21st-century learning requires teachers and students to integrate literacy skills, scientific literacy, mathematics, reading, writing, and technology in the learning process. Students must have initiative, discipline, responsibility, confidence, motivation for independent learning, and the ability to think critically about the problems presented. This study aims to determine students' autonomous knowledge and critical thinking abilities (CTA) using mobile learning technology (MLT). This research is a quantitative study involving 83 students from four junior high schools in the city of Mataram. The data collection for independent learning and students' CTA was carried out by giving tests and non-tests to students. The test conducted was a written test in the form of a description of 10 questions covering indicators of CTA. The non-test was conducted by giving a student learning independence questionnaire with as many as 15 statements, including five indicators of learning independence. This quantitative research data analysis uses the Rash modeling application with the help of Ministep software. The analysis results show that the learning independence of male and female students in the four junior high schools obtained a percentage of 77.38% in the “good” category. Each indicator of learning independence accepts a percentage above 70%, which is in the excellent category. Meanwhile, the CTA of male and female students from the four junior high schools obtained 75.28% in the “good” category. Each indicator of CTA also gets a percentage of more than 70%, meaning that each indicator is in a good category.

The need for early comprehension of scientific concepts in elementary school students is crucial. However, studies have indicated that some students lack a fundamental understanding of such concepts, highlighting the importance of effective teaching methods to improve scientific literacy at an early age. Therefore, this study aimed to determine the ability of Project-Based Learning in Science, Technology, Engineering, Art, and Mathematics (STEAM-PjBL) to improve students' scientific literacy, knowledge, and application of foundational scientific principles. A quasi-experimental methodology was employed, involving 22 female and 26 male fourth-grade elementary school students as participants. The study administered a Scientific Literacy Test (SLT) treatment to the students, followed by unpaired and paired t-tests to examine the impact of the STEAM-PjBL model on their scientific literacy skills. The results showed that STEAM-PjBL improved students' scientific literacy skills significantly more than traditional instruction. The experimental group outperformed the control group in the post-test, indicating the effectiveness of STEAM-PjBL. Therefore, the study recommends the adoption of the STEAM-PjBL model by elementary school teachers to improve students' understanding of fundamental scientific concepts.

The objective of this study is to create a tool for evaluating teachers’ effectiveness in boarding schools. Planning and preparation stages, instrument testing, and measurements were used in this study to implement research on the creation of the Mardapi model instrument. In order to generate instrument items, the planning and preparation stage tasks included a literature assessment of teacher performance appraisal manuals. Data were gathered utilizing documentation approaches, and descriptive and qualitative analysis was performed. Six specialists validated the built instruments, which were subsequently put through limited testing at two boarding schools and extensive trials at nine boarding schools in Surakarta residency area. The Aiken formula was used to examine the expert’s evaluation data, and confirmatory factor analysis was used to analyze the test results. The results of this study indicate that the instrument for assessing teacher performance in boarding schools meets the validity criteria. This is indicated by the existence of loading factor values ranging from .51 to .72 (>.4) and t-sign values ranging from 4.75 to 9.25 (>1.96) and meeting the requirements of a fit model since Chi-square = 1307.95 < 2524 (2*df), p-value = .17956 (>.05), and RSMEA value = .014 (<.08). The instrument items are reliable assessment packages, and this is shown by the reliability value of omega .967 > .70. Because there is a guarantee of validity and reliability, the test can be used to further assess teacher performance in boarding schools.

The purpose of this research is to develop a worksheet that can support a digital science practicum. Conducting a needs analysis comes first in the development of worksheets, then comes product creation. The product produced based on the needs test analysis is a worksheet with the help of science worksheet-augmented reality (SWAR). Two knowledgeable education professionals then evaluate the finished product and test it out on participants or students. The results of the study show that worksheets equipped with augmented reality media are necessary. Meanwhile, the resulting product is valid in an almost perfect category (Pe = 0.7219; Po = 0.9744; K = 0.9078). Student perceptions of the products produced are at an "excellent" level in each category (ME-Av, mean = 3.466; CO-Av, mean = 3.472; CT-Av, mean = 3.503; ST-Av, mean = 3,507; TA-Av, mean = 3.440; IN-Av, mean = 3.640; MO-Av, mean = 3.640). There is a significant inverse relationship between media features (ME-Av) and student interest (IN-Av) based on Pearson's correlation test with r = -.50 (p < .50). Further explanation is presented based on the data that has been collected.

In this article, we discuss the impacts of using 3D printing in education. Our primary goal is to evaluate the pedagogical impact of lessons utilizing 3D printing. We asked one hundred ninety students in four reference schools about the acceptability of existing 3D materials for teaching. Although the results show high attractiveness for the target group, it turned out that the available lessons primarily focus on the acquisition of technical skills and do not use the potential of education in other areas. We, therefore, proposed a concept for creating multidisciplinary teaching lessons that connect the technical part with other educational areas. We show the application of our concept in a newly developed lesson in biology, where we again evaluate its acceptance among the students. The results show that although the multidisciplinary lessons are more complex, they are still acceptable to the students, and, most importantly, they add significant educational value. Finally, we discuss the possibilities of incorporating 3D printing into the teaching curriculum. We also use a selected use case to illustrate the real-world problems we have encountered.

This study aims to analyse the relationship between critical thinking and the learning experience provided by instructors through active learning models, specifically Project-based Learning (PjBL) and Simulation-based Learning (SBL), to the potential achievement of academic performance in undergraduate students. The main analysis technique employed in this research was logistic regression, with additional analysis techniques including discriminant validity, EFA, as well as Kendall’s and Spearman’s correlation, serving as a robustness check. The results of this study indicate significant correlations and effects of critical thinking (CT) on academic performance. Higher levels of CT are associated with a greater likelihood of achieving academic excellence, as indicated by the cum laude distinction, compared to not attaining this distinction. Experiences of receiving PjBL (0.025; 6.816) and SBL (0.014; 14.35) predicted the potential for improving academic performance to reach cum laude recognition, relative to not achieving this distinction. Furthermore, other intercept factors need to be considered to achieve cum laude compared to not achieving cum laude. We recommend that policymakers in higher education, instructors, and others focus on enhancing critical thinking and utilizing both Pub and SBL as learning models to improve students’ academic performance.

Service-learning (SL) emphasizes the fusion and integration of community service and academic learning, while Physical Education (PE) is oriented towards community health and well-being, aligning with Sustainable Development Goals. The study's primary objective is to discern the benefits perceived by PE students when engaged in SL courses and to test the correlation between benefits and the motivational climate they experience. Additionally, the research explores potential gender-specific variations in students' attitudes. The research was conducted with a survey on a sample of 58 students responding to a Motivational Climate in Physical Education Scale (MPCES) and the SErvice LEarning Benefit Scale (SELEB), which assesses the motivation of students and their perceptions of SL benefits. Descriptive statistics was used to analyse the data. Pearson's correlation coefficient was used to test the relationship between the core constructs - SL benefits and student motivation, and t-tests to evaluate gender differences in SL benefits. Key findings underscore that students primarily perceived the greatest advantages from SL in the domain of knowledge application, with comparatively lower scores in general life skills. Notably, female students, on the whole, exhibited higher ratings in both SL benefits and student motivation compared to their male counterparts. Nonetheless, specific exceptions emerged in certain sub-scales, including social relatedness and ego climate within the MPCES scale, as well as critical thinking within the SELEB scale. According to the results, it is suggested that cultivating a student-centered learning environment can augment engagement and motivation in the realm of physical education (PE). Furthermore, the delineated gender differences offer valuable insights for educators, highlighting the need for tailored approaches to accommodate the diverse preferences and requirements of male and female students.

This study aims to analyze the effects of working memory capacity and learning styles of prospective mathematics teachers on their ability to solve higher-order thinking problems. In the present study, learning style was considered students' tendency to learn visually or verbally. In addition, the types of higher-order thinking skills (HOTS) problems are complex and non-complex. Multiple regression tests were used to analyze the effects of learning style and working memory capacity. An ANOVA test was also conducted to analyze the ability of each group to solve each HOTS problem. In addition, one hundred twenty-six prospective mathematics teachers voluntarily participated in this study. The study found that learning styles only affected visual problems while working memory capacity (WMC) only affected the ability to solve complex problem-solving skills. Furthermore, WMC affected the ability to solve complex HOTS problems, not non-complex ones. The ability of visual students to solve HOTS problems will greatly increase when the problems are presented in visual form. On the other hand, the obstacle for visual students in solving verbal problems was to present the problem appropriately in visual form. The obstacle for students with low WMC in solving complex HOTS problems was to find a solution that met all the requirements set in the problem.

The world eagerly anticipates advancements in AI technologies, with substantial ongoing research on the potential AI applications in the domain of education. The study aims to analyse publications about the possibilities of artificial intelligence (AI) within higher education, emphasising their bibliometric properties. The data was collected from the Scopus database, uncovering 775 publications on the subject of study from 2000 to 2022, using various keywords. Upon analysis, it was found that the frequency of publications in the study area has risen from 3 in 2000 to 314 in 2022. China and the United States emerged as the most influential countries regarding publications in this area. The findings revealed that “Education and Information Technologies” and the “International Journal of Emerging Technologies in Learning” were the most frequently published journals. “S. Slade” and “P. Prinsloo” received the most citations, making them highly effective researchers. The co-authorship network primarily comprised the United States, Saudi Arabia, the United Kingdom, and China. The emerging themes included machine learning, convolutional neural networks, curriculum, and higher education systems are co-occurred with AI. The continuous expansion of potential AI technologies in higher education calls for increased global collaboration based on shared democratic principles, reaping mutual advantages.

In the early stages of adopting online learning, both learners and teachers displayed resistance, but the COVID-19 pandemic has forced a widespread shift to digital learning. To facilitate this transition, there is a growing focus on highlighting the effectiveness of online learning, which directly impacts learning outcomes. This study investigates online learning effectiveness through an integrated framework that considers online assessment practices and online course design as independent variables, with online learning support as a moderating variable. Understanding the effectiveness of online learning is crucial as hybrid learning becomes the "new norm" in education, combining online and offline methods for teaching the digital generation. Using a quantitative research design involving 232 students at Universiti Kebangsaan Malaysia, the study found that online assessment practices and course design significantly influence students perceived learning outcomes in an online learning environment. Additionally, online learning support positively moderates this relationship. These findings offer a comprehensive perspective on how online assessment practices, course design, and support systems contribute to the quality of higher education in Malaysia amidst evolving educational practices.

Critical thinking is a skill that enables individuals to keep pace with changes and enhances crucial competencies for contemporary competitiveness. Many researchers have studied learning management approaches to develop students' critical thinking, resulting in a substantial body of knowledge but lacking clear systematic summaries. The researchers aimed to (a) examine the effect sizes and research characteristics influencing students' critical thinking, and (b) compare the effect sizes of learning management approaches after adjusting with propensity score matching from 108 graduate research published between 2002 and 2021. Data were collected using research characteristics recording forms and research quality assessment questionnaires. Effect sizes were calculated using Glass's method and analyzed through random effect, fixed effect, and regression meta-analysis. Findings revealed that (a) research on developing learning management approaches influences students' critical thinking at a high level (d ̅ = 1.669), with nine research characteristics, including the field of publication, courses, total duration, teacher learning process, learning media, measurement and evaluation, research design, research statistics, and research quality, statistically significantly influencing students' critical thinking, and (b) after adjustment, inquiry-based learning significantly influences students' critical thinking. Recommendations for developing students' critical thinking include learning activities that encourage problem exploration, expanding thinking through collaborative analysis, and applying diverse media and activity sheets tailored to context suitability.
 

Analytical thinking is crucial for developing problem-solving, decision-making, and higher-order thinking skills. Many researchers have consistently developed learning management models to enhance students' analytical thinking, resulting in extensive knowledge but lacking clear systematic summaries. This study aims to: (a) explore the effect sizes and research characteristics influencing students' analytical thinking, and (b) compare the effect sizes of learning management models after adjusting for propensity score matching. In exploring 131 graduate research papers published between 2002 and 2021, the research utilized forms for recording research characteristics and questionnaires for assessing research quality for data collection. Effect sizes were calculated using Glass's method, while data analysis employed random effects, fixed effects, and regression meta-analysis methods. The findings indicate that (a) research on learning management models significantly impacts students' analytical thinking at a high level (d̅ = 1.428). Seven research characteristics, including year of publication, field of research, level, duration per plan, learning management process, measurement and evaluation, and research quality, statistically influence students' analytical thinking, and (b) after propensity score matching, learning through techniques such as KWL, KWL-plus, Six Thinking Hats, 4MAT, and Mind Mapping had the highest influence on students' analytical thinking. Recommendations for developing students' analytical thinking involve creating a learning management process that fosters understanding, systematic practical training, expanding thinking through collaborative exchanges, and assessments using learning materials and tests to stimulate increased analytical thinking.

With the current rate of technological advancements, higher education institutions around the world are increasingly adopting a wide variety of technology-related approaches to instruction. One of the teaching strategies used on digital platforms that has been successfully and widely adopted in higher education institutions is blended learning (BL). The objective of this investigation is to provide a comprehensive examination of the research efforts on BL in the context of higher education (HE) over the past 20 years, including the rise in publications, the most cited scientific journals and sources, and the upcoming research topics. This paper uses bibliometric analysis with a dataset of 651 documents from Scopus data, including 638 authors from 95 countries published in 271 journal sources. The results of the study show that the top three countries for BL research in higher education are the United Kingdom, the United States, and Australia; the authors with the highest citation indexes are D. R. Garrison and B. Means, and the top two publishing sources are Education and Information Technologies and Internet and Higher Education. Based on the analysis, the main trends detected are (a) student participation and environment, (b) educational technology instructional innovation, (c) effective instructional strategies within the parameters of the COVID-19 pandemic, (d) effectiveness of evaluation in BL environments and (e) BL with Massive Open Online Courses (MOOCs) and Learning Management System (LMS) in HE. These findings offer meaningful insights to early career researchers who consult the publications and research lists above, as well as to policy makers who develop suitable BL in HE policies.

Successfully solving reality-based tasks requires both mathematical and text comprehension skills. Previous research has shown that mathematical tasks requiring language proficiency have lower solution rates than those that do not, indicating increased difficulty through textual input. Therefore, it is plausible to assume that a lack of text comprehension skills leads to performance problems. Given that different sociodemographic characteristics and cognitive factors can influence task performance, this study aims to determine whether text comprehension mediates the relationship between these factors and competence in solving reality-based tasks. Additionally, it examines the impact of systematic linguistic variation in texts. Using an experimental design, 428 students completed three reality-based tasks (word count: M = 212.4, SD = 19.7) with different linguistic complexities as part of a paper-pencil test. First, students answered questions about the situation-related text comprehension of each text, followed by a mathematical question to measure their competence in solving reality-based tasks. The results indicate that: a) Tasks with texts of lower linguistic complexity have a significantly higher solution rate for both text comprehension (d = 0.189) and mathematical tasks (d = 0.119). b) Cognitive factors are significant predictors of mathematical solutions. c) Text comprehension mediates the relationship between the impact of students’ cultural resources and cognitive factors and their competence to solve reality-based tasks. These findings highlight the importance of linguistic complexity for mathematical outcomes and underscore the need to reinforce text comprehension practice in mathematical education owing to its mediating role.

Augmented reality technologies can create unique interactive learning environments for students with special educational needs that enrich the learning process and provide immediate feedback. This research analyzed the use of augmented reality in teaching digital literacy courses for primary school children with special educational needs. The study involved a quasi-experiment with participants using a mobile augmented reality application to assess its impacts on learning outcomes. The results showed the positive effects of augmented reality on student achievement. The results highlight the potential of augmented reality in inclusive education. In addition, the findings emphasize the importance of further research and development in this area and an increased use of augmented reality to improve the educational experience of students with disabilities. In light of the results, we conclude with recommendations for integrating augmented reality into educational programs and improving educational practices.

Considering the importance of the results of national and international standardized tests, which are a benchmark for measuring educational quality, the objective of this research was to model strategies to improve the results of the evaluations, specifically the Saber 11 standardized tests. These tests are applied to students who finish their Vocational Education and Training (VET) in Bogotá, Colombia. To achieve this objective, we employed the Systems Dynamics methodology for a comprehensive analysis, which is a tool that allows for the analysis and projecting of the behavior of different systems, in which anticipation by means of modeling results over time is required. The modeling was conducted in two stages: First, a causal loop diagram and a stock-and-flow diagram that linked 45 variables were designed, showing the underlying physical structure of the system. Then, five groups of alternative simulations were conducted over a time frame of six years: Reference mode, student self-efficacy rate, management rate, teaching competencies rate, and educational policy. An increase in results was observed in each scenario. The combined activity of educational stakeholders is a notably effective strategy to achieve significant improvements. The data used for these simulations came from a six-year period of standardized test results in Bogotá. This period was selected to capture both recent trends and long-term outcomes, ensuring that the model reflects current educational conditions while allowing for meaningful trend analysis.

This study aims to design, produce, and validate an information collection instrument to evaluate the opinions of teachers at non-university educational levels on the quality of training in artificial intelligence (AI) applied to education. The questionnaire was structured around five key dimensions: (a) knowledge and previous experience in AI, (b) perception of the benefits and applications of AI in education, (c) AI training, and (d) expectations of the courses and (e) impact on teaching practice. Validation was performed through expert judgment, which ensured the internal validity and reliability of the instrument. Statistical analyses, which included measures of central tendency, dispersion, and internal consistency, yielded a Cronbach's alpha of .953, indicating excellent reliability. The findings reveal a generally positive attitude towards AI in education, emphasizing its potential to personalize learning and improve academic outcomes. However, significant variability in teachers' training experiences underscores the need for more standardized training programs. The validated questionnaire emerges as a reliable tool for future research on teachers' perceptions of AI in educational contexts. From a practical perspective, the validated questionnaire provides a structured framework for assessing teacher training programs in AI, offering valuable insights for improving educational policies and program design. It enables a deeper exploration of educational AI, a field still in its early stages of research and implementation. This tool supports the development of targeted training initiatives, fostering more effective integration of AI into educational practices.

This study examines the impact of Project-Based Learning (PjBL) on developing metacognitive skills among preservice science teachers (PSTs) in Northeast Thailand. A sample of 143 PSTs, including first-year students in General Biology 1, second-year students in General Physics 1, and third-year students in Basic Organic Chemistry, participated in an 18-week programme. The study aimed to assess changes in metacognitive skills before and after PjBL implementation, evaluate differences among academic years, and identify predictors of skill development. The methodology included a six-hour orientation workshop and a collaborative, project-based curriculum. Descriptive and inferential statistics were employed, with the item-objective congruence index (IOC) for content validity, paired samples t-tests for pre- and post-intervention comparisons, and Analysis of Variance (ANOVA) to examine differences across academic years. Multiple regression analysis was used to identify significant predictors of metacognitive skill development. Results showed significant improvements in metacognitive skills post-PjBL, with substantial enhancements across all subjects. ANOVA indicated significant differences among academic years, with third-year students demonstrating the highest metacognitive skill levels. Multiple regression analysis identified participation in PjBL and academic level as significant predictors of metacognitive skill development. These findings highlight the effectiveness of PjBL in enhancing metacognitive skills and underscore the importance of active learning and reflective practices in teacher education programmes. This study provides valuable insights into the impact of PjBL on PSTs' professional growth and instructional efficacy, preparing them for modern classroom challenges.

: In this study, we present a didactic experience carried out in a public university with 60 students enrolled in the 2nd year of the Primary Education Teaching Degree. This experience consisted of implementing a teaching and learning sequence in which proportionality problems (mathematics content) and pure substances and mixtures (experimental science content) were addressed together in an ecodidactic garden context. This work presents the results obtained through the analysis of the students' responses. Our findings suggest that pre-service teachers have difficulties similar to those of primary and secondary students in the use of measuring instruments and conversion units, as well as in the calculation of proportions in mathematics and conceptual errors at a microscopic and macroscopic level in experimental sciences. This study highlights the need to design and implement strategies to support students in their formative process in relation to the contents of proportion and matter. As an added value in our work, we emphasize the interdisciplinary connection between mathematics and experimental sciences, offering a more real-life perspective of science.

The use of technology in education aims to improve students' problem-solving skills so that they have the skills needed by 21st century society in dealing with various kinds of challenges and problems. This study was carried out aiming to obtain the characteristics of augmented reality-based learning media for mathematics learning in student problem-solving skill, and obtain the results of the average difference in the problem-solving abilities of junior high school students. This research and development (R&D) study, employing the (Analyze, Design, Develop, Implement, and Evaluate) ADDIE model, investigated Augmented Reality (AR)-based learning media for mathematics to enhance junior high school students' problem-solving skills. The aim was to identify characteristics of effective AR media and assess their impact on problem-solving abilities. Quantitative data, collected from student problem-solving tests, were analyzed using a t-test in SPSS. The AR media featured virtual manipulation, virtual measurement tools, and real-world problem exploration. While the experimental group using AR showed a higher average problem-solving score compared to the control group using Problem-Based Learning (PBL), the difference was not statistically significant (t (df) = 0.638, Cohen's d = 0.0876). This lack of significance, despite the higher mean, is likely due to a small sample size and the limited integration timeframe, coupled with pre-existing skill variations. Future research should address these limitations to further explore the potential of AR in mathematics education.