The objective of this research was to assess the efficacy of project-based learning in enhancing the analysis of student worksheets in the domains of Science, Technology, Engineering, Arts, and Mathematics (STEAM) with the integration of the ecoprint technique, focusing on its influence on student motivation and creativity. This investigation was conducted as a quasi-experiment involving a sample size of 150 students selected through cluster sampling. Data collection was executed using standardized tests, with instrument validity ascertained through the Aiken index and instrument reliability determined via Cronbach's alpha coefficient. Data analysis was performed using multivariate analysis (MANOVA) and descriptive quantitative methods. The study's findings reveal a significant disparity in the mean scores of both learning motivation and student creativity. In conclusion, the implementation of project-based learning coupled with STEAM-based student worksheet analysis utilizing the ecoprint technique yields a substantial enhancement in learning motivation and student creativity. These findings underscore the success of employing STEAM-based worksheets in conjunction with the ecoprint method to foster students' motivation and creativity, as ecoprint inherently encompasses all STEAM components within the manufacturing process.

Increasing the number of entrepreneurs is not just a school task, it requires joint work between educational institutions and the community. Using structural equation modeling, this research aims to investigate the role of community in promoting entrepreneurial careers for students, by adding achievement motivation, entrepreneurial attitudes, and entrepreneurial intentions as predictor variables. The population of this research was high school students in urban areas, and the sample was taken based on convenience sampling, with a total of 300 students participating. Data were analyzed using EFA, CFA, and structural model evaluation using SPSS 24.0 and AMOS 24.0. The research results show that all hypotheses are accepted, meaning that community support influences students' entrepreneurial career choices, as do other predictor variables. This study can provide guidance for developing educational strategies and policies that support the development of young entrepreneurs in the future, through predictor variables.

This study aims to explore the relationship between proactive behaviors, teaching performance, and organizational support among vocational college teachers. Based on the theory of organizational support, we conducted a survey of 373 teachers from four vocational colleges in Shanxi Province, using scales for proactive behaviors, organizational support, and teaching performance. The results indicate that: (a) There is a significant correlation between teachers' proactive behaviors and teaching performance; (b) There is a significant correlation between teachers' proactive behaviors and organizational support; (c) Organizational support plays a significant mediating role in the relationship between teachers' proactive behaviors and teaching performance. This study enriches the application of organizational support in vocational colleges, providing empirical evidence for improving teachers' proactive behaviors in higher education institutions, which could be useful for central or local education policy decision-makers and implementing units. Additionally, this model could be further applied beyond vocational education to other contexts or policies, demonstrating both theoretical and practical significance.

Mathematical modeling offers a promising approach to improving mathematics education. This study aims to determine if the concept of metacognitive awareness in the learning process is associated with mathematical modeling. This study also considers the interaction effect of sex and academic year level on both variables. Focusing the study on preservice elementary teachers might address potential issues and targeted intervention in their preparation program concerning their ability to teach and guide young learners in modeling activities. The research sample includes 140 preservice elementary teachers at Central Luzon State University, Philippines. Data collection used an adapted metacognitive awareness inventory and a validated researcher-made mathematical modeling competency test aligned with the K-12 mathematics curriculum in the Philippines. Results revealed that the preservice elementary teachers had a high metacognitive awareness and mathematical modeling competency, ranging from 22 to 31 out of 36 points. Besides, Factorial ANOVA indicates that academic year level positively affects both variables regardless of sex, and stepwise regression analysis unveiled that information management, declarative knowledge, and planning significantly predict 41.4% of the mathematical modeling competency variance. This suggests that developing metacognitive awareness supports preservice elementary teachers in performing modeling tasks that improve their competency level in mathematics.

Information and Communication Technology (ICT) brings modern learning approaches, forms and methods to education, and with them new opportunities for learning and teaching. The use of ICT in the classroom motivates students, enables them to participate, provides individualisation and differentiation, interactivity, and encourages creativity and critical thinking. Teachers play a very important role in this, as they are the ones who can provide students with a stimulating learning environment, including through the use of ICT. As Slovene (first language) is the subject with the most teaching hours in public primary schools in the Republic of Slovenia, we conducted an empirical study on the views of general and subject teachers of Slovene (N = 190) on the integration of information and communication technology in teaching. Teachers’ opinions were investigated through quantitative research. We found that teachers frequently use ICT in Slovene lessons, namely for repeating and consolidating learning material and for presenting new learning material, and that ICT is used most often in frontal forms of learning. Teachers mostly use LCD projectors, computers, interactive whiteboards, e-workbooks, audio recordings and videos. We also found that teachers are moderately satisfied with the available ICT equipment and e-materials, and that they feel moderately competent when it comes to using ICT in Slovene lessons. Teachers also used ICT during the COVID-19 epidemic. We also found that there are no statistically significant differences in the use of ICT between teachers teaching Slovene according to their teaching level, age and years of service.

The computing and creative skills of students in Indonesia are still low since the government has not focused on student creativity and computational empowerment programs. This research aims to develop a science, technology, engineering, art, mathematics, and reflection (STEAMER) hybrid learning project model for teachers' creative and computational thinking abilities, as well as analyze elementary school teacher candidates' perceptions of the use of STEAMER hybrid learning model to improve teachers' creative and computational thinking abilities. This research is development research with an analysis, design, development, implementation, and evaluation (ADDIE) model. The instruments used in this study were questionnaires and interviews with experts, lecturers, and elementary school teacher candidates. The research was conducted at eight universities in Indonesia with a total sample of 100 elementary school teacher candidates. Through quantitative and qualitative data analysis, the research results have developed the STEAMER hybrid learning project model based on learning theory, syntax, social systems, support systems, and the instructional impact of learning models. The results of the validation show that the developed learning model is feasible in terms of model, material, media, and language experts. The model is suitable for elementary school teacher education. Furthermore, based on the perceptions of the teacher candidates, it is stated that the STEAMER hybrid learning project can develop the ability of the teacher candidates to think creatively and computationally.

The research on the pedagogical knowledge of teachers in technological education arises from the need to address the problem of pedagogical practices, which are traditional. The classes are at the graduate level, focusing on lecturing the student while the student remains with a passive attitude. It is believed that making explicit that teachers' pedagogical knowledge will allow reflection and awareness, thereby transforming pedagogical practices. Therefore, the objective is to understand the teachers’ constructions on pedagogical knowledge in technology programs in Plant Operations and Industrial Instrumentation of the Faculty of Engineering in order to reconstruct it theoretically, as well as identify its characteristics and trace action routes for teacher training. In this way, it allows education to be accessible to low-income and resource-poor populations, whose purpose is to strengthen the productivity and competitiveness of the economy through the training of human talent according to the needs of the working sector in a unique context. This research uses grounded theory as a methodological tool for data processing. In this sense, data collection procedures such as in-depth interviews were conducted with 16 teachers and seven of them were related to the industry. Whereas, 9 were linked to the teaching(educational) sector including elementary, high school and college level. The results showed differentiated, and socially constructed pedagogical knowledge that responds to teachers’ nature in a particular context. These results contribute to consolidate a broad vision about the pedagogical knowledge’s characteristics that the teacher builds.

This PRISMA-based systematic review analyzes how artificial intelligence (AI) and Machine Learning (ML) are integrated into educational institutions, examining the challenges and opportunities associated with their adoption. Through a structured selection process, 27 relevant studies published between 2019 and 2023 were analyzed. The results indicate that AI adoption in education remains uneven, with significant barriers such as limited teacher training, technological accessibility gaps, and ethical concerns. However, findings also highlight promising applications, including AI-driven adaptive learning systems, intelligent tutoring, and automated assessment tools that enhance personalized education. The geographical analysis reveals that most research on AI in education originates from North America, Europe, and East Asia, while developing regions remain underrepresented. Without strategic integration, the uneven implementation of AI in education may widen social inequalities, limiting access to innovative learning opportunities for disadvantaged populations. Consequently, this study underscores the urgent need for policies and teacher training programs to ensure equitable AI adoption in education, fostering an inclusive and technologically prepared learning environment.

These days, many schools are reviewing their curricula, and Science, Technology, Engineering, Arts, and Mathematics (STEAM) education is one area where these changes are being applied. Because STEAM education integrates five subjects, it requires an approach in which teachers from these subjects work collaboratively. However, applying traditional assessment methods in STEAM education is challenging, as it requires teachers to jointly decide on appropriate assessment strategies. At present, no clear framework exists to support this process. This study examined the potential of the ordinal priority approach (OPA), a recently introduced method for multi-criteria decision-making, to facilitate teachers’ collaborative selection of assessment methods for STEAM education. It further explored the extent to which subject differences affect collaboration by comparing the decision-making of two groups: a homogeneous group (teachers of the same subject) and a heterogeneous group (teachers of different subjects). Pre- and post-questionnaires were administered to both groups to determine how the OPA can assist teachers in jointly developing a STEAM assessment method. Analyses of the responses identified differences in each group’s consensus-building process. The study revealed three key contributions of OPA to teacher collaboration in STEAM education: 1) it ensures that teachers from diverse subjects have their opinions considered; 2) its transparent decision-making process helps mitigate distrust during discussions; and 3) it promotes fair decision-making, unaffected by social power differences within the group. Based on these findings, OPA appears effective in converging diverse expert opinions through a clear decision-making process.

In recent years, significant developments have occurred in AI-based chatbots that have been effectively deployed in the educational field. However, given the novelty of this technology, descriptive analyses remain scarce. Although many review studies have focused on the effectiveness of chatbots, they generally present broad results, and only a few have addressed the impact of this technology on learning outcomes. The present study examines the educational implications of AI chatbots on various learning outcomes through a post hoc analysis conducted in accordance with PRISMA principles. It aims to aggregate and analyze findings from studies that examined the use of chatbots and their impact on specific learning outcomes. A total of 26 studies were selected from a pool of 6,721 published between 2021 and 2024 and indexed in the Scopus and Web of Science databases. Data analysis was conducted using the Newcastle-Ottawa Scale (NOS) for Education. The results revealed that AI-chatbot technology has a positive influence on several learning outcomes, including academic achievement, motivation, self-assessment, engagement in learning, self-efficacy, and language learning, among others. The studies also detailed the methodologies and tools employed in these investigations. The study also offers insights into how intelligent chatbots can be leveraged to enhance various learning outcomes.

Vocational education plays a pivotal role in nurturing talent and supporting national development. However, challenges such as outdated talent development concepts, insufficient teacher training, and a lack of attention to soft skills cultivation from both schools and students have hindered the comprehensive development of secondary vocational students. This study aims to explore the direct effect of perceived teachers’ transformational leadership on the soft skills of 324 secondary vocational students in China and to examine the mediating role of students’ self-efficacy in this relationship. Using Structural Equation Modeling (SEM), the results show that teachers’ transformational leadership has a significant positive effect on students’ soft skills (β = 0.33, p < .01). Moreover, self-efficacy partially mediates this relationship (indirect effect β = 0.07, p < .05), accounting for 22.6% of the total effect. These findings suggest that teachers’ inspirational motivation, individualized consideration, and intellectual stimulation directly foster students’ communication, teamwork, and problem-solving skills, while also indirectly strengthening them by enhancing students’ confidence. Practically, the study underscores the need for teacher training in transformational leadership and for policy initiatives that integrate soft skills into vocational curricula.