This study aims at exploring the problem of the readiness and competence of new teachers to teach in primary schools. This study specifically focuses on identifying the readiness of new teachers to conduct teaching professionally, and analyzing their competence in conducting teaching. This study employs a mixed-method research design with data collected from two different approaches: a qualitative approach by conducting interviews and observation, and a quantitative approach by conducting a survey. The data were collected from lecturers, graduate teachers working as teachers, graduate teachers working not as teachers, and users of graduate teachers. The results of data collection and analysis were made into several themes. The results showed that the majority of graduates were ready to join the workforce as professional teachers with the risk that they had to accept the lack of welfare and legitimacy as unprofessional teachers because they had to attend further professional education programs. The education provided by the lecturers during their study in their institution in the aspects of knowledge and skills in the field of study and pedagogy became the foundation for new teachers in starting their careers as professional teachers in schools. A good educational process had produced teachers who have competencies with good categories in various aspects.

The purpose of the research was to identify whether the English language e-classes that are automated and delivered through the Smart Sender platform influence the students’ attendance and procrastination rates, their motivation, time management skills, cognitive processing speed, and satisfaction. The study used qualitative and quantitative methods to monitor students’ attendance and procrastination rates, motivation and engagement, time management skills, thinking speed, and satisfaction. The questionnaire on learning motivation, engagement, and competence, the time management skills test, the mental speed test, and the course satisfaction questionnaire were used to collect data. The focus group discussion questionnaire was used to obtain verbal feedback for the participants. The Smart Sender platform proved effective as an instructional tool for teaching the English Language to students majoring in Philology, International Business, and Law. The automated delivery of the English language e-classes was effective in addressing the issues of dropouts and procrastination in distance learning through automation of the lesson delivery based on the ‘push’ factor. It increased students’ motivation, improves time management skills, and satisfaction. The quantitative findings showed that the students experienced a positive change in attendance, motivation and learning engagement, time management skills, and thinking speed due to the intervention. The students perceived the automated delivery-based approach to language teaching positively. They reported that the delivery approach content met the participants’ expectations and needs. Focus group discussion revealed that the intervention changed their learning behaviour and strategies which were considered the improvements of the quality learning outcomes.

Problem-solving is considered one of the thinking skills that must be possessed in 21^st-century education because problem-solving skills are required to solve all problems that arise. The problem-solving stages that can be used are Polya's four steps, namely, understanding the problem, devising a plan, carrying out the plan, and looking back. Problem-solving skills are essential for solving word problems. Word problems based on arithmetic operations are divided into three types: one-step, two-step, and multistep. This qualitative research aimed to see problem-solving skills viewed from the type of word questions and elementary school students’ third, fourth, and fifth grades. A purposive sampling technique with 22 third-grade students, 28 fourth-grade students, and 21 fifth-grade students was used. The data were collected using documentation, testing, and interview methods. The findings of the study showed that fourth-grade students’ problem-solving skills are better than those of third-grade students, and the problem-solving skills of fifth-grade students are better than those of fourth-grade students. The percentage of Polya's steps always decreases because not all students master problem-solving. Based on the types of questions, the percentage of the one-step word problem is better than that of the two-step while the percentage of the two-step word problems is higher than that of the multistep.

The research delved into the assessment of integrating Learning Management System as an aid in teaching. Data were collected from 26 students at Rizal Technological University-College of Education, Philippines, through pretest-posttest quasi-experimental and normative survey design of research. Data were statistically tested using the frequency, percentage, mean, standard deviation, t-test for dependent and independent samples, and paired t-test. Results of the research indicate that the respondents have optimistic attitudes towards the integration of learning management system in teaching. The respondents performed poorly in the pretest examination but performed very satisfactorily in the posttest examination. Furthermore, the research found out that there is no significant difference between the performances of the experimental group and control group in pretest and posttest, moreover, there is a significant difference between the pretest and posttest scores of the experimental group and the pretest and posttest scores of the control group.

The purpose of the present study is to examine the contribution of professional learning community of pedagogical instructors, training teachers, and teaching students in clinical model for teacher education to their professional development. The prior is carried out through examining a variety of categories: namely, collaborative learning, personal responsibility, collective responsibility, reflective pedagogical discourse and action research, knowledge development and learning processes. Thirty-three members of the learning community constituted the study community. The research tool is a multiple-choice questionnaire that was developed for the requirements of the research and personal feedback on open-ended questions. The quantitative data collected by the questionnaire indicated that the learning community of the clinical model for teacher education contributed greatly to the professional development of all participants regardless of field of knowledge, role in the training process, and the curricular activities offered by colleges and schools. The findings revealed a negative relationship between the field of teacher education among the participants on the one hand, and professional development on the other hand.

Learning activities are conducted to help students achieve optimal academic achievement. This research aims to optimize student academic achievement through a learning process that integrates comprehensive formative assessments, including formative tests, self-assessment, peer assessment, and the initiator of creating summaries or concept maps that are given to students in a structured manner at the end of every lesson. The research method used was a quasi-experimental method with a 2x2 factorial design. Students enrolled in the biology education program of the basic physics course for the 1st semester of the 2019 academic year participated in this study. The participants were 66 undergraduate students divided into two classes. Thirty-four students in the experimental group were in class A, while 32 students in the control group were in class B. Data were collected using a learning outcome test instrument to measure academic achievement, which was tested at the end of the semester. Data were analyzed using a two-way ANOVA. This study concluded that a learning process that includes comprehensive formative assessment significantly affects students' academic achievement. These findings support the theory that formative assessment provides feedback, correction, and improvement in student learning.

This study aimed to explore the implementation and impact of the Flipped Learning Model (FLM) and STEM Approach in elementary education. The advancement of technology and the Covid-19 pandemic has increased the importance of e-learning, including in elementary schools. The literature review analyzed 193 academic works published in the past six years using NVivo, Mendeley, and VOSviewer software. The validity of the data was verified through the analysis of five online databases. The results showed that STEM research has been well-developed with innovative approaches that improve learning outcomes, while FLM research in elementary schools is limited. The study suggested that combining FLM with STEM Approach (FLM-SA) can optimize learning in the technological era. By integrating FLM-SA, students can engage in active learning experiences in class and acquire fundamental knowledge outside of class, offering a solution to e-learning challenges. The study emphasized the strong connection between FLM and STEM Approach and how they can support each other to enhance student learning.

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.

Psychosocial and educational intervention approaches employ diverse treatment frameworks, most of which involve delivering some form of feedback to participants about their behavior. General conceptions of feedback are well-known to underlie mainstream therapeutic and educational approaches. Recently emerging ‘smart’ approaches also rely on feedback principles. However, little scholarship is available to stitch together evolving strands of feedback principles and no literature characterizes explicitly the diverse landscape of feedback practices employed in education or intervention science. This paper reviews intrinsic conceptions of feedback along with diverse cases of its use in intervention and education. Based on our consideration, we present a typology of feedback modalities that we hope will enrich the efforts of interventionists and educators to design treatment and educational frameworks incorporating feedback.

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.

This qualitative study investigates the strategies employed by Vietnamese tertiary-level English as a Foreign Language (EFL) teachers to promote learner autonomy (LA) and enhance cultural awareness. This research provides a deeper understanding of EFL teaching practices in this setting, conducted in the context of Vietnam’s evolving educational landscape, where English proficiency and cultural competence are increasingly prioritized. The study utilized semi-structured interviews with nine EFL teachers from two different Vietnamese tertiary institutions, representing various career stages: novice, mid-career, and near-end career. Thematic analysis was employed to analyze the data, revealing a range of strategies encompassing collaborative learning, technology integration, personalized feedback, real-life scenarios and role-play, reflective learning practices, local culture incorporation, contextualized language instruction, critical thinking, and cultural analysis, student-centered environments, interdisciplinary approaches, language skills for intercultural communication, and authentic material use. Findings highlight the multifaceted nature of language teaching, emphasizing not just linguistic competence but also cultural understanding and LA. These strategies are crucial in a globalized world where intercultural communication is a key skill. The study suggests the need for continuous professional development and policy support for diverse and holistic teaching practices. It offers practical insights for EFL educators, particularly in similar socio-cultural contexts, on integrating various strategies to enhance language skills and cultural awareness.

One of the ways to enhance and improve the quality of learning delivery is through the use of technology, particularly the Internet, which facilitates faster and easier access to information. This research aims to explore the degree to which factors such as digital literacy, metacognitive awareness, meaningful learning, habits of using smartphones, and personal learning competence are related to one another. Both the relationship between metacognitive awareness and personal learning competence, as well as the relationship between smartphone habits and personal learning competence, are moderated by a moderating variable known as the fear of missing out. Fear of missing out is a moderating variable. Structural equation modeling, specifically partial least squares, was employed to analyze data from 597 engineering students. SmartPLS version 4 was the tool used for this analysis. The study found that the moderating variable, fear of missing out, significantly impacts metacognitive awareness, learning personal competence, and smartphone habits, making it a crucial factor to investigate. This result is significant because it is a variable that influences the learning that students go through for their education and because it is an extremely important thing to investigate.

The integration of AI tools in education is reshaping how students view and interact with their learning experiences. As AI usage continues to grow, it becomes increasingly important to understand how students' perceptions of AI technology impact their academic performance and learning behaviours. To investigate these effects, we conducted a correlational study with a sample of 44 students to examine the relationship between students' perceptions of ChatGPT’s utility—focusing on usage frequency, perceived usefulness, accuracy, reliability, and time efficiency—and key academic outcomes, including content mastery, confidence in knowledge, and grade improvement. Additionally, we explored how these perceptions influence student behaviours, such as reliance on ChatGPT, procrastination tendencies, and the potential risk of plagiarism. The canonical correlation analysis revealed a statistically significant relationship between students' perceptions of ChatGPT's utility and their academic outcomes. Students who viewed ChatGPT as reliable and efficient tended to report higher grades, improved understanding of the material, and greater confidence in their knowledge. Furthermore, the bivariate correlation analysis revealed a significant relationship between dependency on ChatGPT and procrastination (r = 0.546, p < .001), indicating that a higher reliance on AI tools may contribute to increased procrastination. No statistically significant association was identified between ChatGPT dependency and the risk of plagiarism. Future research should prioritize the development of strategies that promote the effective use of AI while minimizing the risk of over-reliance. Such efforts can enhance academic integrity and support independent learning. Educators play a critical role in this process by guiding students to balance the advantages of AI with the cultivation of critical thinking skills and adherence to ethical academic practices.

The digital age has sparked interest among educators in utilizing information technology, especially artificial intelligence (AI) chatbots. Due to the constant technological involvement, students must also acquire solid digital skills, especially AI proficiency, for learning and everyday life. However, there are few studies on models applying AI in teaching to develop mathematical abilities for high school students. Therefore, this paper proposes a theoretical framework for incorporating AI chatbots into education, boosting students’ mathematical problem-solving competence. Based on student data analysis, this framework will cover teaching, assessment, feedback, and dynamic learning activity adjustment. The paper then explains the operations of AI chatbots to provide personalized feedback. This process emphasizes the importance of error handling and information security, ensuring safety and efficiency in the learning process. This theoretical model supports the integration of AI chatbots in personalized teaching, specifically for improving mathematical skills.

Research fronts are dynamic, knowledge-driven clusters of scholarly activity that emerge in response to pressing problems and/or groundbreaking discoveries. Clarivate Analytics provided a valuable tool based on Citation Productivity and Trajectory (CPT) indicator, which successfully identified particularly hot research fronts on a global scale. To enhance the accuracy and comprehensiveness of identifying both active and emerging research trends, this study develops an extended Clarivate formulation incorporating a novel Impact Factor (IF) metric. The refined approach incorporates growth rates, publication productivity, and the average publication gap between published and citing publications. This method is applied to exploring key research fronts in the digital education ecosystem using bibliometric data from the Scopus database in the period of 2019-2023. The results reveal that artificial intelligence and online learning are the most prominent and influential fields, with virtual reality, blockchain, hybrid learning, and digital literacy representing fast-growing areas. By analyzing both quantitative and qualitative aspects, this work informs key stakeholders about the evolving priorities and trends in the digital educational landscape.