This study investigated the influence of CThink4CS² Module on computational thinking (CT) skills of form four chemistry students. The CThink4CS² Module integrated CT with the Engineering Design Process (EDP) in chemistry class. This study utilized quantitative research methods and quasi-experimental design. Quantitative data were collected using the Computational Thinking Skill Test (CTST) which consisted of algorithmic reasoning, abstraction, decomposition, and pattern recognition constructs. A total of 73 students were in the treatment group (n=39) and control group (n=34). Experimental data were described by means of descriptive analysis and inferential analysis employing two-way MANOVA analysis. The results of the analysis indicated significant differences in CT skills between groups; students in the treatment group demonstrated better results compared to those in the control group. The paper provides insight into the integration of CT and EDP as effective pedagogical strategies for inculcating CT skills.

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.

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 incorporation of Computer Science teaching in educational systems has increased in recent years. Given international interest, Chile has promoted projects to promote the development of students' digital skills. Focusing on this new educational context, this research reports the results regarding the identification of computational concepts and practices that can be articulated with the contents and skills of the curriculum. of Chilean mathematics. for first grade of primary school based on the use of the Bee-Bot robot. For this, the study followed a qualitative approach, developing a case study of the Chilean study program with the content analysis technique and using, as analysis categories, computational concepts and practices from the field of educational computing. In total, 30 learning objectives of the study program were analyzed. The results indicate that, although there is little articulation between computational concepts and first grade content proposed in the curriculum, there is greater articulation between computational practices and mathematical skills suggested in the Chilean curriculum. It is concluded that Computational Thinking can be developed from the earliest school levels using the Bee-Bot robot (or similar), and this is demonstrated by the structure of the Chilean primary mathematics curricular program.

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.

Although research on ethnomathematics has been widely carried out, there is still little empirical evidence reporting the mapping and trends of ethnomathematical research in Scopus-indexed journals. The purpose of writing this article is to map trends in ethnomathematical research in Scopus-indexed journals in the range from 1986 to 2022. The fundamental tenet of ethnomathematics is to study, appreciate, and exclusively take into account the application of mathematics by ethnic groups. In other words, in understanding mathematics to look attractive, it is necessary to make a connection between everyday life and the realm of abstract mathematics. Scopus is a resource for further research, identifying scientific uniqueness and gaps. This study uses bibliometric analysis methods using VOSviewer, article searches using Publish or Perish (version 8), and SEforRA applications. Bibliometric research provides a reliable and impartial way to gauge the contribution of an article to knowledge advancement and is a tool that is often used to analyze trends and performance on certain subjects. These findings reveal an increasing trend in ethnomathematical research and identify some topics or keywords that could form the basis for additional studies. In conclusion, for future studies, bibliometric analysis will provide information and knowledge about the evolution of ethnomathematical research.

The research on the pedagogical knowledge of teachers in technological education arises from the need to address the problem of pedagogical practices, which are traditional. The classes are at the graduate level, focusing on lecturing the student while the student remains with a passive attitude. It is believed that making explicit that teachers' pedagogical knowledge will allow reflection and awareness, thereby transforming pedagogical practices. Therefore, the objective is to understand the teachers’ constructions on pedagogical knowledge in technology programs in Plant Operations and Industrial Instrumentation of the Faculty of Engineering in order to reconstruct it theoretically, as well as identify its characteristics and trace action routes for teacher training. In this way, it allows education to be accessible to low-income and resource-poor populations, whose purpose is to strengthen the productivity and competitiveness of the economy through the training of human talent according to the needs of the working sector in a unique context. This research uses grounded theory as a methodological tool for data processing. In this sense, data collection procedures such as in-depth interviews were conducted with 16 teachers and seven of them were related to the industry. Whereas, 9 were linked to the teaching(educational) sector including elementary, high school and college level. The results showed differentiated, and socially constructed pedagogical knowledge that responds to teachers’ nature in a particular context. These results contribute to consolidate a broad vision about the pedagogical knowledge’s characteristics that the teacher builds.

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 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.

Teachers’ access to technology in this day and age could have a positive effect on the teaching and learning of English first additional language (EFAL). This qualitative interpretive case study explored how limited access to technology resources affects the teaching practices of Intermediate Phase EFAL teachers in rural schools in Limpopo, South Africa. This study, underpinned by the Technology Acceptance Model (TAM), conducted semi-structured interviews to collect data from ten EFAL teachers who were purposively sampled. Thematic analysis was used to analyse the data. The study revealed that three of the ten EFAL teachers sampled integrated technology into their teaching despite challenges such as insufficient projectors, lack of learners’ smartphones and data bundles, and Internet connectivity. However, the other seven sampled participants did not use technology, citing a lack of digital tools and knowledge as a contributing factor. The study concludes that the lack of resources contributed to limited or no use of technology and the motivation to integrate technology into their lessons. Based on these findings, it is recommended that technological resources that can help EFAL teachers with digital teaching be made available so that they can integrate them to assist learners in developing language skills. Furthermore, in-service training and ongoing support should be provided to EFAL teachers to give them knowledge and skill to use available technology resources effectively.

The objective of this study is to analyze secondary school students' conceptual understanding of integer addition and subtraction. To achieve this, a test based on the multidimensional assessment approach Skills, Properties, Uses, and Representations (SPUR) was administered to 34 secondary school students selected through convenience sampling at a secondary school in Puebla, Mexico. The study employs a qualitative research methodology at a descriptive depth level. The analysis of student responses utilized basic descriptive statistics and the qualitative content analysis technique. Significant differences were found in the accuracy levels across the SPUR dimensions: skills (51.8%), properties (41.9%), uses (60.8%), and representations (20.6%). Students with a solid conceptual understanding of integer addition and subtraction demonstrated high accuracy levels in at least three dimensions. The main difficulties identified were the use of the negative sign and challenges in adding two negative integers. The SPUR approach is a viable alternative for multidimensionally analyzing and assessing conceptual understanding of integer addition and subtraction.

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 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 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.