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 research aims to systematically review the integration of artificial intelligence (AI) in English language teaching and learning. It specifically seeks to analyze the current literature to identify how AI could be utilized in English language classrooms, the specific tools and pedagogical approaches employed, and the challenges faced by educators. Using the PRISMA-guided Systematic Literature Review (SLR) methodology, articles were selected from Scopus, Science Direct, and ERIC, and then analyzed thematically with NVivo software. Findings reveal that AI enhances English teaching through tools like grammar checkers, chatbots, and language learning apps, with writing assistance being the most common application (54.55% of studies). Despite its benefits, challenges such as academic dishonesty, over-reliance on AI (27.27% of studies), linguistic issues, and technical problems remain significant. The study emphasizes the need for ethical considerations and teacher training to maximize AI’s potential. It also highlights societal concerns, including the digital divide, underscoring the importance of equitable access to AI-powered education for learners of all socioeconomic backgrounds.

STEM/STEAM education is an interdisciplinary pedagogical approach that cultivates skills in science (S), technology (T), engineering (E), arts (A), and mathematics (M) while also fostering 21st century skills like teamwork, problem-solving, critical thinking, and creativity in learners. Enhancing STEAM and 21st century skills for engineering students facilitates their swift adaptation to STEM/STEAM employment demands in the 4.0 industrial revolution and the ongoing digital transformation in Vietnam. This study aims to investigate the effect of STEAM project-based learning on the 21st century skills of 47 mechanical engineering technology students at a public university in Vietnam. The findings of a one-group pretest-posttest design and an analysis of engineering student groups’ STEAM project-based learning products revealed that there was a significant improvement in students' 21st century skills at a 95% confidence level. Among the three 21st century skills studied, engineering students’ collaboration skill showed a moderate effect size, while problem-solving and creative thinking skills demonstrated a large effect size after implementing STEAM project-based learning in the “Workplace Skills” course. Some significant limitations were identified, including (a) the lack of a comparison group, which may have influenced the difference between the pretest and posttest; and (b) the sustainability of 21st century skills developed through STEAM project-based learning in the “Workplace Skills” course was not investigated. Therefore, studying the effect of other factors on engineering students’ 21st century skills and exploring their sustainability were main recommendations for further research.

Integrating generative artificial intelligence (GenAI) in education has gained significant attention, particularly in flexible learning environments (FLE). This study investigates how students’ voluntary adoption of GenAI influences their perceived usefulness (PU), perceived ease of use (PEU), learning engagement (LE), and student-teacher interaction (STI). This study employed a structural equation modeling (SEM) approach, using data from 480 students across multiple academic levels. The findings confirm that voluntary GenAI adoption significantly enhances PU and PEU, reinforcing established technology acceptance models (TAM). However, PU did not directly impact LE at the latent level—an unexpected finding that underscores students’ engagement’s complex and multidimensional nature in AI-enriched settings. Conversely, PEU positively influenced LE, which in turn significantly predicted STI. These findings suggest that usability, rather than perceived utility alone, drives deeper engagement and interaction in autonomous learning contexts. This research advances existing knowledge of GenAI adoption by proposing a structural model that integrates voluntary use, learner engagement, and teacher presence. Future research should incorporate variables such as digital literacy, self-regulation, and trust and apply longitudinal approaches to better understand the evolving role of GenAI inequitable, human-centered education.

Open schooling is a recent educational approach that has been recently introduced in European policies, so the literature on its transfer to the education system is still limited. The aim of this study is to configure an overview of how open schooling has been implemented in science education in terms of its definition, the topics addressed, the pedagogical aspects considered, and the benefits obtained for the teaching-learning processes. A systematic literature review was carried out using the PRISMA 2020 methodology, in which 27 documents published between 2015 and 2024 were analysed. Open schooling is defined mainly as an approach in which students, teachers, and other stakeholders, especially students’ families, collaborate to provide solutions to real-life issues in search of the community’s well-being. The open schooling experiences usually addressed environmental and health issues through scientific practices and contextualization mainly, developing activities of data collection, synthesis and analysis, dissemination, and information and communication technologies with the students. Companies and local businesses are the preferred stakeholders involved, followed by experts and researchers. Questionnaires are the preferred instruments for data collection, and the documents analysed report benefits for students’ learning and motivation and also for teachers and schools. 

This study explored how the Self-Determination Theory (SDT) framework shaped physics teachers’ professional identities. Through a qualitative case study design, the researcher analyzed the teaching practices, interactions, and pedagogical preferences of two experienced physics teachers. The data sources included classroom observations, semi-structured interviews, informal conversations, and teaching materials. The male teacher adopted a traditional, authority-based approach, while the female teacher employed a student-centered, autonomy-supportive, and relationship-based teaching approach. These findings revealed that teacher identity differed significantly according to the level of meeting the three basic components of SDT: autonomy, competence, and relatedness. The teacher, who gave her students the right to choose experimental activities, collaborated with science centers and included parents in the process, developed a more flexible, participatory, and supportive structure. The other teacher allowed limited student participation in decision-making processes and created a more control-oriented classroom atmosphere. These results showed the importance of addressing autonomy-supported approaches in science teacher education.

The complexity of naming and writing structures of functional groups presents a challenge for many students, often leading to difficulties in mastering fundamental concepts in organic chemistry. This underscores the need for an innovative teaching tool to improve students' understanding and attitude toward the abstract concept of organic chemistry. This study examined the effect of an improvised molecular kit on students' academic performance and attitudes in organic chemistry, focusing on the concepts of alcohol, aldehyde, carboxylic acid, ester, ether, and ketone. A quasi-experimental pretest-posttest design was employed, comparing the control group (traditional teaching methods) with the experimental group (using the improvised molecular kit). Pretest results indicated that both groups initially "did not meet the expectation" in all topics. However, posttest scores showed significant improvement, with the experimental group achieving higher mean scores, while the control group remained at a level of "fairly satisfactory" to "satisfactory." Statistical analysis ANCOVA confirmed significant differences (p < .001) in learning gains, demonstrating the effectiveness of the molecular kit. Furthermore, students' attitudes toward the kit were positive, with strong agreement on its ability to enhance engagement, understanding, and visualization of molecular structures. These findings suggest that the improvised molecular kit is an effective instructional tool, improving conceptual retention and fostering a more interactive learning experience. Integrating hands-on learning strategies in organic chemistry could significantly enhance students' comprehension and overall academic performance.

The emergence of artificial intelligence (AI) has transformed higher education, creating both opportunities and challenges in cultivating students’ critical thinking skills. This study integrates quantitative bibliometric analysis and qualitative systematic literature review (SLR) to map global research trends and identify how critical thinking is conceptualized, constructed, and developed in the AI era. Scopus served as the primary data source, limited to publications from 2022 to 2024, retrieved on February 8, 2025. Bibliometric analysis using Biblioshiny R and VOSviewer followed five stages—design, data collection, analysis, visualization, and interpretation—while the SLR employed a deductive thematic approach consistent with PRISMA guidelines. A total of 322 documents were analyzed bibliometrically, and 34 were included in the qualitative synthesis. Results show that Education Sciences and Cogent Education are the most productive journals, whereas Education and Information Technologies have the highest citation impact. Several influential documents and authors have shaped global discussions on AI adoption in higher education and its relationship to critical thinking. Thematic mapping identified five major research clusters: pedagogical integration, ethical and evaluative practices, technical and application-oriented AI models, institutional accountability, and socio-technical systems thinking. Conceptually, critical thinking is understood as a reflective, evaluative, and metacognitive reasoning process grounded in intellectual autonomy and ethical judgment. Across the reviewed literature, strategies for fostering critical thinking converge into three integrated approaches: ethical curriculum integration, pedagogical and assessment redesign, and reflective human–AI collaboration. Collectively, these strategies ensure that AI strengthens rather than replaces human reasoning in higher education.

This study aims to investigate the effect of digital leadership, creativity, and proactive personality on innovative work behavior (IWB) through work engagement. The research involved 436 private school teachers in Indonesia. The research data were collected by a Likert scale questionnaire. Data analysis is done using structural equation modeling based on Partial Least Squares (SEM-PLS), with descriptive and correlational analysis as supplements. The findings indicated that digital leadership, creativity, proactive personality, and work engagement affect teacher IWB; digital leadership, creativity, and proactive personality impact teacher work engagement; and digital leadership, creativity, and proactive personality affect teacher IWB through work engagement. These findings introduce a new empirical model of the influence of digital leadership, creativity, and proactive personalities on teachers' IWB through work engagement. This model deserves to be discussed critically and in-depth, and adapted and adopted by researchers to enrich their future research. This model can also be modified and adopted by school practitioners (management) to accelerate and optimize teachers' IWB capacity based on digital leadership, creativity, proactive personality, and work engagement.