Changes and challenges in the highly dynamic world of education require postgraduate students to manage their learning well and create something from their creative thinking according to the needs of the field. One of them is the activity of students in developing integrated natural science teaching materials is very necessary because learning at the primary level still uses integrated or thematic learning. Furthermore, students also need to be encouraged to be adaptive to these challenges by empowering their independence in learning. The ability to manage learning and creativity to create something new is highly prioritized for college graduates to contribute generously to their environment. This study aims to describe the empowerment of self-regulated learning and student creativity in developing natural science teaching materials in collaboration through community-based project learning. This study used a quasi-experimental design with a single-subject design type. The instruments used to retrieve data are creativity assessment rubrics and self-regulated learning questionnaires. The conclusion is that students are intrinsically and extrinsically motivated to fulfill the given tasks. Learning is essential for increasing competence, and learning strategies have been adjusted to the material's complexity or the difficulty level of the studied content. The aspect of student creativity in developing Integrated Science teaching materials shows the existence of change from stage one to the next and good categories.

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.

Situational interest is an important factor that has a great influence on learning success in both in-school and out-of-school learning situations. Although there has been extensive research on interest in its diverse forms for decades, an evaluated measurement instrument for situational interest that covers the three theoretically defined components of interest (emotional, cognitive, value-related) is still missing. Therefore, in this study, based on person-object theory of interest, a short scale was developed that can be used in a variety of learning programs independent of content or methods. In study 1, eight suitable items were selected and their structure was examined using exploratory methods. In study 2, the results of study 1 were verified using confirmatory factor analyses. Study 3 shows an example of a practical application of the newly developed scale in two different learning settings. The findings provide evidence that the scale developed here is a practical instrument to measure situational interest taking into account all its components. On the one hand, the scale can help teachers evaluate their educational programs; on the other hand, it can be used by researchers to empirically investigate the construct of interest. Thus, the scale makes an important contribution to research and practice.

School attendance problems are of great research interest, which is reflected in the increase of scientific publications. This increase hinders the adequate follow-up and updating of the scientific community on the subject. The aim of the present bibliometric study lies in the review of the scientific literature published on school attendance problems during 2014-2021. A bibliographic search and analysis of scientific articles was performed, obtaining a definitive sample of 700 documents. Results were extracted and analyzed for the following indicators: temporal productivity, productivity by authors, co-authorship index, productivity by journals, use of topics, research areas addressed and types of samples used. The number of publications indicates a progressive increase of interest on the subject, which has not corresponded to the creation of a specific journal on the subject. There is also evidence of the need for consensus on the topics to be used; the preference for knowing the factors associated with school attendance problems over other areas of research; and the generalized use of community samples as opposed to more specific ones. In conclusion, the characteristics researched on school attendance problems are presented; knowledge that will facilitate the establishment of intervention processes applicable to different contexts and realities.

It is known that the COVID-19 pandemic led to learning losses among students both domestically and internationally. Therefore, situational and casual factors were examined to discover and understand them so that learning loss could be reduced or recovered from. This research aimed to: (a) study learning loss situation; and (b) develop and examine the causal model of learning loss among lower secondary school students affected by the pandemic. The sample included 650 Grade 7-9 students selected by multi-stage random sampling. The data was collected using a self-developing questionnaire as a research instrument. The data was analyzed using descriptive statistics, independent samples t-test, ANOVA, and structural equation modeling (SEM) through the LISREL program. The findings were: (a) Lower secondary school students had an average academic achievement learning loss at the moderate level with the highest mean of learning loss in mathematics (M=3.012, SD=1.074), and an average learning characteristics learning loss at the medium level (M=2.824, SD=0.842). Several situational factors had a different effect depending on the school size with a statistical significance of .05.; and (b) the causal model showed the learning loss of grade 7-9 students was consistent with the empirical data (χ2=46.885, df=34, p= .069, GFI=0.991, AGFI=0.964, CFI=0.999, RMSEA=0.024, SRMR=0.014).

This research aimed to explore the influence of a robotic program using the robot kit "RoboBuilder RQ+110" on students' attitudes toward effective communication. The study used a quantitative research design and involved 475 grade 4 (10 years old) students from Malaysia's Selangor and Malacca states. A quasi-experimental research (pre-test & post-test) approach with control and experimental groups was adopted, and the data were analyzed with inferential statistical test and repeated measures analysis of variance (ANOVA) using SPSS 25 software at 0.05 significance level. Questionnaires were administered to collect data from the experimental and control groups. The results showed statistically significant changes (α ≤ .05) in attitudes toward effective communication for the experimental group that received a robotics program compared with the control group. The study results suggest that innovative technological tools or programs such as robotics programs are recommended as innovative science, technology, engineering, and mathematics (STEM) program rooted in constructivism to improve students' attitudes toward effective communication.

Understanding graphs in the dynamics of market (DM) is a challenge to learners; its teaching demands a specific kind of teacher’s knowledge. This study aims to examine the topic-specific pedagogical content knowledge (TSPCK) of experienced economics teachers in teaching graphs in DM to enhance learners’ understanding of the topic. It reports using a qualitative approach underpinned by the TSPCK framework for teaching specific topics developed by Mavhunga. Data were collected through classroom observations and analyzed thematically using a case study of two economics teachers. The study revealed that adopting a step-by-step approach and the use of worked graphical examples promote an understanding of graphs in DM. It also established that active learning is preferable to the predominant chalk-and-talk (lecture) method of teaching graphs in DM. The study proposed a Dynamics of Market Graphical Framework (DMG-Framework) to enable teachers, particularly pre-service teachers in lesson delivery, to enhance learners’ understanding of graphs in DM. The result of this study will broaden the international view in the teaching of graphs in DM.

This study aims to explore the impact of outdoor education on senior elementary school students' perceptions of scientific literacy and learning motivation. 42 senior elementary school students (25 males, 17 females; average age = 11.6) were enrolled and divided into experimental (N = 21) and control (N = 21) groups. Participants were taught the same content about science for four weeks. The control group adopted traditional indoor teaching, whereas the experimental group adopted outdoor education. Before and after the course, each student completed the 23 items of scientific literacy and the 6 items of learning motivation scale. The results show that the experimental group had significantly higher perceptions of scientific literacy and learning motivation. The outdoor education teaching method has positive effects on the higher levels of awareness and creative development of students. These findings imply that outdoor education has a positive effect on improving students' perceptions of scientific literacy and learning motivation.

The primary objective of this study was to determine how students and teachers in primary schools view the classroom climate and its dimensions: (a) peer relationships and (b) student-teacher relationships. Additionally, the study aimed to explore the role of students' age (11-12 years old - 7th grade students vs. 14-15 years old - 9th grade primary school students) and gender on their perceptions of the school climate. Classroom climate was measured with the "Classroom Climate Questionnaire", which was completed by a total of 1,531 students (792; 51.6% female) and 348 teachers (296; 84.6% female). The findings of the study indicated that both students and teachers generally perceived the classroom climate as being relatively neutral to positive. However, teachers tended to report more positive classroom relationships compared to students. Furthermore, the study found no significant gender-based differences in how students perceived the classroom climate, peer relationships, and student-teacher interactions. However, differences were identified based on the age or grade level of the students. The results were discussed in the context of the students’ psychological development characteristics and the aspects of socio-emotional learning within school environments, also considering educational policies for achieving greater school quality.

Students’ mastery goal orientation tends to decline over the course of compulsory school, especially after the transition to lower secondary school. According to stage-environment fit theory, secondary school is less accommodating to students' needs, interests, and abilities than primary school. In consequence, the perceived person-environment fit declines as well. It is assumed that a strong sense of classroom community in primary school can counteract a potential decline in both of these important individual aspects. Using data from the Swiss longitudinal research project WiSel (“Wirkungen der Selektion”; “Effects of Tracking”), we conducted a latent growth curve model (LGCM) to examine the correlation between the development of students' mastery goal orientation and the development of their person-environment fit during the transition from primary school to lower secondary school. Perceived classroom community was assumed to benefit from these developments. The results show that both mastery goal orientation and person-environment fit decrease during the transition to lower secondary school. A strong sense of classroom community in fifth grade leads to a smaller decline in both constructs. Implications for educational practice are discussed.

The wide use of the Internet of Things (IoT) in all spheres of life has led to a surge of cyberbullying among learners worldwide. That is why it cannot be denied that underlying factors, manifestations, consequences, and preventive measures of cyberbullying improve the welfare and overall mental development of students. This systematic literature review examines the causes, effects, and preventive measures of cyberbullying based on empirical studies conducted on learners in various situations. The review will focus on existing material published between 2015 and April 2024. For the inclusion and exclusion of literature, the Scopus online database was employed, along with the guidelines of the PRISMA model. Of 1004 studies, 51 were closely reviewed to determine the responses to the objectives of this study. NVIVO-12 was used for both thematic and content analysis in this study. The results show that there are 29 causes, 12 forms, 31 effects, and 41 different preventives for cyberbullying. The results of this study will not only enhance the comprehension of various concerns for parents, guardians, policymakers, educators, and governments but also provide valuable insights to researchers for addressing this issue.

The education of gifted students is often characterized by high expectations, ambitious goals, and significant effort invested in learning. Their experiences of success and failure are shaped by a variety of factors, including personal, family, school, cultural, and social influences. This article examines how gifted students perceive and experience their own successes and failures, as well as how these experiences are perceived and responded to by their peers. Using qualitative methods, the study involved semi-structured interviews with thirty gifted students from seventh to ninth grades across ten elementary schools in Slovenia. The findings indicate that gifted students experience a range of emotions in response to success, from satisfaction to anxiety, while their reactions to failure often involve frustration and self-criticism. Peer responses to their success and failure vary significantly, ranging from supportive encouragement to jealousy and social exclusion. These findings highlight the complex interpersonal dynamics at play within school environments. Understanding and addressing these dynamics is crucial for creating inclusive, supportive, and stimulating learning environments that nurture both the academic and social-emotional well-being of gifted students.

This study addresses global concerns surrounding elementary students' science performance following the COVID-19, as a result of international tests such as Trends in International Mathematics and Science Study (TIMSS) highlight the ongoing challenges that urge the exploration of innovative educational approaches to improve science learning. This research employed gamification-assisted instruction and explored its impact on enhancing the understanding of science concepts and attitudes toward science class among fourth graders. The study adopted a quasi-experimental design and included an experimental group (ExG) that was taught using a gamification strategy and a control group (CoG) that was taught using a traditional method with a sample of 38 female elementary students from a public school in Jordan. Data were gathered using valid and reliable tools: the developed scientific concepts test and the Attitude Towards Science class measures. The ANCOVA analysis revealed that gamification significantly improves the acquisition of scientific concepts (η2=.208) and boosts a positive attitude toward science classes among elementary students (η2=.626). These findings encourage decision-makers to incorporate gamification into science teaching practices and methods.

This article provides a comprehensive guide to conducting and documenting systematic reviews (SRs) in educational research. While SRs are increasingly recognized for their value in synthesizing and evaluating literature on specific research questions or topics, there remains a notable scarcity of research-based papers that guide their development within the field of education. Systematic reviews, distinguished from traditional literature reviews by their standardized processes—including systematic searching, selection, and critical appraisal of relevant studies—offer a more accurate and comprehensive understanding of the research landscape by integrating findings from multiple sources. This paper underscores the importance of adhering to established methodologies and guidelines to ensure the quality and reliability of SRs. Essential elements discussed include defining research questions, developing search strategies, applying inclusion and exclusion criteria, and synthesizing results. The paper also highlights the role of frameworks such as the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) in enhancing transparency and methodological rigor. By following this structured approach, researchers can produce systematic reviews that provide valuable insights into educational practices and policies, thereby supporting evidence-based decision-making and advancing the field of education.

This umbrella review aimed to synthesize variables that explain dropout among students in preschool, primary, secondary, and high school education. The study focused on peer-reviewed articles indexed in SCOPUS, Web of Science, and ERIC, identifying five systematic reviews that provided comprehensive insights. Key findings revealed individual factors, such as insufficient parental support, emotional and behavioral challenges, and substance use, play significant roles in influencing student dropout. Socioeconomic factors, including poverty, financial constraints, and social inequalities, were also identified as critical contributors. Additionally, institutional elements such as inadequate school infrastructure, insufficient teacher training, and a lack of culturally relevant resources emerged as barriers to student retention. This review highlights research gaps in political-legislative, sociocultural, and family determinants, longitudinal analyses, dropout interventions’ long-term effectiveness, and marginalized populations’ representation, limiting a comprehensive understanding of student dropout and effective policy development. Recommendations include targeted policies and interventions that foster inclusive and supportive educational environments, reduce inequities, and improve access to resources to minimize dropout rates among students in preschool, primary, secondary, and high school education.

This study aims to evaluate the effectiveness of cooperative learning models in improving critical reading skills. This study uses a meta-analysis study method by analyzing 28 articles extracted from the databases of Scopus, Google Scholar, EBSCO, EmeraldInsight, Science & Direct, SpringerLink, Taylor & Francis, and ProQuest. The meta-analysis allows researchers to combine the results of previous research, providing a more comprehensive picture of how effective a particular approach is in teaching critical reading. The research findings show that cooperative learning models significantly improve essential skills of reading more effectively than traditional ones. This is shown by the effect sizes based on the fixed model, showing the overall standard difference in the mean is 0.784 (95% CI, 0.689 to 0.880) with p-values = 0.00 (<0.05). Using a cooperative learning model, The measure showed positive effect sizes on critical reading learning. Based on these results, it can be concluded that the cooperative learning model effectively improves essential reading skills. However, several factors, such as the quality of the facilitators and the teaching methods, influence the results. The implications of this study show the need for a broader application of cooperative learning models to improve critical reading skills in schools and other educational institutions, with adjustments to the needs and characteristics of students.

Artificial intelligence (AI) has revolutionized higher education. The rapid adoption of artificial intelligence in education (AIED) tools has significantly transformed educational management, specifically in self-directed learning (SDL). This study examines the factors influencing Indonesian higher education students' intention to adopt AIED tools for self-directed learning using a combination of the Theory of Planned Behavior (TPB) with additional theories. A total of 322 university students from diverse academic backgrounds participated in the structured survey. This study utilized machine learning it was Artificial Neural Networks (ANN) to analyze nine factors, including attitude (AT), subjective norms (SN), perceived behavioral control (PBC), optimism (OP), user innovativeness (UI), perceived usefulness (PUF), facilitating conditions (FC), perception towards ai (PTA), and intention (IT) with a total of 41 items in the questionnaire. The model demonstrated high predictive accuracy, with SN emerging as the most significant factor to IT, followed by AT, PBC, PUF, FC, OP, and PTA. User innovativeness was the least influential factor due to the lowest accuracy. This study provides actionable insights for educators, policymakers, and technology developers by highlighting the critical roles of social influence, supportive infrastructure, and student beliefs in shaping AIED adoption for self-directed learning (SDL). This research not only fills an important gap in the literature but also offers a roadmap for designing inclusive, student-centered AI learning environments that empower learners and support the future of SDL in digital education.

Mindfulness, recognized as a protective factor against learning burnout in higher education, has garnered considerable attention, yet its underlying mechanisms remain underexplored. This study examined the relationship between mindfulness, regulatory emotional self-efficacy, and learning burnout. Data from 461 Chinese university students were collected using a correlational design and cluster sampling method, employing the Five Facet Mindfulness Questionnaire, University Student Learning Burnout Scale, and Regulatory Emotional Self-Efficacy Scale. Hypotheses were tested using partial least squares structural equation modeling. Results showed that Participants exhibited above-average mindfulness (M=3.090), learning burnout (M=3.278), and regulatory emotional self-efficacy (M=3.417). Results revealed that mindfulness is directly and negatively related to learning burnout (β=-0.679, t = 28.657, p < .001). Regulatory emotional self-efficacy (β = -0.357, t = 8.592, p < .001) was significantly and negatively related to learning burnout. Mindfulness was significantly and positively related to regulatory emotional self-efficacy (β = 0.638, t = 24.306, p < .001), and regulatory emotional self-efficacy (R2: from .461 to .537) partially mediated the relationship between mindfulness and learning burnout. Besides, the Importance-Performance Matrix Analysis revealed that managing negative emotions significantly contributes to learning burnout but performs poorly, whereas non-reacting demonstrates both the lowest contribution and performance. Findings suggest that mindfulness indirectly alleviates learning burnout through regulatory emotional self-efficacy, providing evidence-based insights for targeted mindfulness interventions in higher education.