Modern technology is necessary and important for improving the quality of education. While machine learning algorithms to support students remain limited. Thus, it is necessary to inspire educational scholars and educational technologists. This research therefore has three main targets: to educate the holistic context of rural education management, to study the relationship of continuing education at the upper secondary level, and to construct an appropriate education program prediction model for high school students in a rural school. The data for research is the academic achievement data of 1,859 students from Manchasuksa School at Mancha Khiri District, Khon Kaen Province, Thailand, during the academic year 2015-2020. Research tools are separated into 2 sections. The first section is a basic statistical analysis step, it composes of frequency analysis, percentage analysis, mean analysis, and standard deviation analysis. Another section is the data mining analysis phase, which consists of discretization technique, XGBoost classification technique (Decision Tree, Gradient Boosted Trees, and Random Forest), confusion matrix performance analysis, and cross-validation performance analysis. At the end, the research results found that the reasonable distribution level of student achievement consisted of four clusters classified by academic achievement. All four clusters were modeled on predicting academic achievement for the next generation of students. In addition, there are four success models in this research. For future research, the researcher aims to develop an application to facilitate instruction for learners by integrating prediction models into the mobile application to promote the utilization of modern technology.

This study aimed to explore online and distance learning (ODL) issues related to higher education during the coronavirus disease (COVID-19) in Nepal. We applied an online survey design with a five-point Likert scale. We surveyed 71 (57 male and 14 female) postgraduate students in science education at a public higher education institution in Kathmandu, Nepal. A Principal Component Analysis identified four major constructs as the components of ODL issues. They are scarcity, efficiency, access, and inconvenience. The results of the Independent Samples Test (t-test and ANOVA) showed that participants' views about scarcity were significantly different across their gender (male and female) and device use (mobile, laptop, and desktop). They were not significantly different in their views about efficiency, access, and inconvenience across gender, device use, hometown, age group, ethnicity, and school type at .05 level of significance.

Learning by teaching is a technique where students teach an actual class to facilitate active learning. This paper reports ongoing research involving undergraduate students at an established university in Indonesia. The objective of this quantitative study was to find out the effect of this teaching technique in improving students’ 21st century skills. The sample was selected using a cluster sampling technique, where 25 students who were English as a Foreign Language pre-service teachers were assigned to an experimental group, and the other 23 students were treated as a control group. The students in the experimental group were asked to conduct a workshop in groups to students from the same department at a different university. Each group selected one of the topics in their course syllabus. A pre-test measuring the students’ soft skills was conducted before the course started and after it finished. The results show that soft skills, which include accountability, communication, innovation, problem-solving, teamwork, professional working, and networking skills, improved significantly among students in the experimental group, but the improvement was not evident in the control group. Therefore, learning by teaching should be embraced as an alternative teaching technique when soft-skill development becomes a target of instruction.

Mathematics teachers’ instructional strategies lack in-depth knowledge of algebraic systems and hold misconceptions about solving two algebraic equations simultaneously. This study aimed to gain an in-depth analysis of teachers’ knowledge and perceptions about the promotion of conceptual learning and effective teaching of algebraic equations. The main question was, ‘How do junior secondary school mathematics teachers manifest their pedagogical practices when teaching algebraic equations? This article reports on a qualitative, underpinned by the knowledge quartet model study, that sought to explore how junior secondary school teachers’ pedagogical practices manifested in the teaching of algebraic equations. Data were collected from observations, semi-structured interviews, and document analysis of two mathematics teachers purposely selected from two schools. The collected data were analysed using a statistical analysis software called Atlas-ti. (Version 8) and triangulated through thematic analysis. The study revealed that teachers’ choices of representations, examples, and tasks used did not expose learners to hands-on activities that promote understanding and making connections from the underlying algebraic equation concepts. The study proposed Penta-Knowledge Collaborative Planning and Reflective Teaching and Learning Models to enable teachers to collaborate with their peers from the planning stage to lesson delivery reflecting on good practices and strategies for teaching algebraic equations.

The primary objective of this study is to require the experts’ unanimous agreement on the e-learning antecedents and usage behavior towards e-learning performance. This study used the Fuzzy Delphi Method (FDM) to gather answers and feedback using a 7-point Likert scale. The survey (items) was reviewed and approved by eight panel members or experts. It was analyzed using Fuzzy Delphi Logic (FUDELO 1.0) software. The data were evaluated using triangular fuzzy numbering and the position (ranking) of each variable was established through defuzzification. The findings revealed that all of the items received high levels of expert agreement, significantly greater α-cut defuzzification values >.5, the overall value of the threshold (d) is less than .2 and had to comply with the overall percentage of percent consensus, which must be greater than 75%. All 45 recommended items were retained adequately and acceptable for a large-scale survey in this study. Finally, each item was prioritized (ranked) based on the defuzzification value, and then some additional items were added, as recommended by experts.

The peer tutoring approach is a student-cantered teaching method in which students learn in pairs with teacher supervision. The study discussed in this paper is a systematic literature review related to the effectiveness of peer tutoring approaches which has been published within the last 5 years. A complete text analysis was conducted using 20 research papers stating the impact of the peer mentoring approach for this writing. Among the things obtained from previous studies are the variety of ways to implement peer tutoring approach, the impact on 3 aspects in students which are mathematical achievement, social skills and cognitive skills and the teaching theories used. The findings of the study indicate that most past studies used quantitative research methods with the concept of age peer approach. Then, constructivism theory was the most frequently applied with a sample of high school students. In conclusion, this systematic literature review shows that the peer tutoring approach in mathematics education has many benefits in various aspects and needs to be extended to improve the quality of education.

This meta-analysis study investigates the effect of computer-based tests on motivation. The random effect model is the basis for calculating the summary effect, and it is found that the 30 articles obtained through the PRISMA method, which consist of four parts, namely identification, screening, eligibility, and included, can be generalized. Data analysis was performed using R studio and OpenMEE. Based on the research results, the p-value <.05 was obtained, so it was concluded that using a computer-based test significantly affected motivation. In the moderator analysis, it was found that computer-based tests were most effective for intrinsic motivation for the motivation variable, university students for the participants variable, and the country of Iran for the region variable. Evaluation of publication bias using the funnel plot and regression method shows no publication bias, proving that the 30 articles analyzed represent all existing studies on computer-based tests.

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.

Digital technologies in all forms have become ubiquitous in our media-rich, modern information society, but the connection between their use and information literacy is not always clear. This paper examines the impact of daily use of digital technologies on the reading and information literacy skills of 15-year-old students in Slovenia, based on data from the Programme for International Student Assessment (PISA) 2018 study. The study examines PISA 2018 variables related to Information and Communication Technologies (ICT), as well as a reading task involving the use of ICT. The sample consists of 2612 Slovenian students with a gender distribution of 50.8% girls and 49.2% boys. The study explores students' experiences, enjoyment, self-efficacy, autonomy, and independence in using ICT and learning about its use and identifies two groups of students: one group that is curious and another that is cautious. The results of confirmatory factor analysis (CFA) and structural equation modelling (SEM) show that the constructs of enjoyment, self-efficacy, learning, autonomy, and independence are highly/strongly correlated but have a low/insignificant impact on information literacy skills.

This study aimed to investigate the relationship between teacher professional development, quality of lecture design, student engagement, teacher technical skills, pedagogical content knowledge and teacher satisfaction in using Artificial Intelligence (AI)-Powered Facilitator for designing lectures. The study used a non-random sample technique, and 208 participants answered a survey via Google Form after one semester, using a 5-point Likert scale to rate their responses. The structural equation model was used to analyze the data, and six factors were included in the study. The study confirmed hypotheses that teacher professional development, quality of lecture design, student engagement, and pedagogical content knowledge have a positive effect on teacher satisfaction. However, the study also revealed that teacher technical skills have a negative effect on teacher satisfaction, and pedagogical content knowledge has no significant effect. The proposed conceptual model explained 55.7% of the variance in teacher satisfaction Theoretical and practical implications were also discussed. These findings provide insights into the factors that contribute to teacher satisfaction in utilizing AI-Powered Facilitator for designing lectures and could inform the development of effective teacher training programs.

Students in mathematics classes do not understand the importance of sociomathematical norms in learning mathematics. This causes sociomathematical norms not to be teachers' focus when learning mathematics. Besides, there is no standardized instrument for assessing this norm, so developing this instrument is necessary to measure socio-mathematical norms in learning mathematics. This study aims to create and verify the psychometric validity of the sociomathematical norm scale. This research used a survey method with 505 senior high school students from Jakarta and West Java as respondents. The results showed that 25 items had convergent validity, with a loading factor value of > 0.700, meaning they could be declared valid. Concurrent validity indicates that each sociomathematical norms indicator is valid as a whole. Discriminant validity shows that the average variance extracted value on the diagonal is higher than the other values, so each item is declared valid. It was concluded that each item of the sociomathematical norms instrument has accuracy in its measurement function. The reliability test shows that each sociomathematical norms item is declared reliable. The reliability value of the sociomathematical norm item is .99, and the person's reliability is .86. Thus, the instruments developed can measure sociomathematical norms in learning mathematics.

The central focus of this study is exploring the potential of Artificial Intelligence (AI) Chatbots in enhancing digital dialogue for students. The study investigates the key attributes of Chatbots that can contribute to the feasibility of facilitating digital dialogue to improve students' communication skills through discussions and dialogues. The study employed a descriptive method using a questionnaire to gather the perspectives of 35 educational experts on the use of AI Chatbots in digital dialogue skills. This study revealed that using AI Chatbots plays a crucial role in enhancing digital dialogue skills and can be effectively integrated into instructional practices to facilitate meaningful dialogue among students. Finally, the study recommends that educational technology specialists leverage new technologies, such as Al Chatbots to help improve student performance and facilitate digital dialogue in education.

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.