiken index and instrument reliability determined via Cronbach's alpha coefficient. Data analysis was performed using multivariate analysis (MANOVA) and descriptive quantitative methods. The study's findings reveal a significant disparity in the mean scores of both learning motivation and student creativity. In conclusion, the implementation of project-based learning coupled with STEAM-based student worksheet analysis utilizing the ecoprint technique yields a substantial enhancement in learning motivation and student creativity. These findings underscore the success of employing STEAM-based worksheets in conjunction with the ecoprint method to foster students' motivation and creativity, as ecoprint inherently encompasses all STEAM components within the manufacturing process.

The review article presents an analysis of the literature on environmental literacy in sustainable development. By utilizing techniques to examine multiple documents published between 2013 and 2023, including citation analysis, co-authorship analysis, subject area analysis, and keyword analysis, this study aims to provide valuable information and insights into the research landscape surrounding environmental literacy and its contribution to promoting sustainable development. A systematic search was conducted to gather several scientific articles, conference papers, and publications from the Scopus database from 2013 to 2023. The findings of this analysis shed light on authors, influential institutions, and active research groups that contributed to the study of environmental literacy and sustainable development. This comprehensive review offers an understanding of the state of research in this field while identifying areas for further exploration and research gaps. The insights gained from this study can be highly beneficial for researchers, policymakers, and practitioners seeking to advance knowledge and take action toward promoting literacy's role in sustainable development. This analysis is a foundation for advancing our understanding of literacy's significance while emphasizing its vital role in sustainable development efforts.

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.

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 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.

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.

This study evaluates the effectiveness of a twelve-week Inquiry-Based Science (IBS) program on enhancing science process skills and scientific knowledge among preschool children in Morocco. Conducted in a quasi-experimental setting, it involved 105 children (M = 60.46 months, SD = 4.32), with 37 in the IBS group and 68 in the control group. The program utilized the 5Es instructional model and the Engineering Design Process (EDP) to engage children in active, hands-on learning experiences. Statistical analysis demonstrated that the IBS group achieved substantial improvements in both science process skills and scientific knowledge relative to the control group, with between-group effect sizes (Cohen’s d) ranging from 1.02 and 2.31. These findings highlight the significant impact of structured inquiry-based approaches in early childhood education. The study underscores the need for integrating such methods into the preschool curriculum to foster scientific understanding and skills from a young age, thereby better preparing Moroccan children for future academic and professional challenges. The results advocate for educational stakeholders to consider adopting inquiry-based learning frameworks to enhance the overall quality of early childhood education in Morocco.

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.

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.

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.

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.

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.

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.

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.

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.

This study investigates how learning-oriented school cultures, conceptualized through the Schools as Learning Organizations (SLO) framework, relate to teacher self-efficacy, job satisfaction, and work effectiveness in primary schools within a centralized education system. While these constructs have received considerable attention in the literature, they have rarely been examined together within a unified organizational learning perspective, particularly in contexts marked by limited school autonomy. Using a cross-sectional survey design, data were collected from 94 teachers in nine public primary schools, alongside aggregated student ratings of instructional effectiveness from 364 pupils. The findings showed that learning-oriented school cultures were positively associated with teacher self-efficacy, job satisfaction, and work effectiveness. Teacher self-efficacy also partially mediated the relationship between SLO conditions and both job satisfaction and work effectiveness. These findings indicate that learning-oriented school cultures may strengthen teacher outcomes directly and indirectly by reinforcing teachers’ sense of efficacy. Thus, the role of school leadership in cultivating collaborative and inquiry-oriented professional environments is particularly important