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.

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.

Teachers’ access to technology in this day and age could have a positive effect on the teaching and learning of English first additional language (EFAL). This qualitative interpretive case study explored how limited access to technology resources affects the teaching practices of Intermediate Phase EFAL teachers in rural schools in Limpopo, South Africa. This study, underpinned by the Technology Acceptance Model (TAM), conducted semi-structured interviews to collect data from ten EFAL teachers who were purposively sampled. Thematic analysis was used to analyse the data. The study revealed that three of the ten EFAL teachers sampled integrated technology into their teaching despite challenges such as insufficient projectors, lack of learners’ smartphones and data bundles, and Internet connectivity. However, the other seven sampled participants did not use technology, citing a lack of digital tools and knowledge as a contributing factor. The study concludes that the lack of resources contributed to limited or no use of technology and the motivation to integrate technology into their lessons. Based on these findings, it is recommended that technological resources that can help EFAL teachers with digital teaching be made available so that they can integrate them to assist learners in developing language skills. Furthermore, in-service training and ongoing support should be provided to EFAL teachers to give them knowledge and skill to use available technology resources effectively.

In recent decades, the work of teachers has been carried out in classrooms characterised by a high degree of diversity, necessitating the provision of pedagogical responses that promote the inclusion of students. This article is derived from the research, development and innovation (R+D+I) project 'Intergenerational Professional Development in Education Implications for the Professional Initiation of Teachers (DePrInED) and aims to analyse how teachers at compulsory education recognise, characterise and conceptualise the diversity and needs of students. A mixed methodological approach was employed, with information collected through focus groups and interviews with a total sample of 147 teachers from different educational levels (young, senior and retired). Thematic analysis, combined with a comparative analysis, was employed to analyse the data using ATLAS.ti software. The main categories analysed dealt with students' needs and their own diversity. The study's primary findings suggest that, in comparison to their retired counterparts, both young and veteran teachers make greater reference to the diversity and needs of students, and emphasise the scarcity of resources and support to effectively address the diversity of students in the classroom. Experienced teachers are found to make more frequent references to diversity and students' needs, while retired teachers make these references less often. This finding assumes particular significance in light of the paucity of studies that adopt a generational perspective to analyse how teachers perceive diversity.

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.