This research investigates the impact of Non-digital Gamification (NDG) techniques on students' math achievement, focusing on Fractions. Utilizing a quasi-experimental design, the study involved 100 primary school students in Perak. Two groups were formed: the control group, which followed traditional teaching methods, and the experimental group, which experienced NDG learning approaches. The findings indicate that students using NDG perform better in math (fractions) assessments compared to those using conventional methods. This study provides empirical evidence supporting the efficacy of NDG in teaching Fractions. The results underscore the potential for educators to innovate and enhance gamification tools, particularly in mathematics, contributing to educational advancements aligned with the goals of the Malaysian Ministry of Education. © 2024, STKIP Siliwangi Bandung (IKIP Siliwangi). All rights reserved...

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Education in Malaysia has undergone transformation and reformation over decades to meet contemporary needs. In the era of Industrial Revolution 4.0 (IR4.0) has brought direct impact to the field of education, as a steppingstone for generating future workforce. To meet these demands, 21st century learners who have the potential to shape a competitive future nation by possessing 21st century skills: critical thinking, creativity, collaboration, and communication. Therefore, the transformation in learning and teaching practices is necessary following the rapid development in information, communication, and multimedia technology. Even now, Malaysian mainstream educators continually report that they need better understandings and knowledge to be proficient in supporting individualized, personalized, and differentiated learning to stimulate the improvement of learner-centred learning, not the traditional teaching and learning process with teacher-centred. This study upholds a new defining on.....

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Background: Eurycoma longifolia (E. longifolia), Labisia pumila (L. pumila), and Orthosiphon stamineus (O. stamineus) are popular species known for their therapeutic properties. An increase in local demand for herbal products makes them susceptible to adulteration, which poses a risk to their safety and efficacy. Current identification methods, such as organoleptic, microscopic, and macroscopic analysis, need to be revised to identify plant species in highly processed herbal products due to their limited ability to detect morphological features and provide comprehensive plant taxonomy information. Methods: This research objective was to develop a simple, reliable, and accurate DNA molecular identification method based on polymerase chain reaction–restriction fragment length polymorphism (PCR–RFLP) for E. longifolia, L. pumila, and O. stamineus, used to validate the species identification for herbal products. PCR–RFLP was developed for rapid identification using restriction enzyme.....

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This article aims to address the challenge of predicting the salaries of college graduates, a subject of significant practical value in the fields of human resources and career planning. Traditional prediction models often overlook diverse influencing factors and complex data distributions, limiting the accuracy and reliability of their predictions. Against this backdrop, we propose a novel prediction model that integrates maximum likelihood estimation (MLE), Jeffreys priors, Kullback-Leibler risk function, and Gaussian mixture models to optimize LSTM models in deep learning. Compared to existing research, our approach has multiple innovations: First, we successfully improve the model’s predictive accuracy through the use of MLE. Second, we reduce the model’s complexity and enhance its interpretability by applying Jeffreys priors. Lastly, we employ the Kullback-Leibler risk function for model selection and optimization, while the Gaussian mixture models further refine the capture o.....

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The rapid advancements in technology have opened up new doors for both teachers and students to explore, learn, and create in innovative ways. However, this progress has also brought forth new challenges and complexities that demand a deeper understanding of the use of technology in art education. In this context, bibliometric analysis has emerged as a potent tool to examine emerging trends in the intersection of technology and art education. Employing the PRISMA approach (Preferred Reporting Items for Systematic Review and Meta-Analysis) and utilizing relevant Scopus databases with standardized procedures that ensure comprehensiveness and replicability, this bibliometric study identified 29 articles. The number of published articles in 2022, at 12, exceeded that of 2021, with only 6. Furthermore, the study highlighted the top 10 countries conducting research in technology and art education, with China having 17 studies, followed by the United States with 3 and Australia with 2. The to.....

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The University Course Timetabling Problem presents a complex optimization problem as it seeks to meet the diverse requirements and constraints of a university's academic program through efficient timetabling. The objective of this research is to conduct comprehensive review of existing studies on optimization approaches in optimizing university timetable problems. The aim of the comprehensive studies is to further analyse the existing studies to discuss comparative studies to compare the performance of the approach methods in satisfying the constraints involved in university timetabling. The methodology used for this paper is systematic literature review which brought three main themes such constraints, optimization approaches, and datasets involved in University Course Timetabling Problem. The result shown that the majority of approaches involved hybrid approaches. In conclusion, this comprehensive review summarizes the constraints, optimization approach and datasets involved Universi.....

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This study explores the application of virtual reality technology and traditional offline hybrid teaching mode for the specialized course “Animation Laws of Motion”. Through the improved ORB algorithm, this paper effectively combines the BRIEF and ORB image feature and matching algorithms to optimize capturing and matching image features. Two classes of animation majors in a school were selected for experiments in the study, and the effects of the two teaching modes were compared through half-term tests, pre- and post-test question analyses, and questionnaire surveys. The results show that after the teaching assisted by VR animation technology, students' acceptance and emotional attitudes are significantly improved, and the students in the experimental class better mastered the six motion methods in the animation motion course and completed the animation design tasks with high quality. In the animation modeling course, the proportion of low-quality works in the experimental class i.....

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The metaverse is an envisioned realm offering immersive digital spaces, bolstering highly interactive environments within educational contexts. This digital dimension amplifies synchronous communication, uniting a vast number of users as they share their unique experiences. This research aims to scrutinize the perceptions of elementary students towards the metaverse system (MS). Our proposed model underwent validation through the Partial Least Squares Structural Equation Modelling (PLS-SEM) technique. Data, sourced from 287 students of Dubai National School, revealed that the primary predictor of students' intent to engage with the MS is personal innovativeness. This is followed closely by perceived usefulness and then perceived ease of use. The findings of this research provide deeper insights into the driving factors behind the adoption of MS among young learners. © 2024, Semarak Ilmu Publishing. All rights reserved...

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Text analytics can be applied in education to gain insights into student learning, teacher performance, and educational trends by analysing various forms of text-based data such as student essays, social media posts, and educational resources. While the need for teacher preparation and training is identified, specific solutions or effective strategies for equipping educators with the skills and knowledge to integrate graphic visualizations into their teaching practices might be underexplored. This Scientometrics study used PRISMA approach (Preferred Reporting Items for Systematic Review and Meta-Analysis) Using R tool. Scopus databases that were relevant to the research topic, and its standardized procedures ensured comprehensiveness and replicability. The study found 85 articles using the PRISMA approach from the Scopus database, with 98.82% being articles and 1.18% from conference proceedings. The number of articles published increased in 2022, with 33 articles, compared to 22 articl.....

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Artificial intelligence is widely developed in the health sector, and machine learning has been increasingly used in healthcare to make predictions, assign diagnoses and as a method of prioritizing actions. machine learning methods have become a feature of several tools in the field of obstetrics and child care. Is to identify the applicability and performance of machine learning methods used to identify preterm labor during pregnancy the main precision metric used is the AUC. the machine learning method with the best results was the prediction of prematurity the SVM classifier algorithm method is the best method for predicting the incidence of premature birth with an accuracy level of 0.997, recall of 0.995, and specificity of 1.0, for identifying a diagnosis of premature birth which is quite good. good. accurately. These results are similar to the results of Rawashdeh et al.'s research on a data mining-based intelligence system using the Naïve Bayes, Decision Tree, K-NN, RF, And NN .....

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