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As distance learning becomes increasingly important and artificial intelligence tools continue to advance, automated systems for individual learning have attracted significant attention. However, the scarcity of open-source online tools that are capable of providing personalized feedback has restricted the widespread implementation of research-based feedback systems. In this work, we present RATsApp, an open-source automated feedback system (AFS) that incorporates research-based features such as formative feedback. The system focuses on core STEM competencies such as mathematical competence, representational competence, and data literacy. It also allows lecturers to monitor students’ progress. RATsApp can be used at different levels of STEM education or research, as it allows the creation and customization of the educational content. We present a specific case of its implementation in higher education, where we report the results of a usability survey (N=64), using the technology acceptance model 2 (TAM2), to evaluate the user experience of undergraduate students. Our findings confirm the applicability of the TAM2 framework, revealing that factors such as the relevance to the course of study, output quality, and ease of use significantly influence the perceived usefulness. We also found a linear relation between the perceived usefulness and the intention to use, which in turn is a significant predictor of the frequency of use. Moreover, the formative feedback feature of RATsApp received positive feedback, indicating its potential as an educational tool. Furthermore, as an open-source platform, RATsApp encourages public contributions to its ongoing development, fostering a collaborative approach to improve educational tools.

Recently, integrated science, technology, engineering, and mathematics (STEM) education has gained sustained attention in K-12 settings, and engineering design-based pedagogy has become a key issue. Compared with rich research in higher education, relatively few studies are performed on engineering education in K-12 schools. In this study, we combined Conceive-Design-Implement-Operate (CDIO) model with the engineering design process (EDP), naming EDP-CDIO, aiming to promote high school students’ STEM competence and compare its effects with the conventional CDIO approach. A pretest–posttest nonequivalent group design was conducted among 64 eleventh-grade students with eleven lessons. Quantitative data were collected via a pretest and posttest, and qualitative data were collected via artifacts and semistructured interviews. The repeated-measures analysis of variance and epistemic network analysis revealed that, compared with the conventional CDIO approach, the EDP-CDIO model significantly improved students’ STEM knowledge, skills, and attitudes and developed more comprehensive epistemic networks in STEM competence. These findings provide a reference for K-12 STEM teachers, encouraging them to implement the EDP-CDIO model more frequently in the classroom, especially with the iterative design process.

STEM education is established as an alternative for developing 21st century skills, with the premise of integrating its component disciplines. Although numerous studies exist on the subject, STEM teacher training programs are not widely discussed. Therefore, a systematic literature review was conducted in Scopus and Web of Science to identify the intentions of the training and the design and implementation of such teacher training programs. Among the 15 articles identified, there are three groups of intentions: Improving knowledge, developing competencies and skills, and changing attitudes and perceptions. Five methodological strategies were identified: project-based learning, problem-based learning, collaborative learning, ODR (observation/discussion/reflection) approach, and design-based learning. Disciplinary integration can be achieved through content or competencies. It is concluded that design-based learning is the most appropriate strategy for disciplinary integration. It is recommended that research be conducted to measure the impact of modality and time of training on the development of STEM competencies.

Artificial intelligence and the autonomous robots of the Fourth Industrial Revolution will render certain jobs and competences obsolete but will also create new roles, which in turn will require new sets of skills. They will also transform how we produce, distribute and consume, as well as how we think. Rather than a linear understanding of evolutionary processes, we will develop a more interactive and circular interpretation. This book offers a unique and holistic perspective on the future of work in the context of industry 4.0. It discusses the globalization of capital markets, how artificial intelligence can help organizations to be more competitive and the new role of leadership in this technological landscape. The author argues that there are four categories of competences, which will be required to maintain the relevance of human skills and expertise in the innovation economy. The new jobs that come into being will lend themselves to a particular set of skills. General competences will be necessary for roles involving the 4Cs of communication, creativity, collaboration and change. Specific or STEM competences will be called for across the science, technology, engineering and mathematics sectors. Human competences will lend themselves to positions comprising the SELC framework of social, emotional, leadership and cultural skills. Critical or REVE competences will be in demand for roles embracing reflection, ethics, values and the environment. This book provides a human-centric view of the current technological advancements of artificial intelligence and robotics and offers a positive outlook for human actors seeking continued relevance. It will appeal to scholars and students of the innovation economy, the knowledge society and the coming Fourth Industrial Revolution.

Gaps between science, technology, engineering, and mathematics (STEM) education and required workplace skills have been identified in industry, academia, and government. Educators acknowledge the need to reform STEM education to better prepare students for their future careers. We pursue this growing interest in the skills needed for STEM disciplines and ask whether frameworks for 21st century skills and engineering education cover all of important STEM competencies. In this study, we identify important STEM competencies and evaluate the relevance of current frameworks applied in education using the standardized job-specific database operated and maintained by the US Department of Labor. Our analysis of the importance of 109 skills, types of knowledge and work activities, revealed 18 skills, seven categories of knowledge, and 27 work activities important for STEM workers. We investigate the perspectives of STEM and non-STEM job incumbents, comparing the importance of each skill, knowledge, and work activity for the two groups. We aimed to condense dimensions of the 52 key areas by categorizing them according to the Katz and Kahn (1978) framework and testing for inter-rater reliability. Our findings show frameworks for 21st century skills and engineering education do not encompass all important STEM competencies. Implications for STEM education programs are discussed, including how they can bridge gaps between education and important workplace competencies.

This paper explores the potential of microbiology education at the secondary school level as a catalyst for enhancing both science, technology, engineering and mathematics (STEM) literacy and essential 21st‐century competencies. As an inherently interdisciplinary field, microbiology offers an effective platform to develop scientific and technological knowledge while cultivating broader competencies, such as emotional intelligence, creativity and critical thinking, as outlined by UNESCO (UNESCO, 2016). Scientific, societal and educational (SSE) challenges for the next decade are interlinked, and many of these trans‐dimensional issues require a solid foundation in biology and microbiology. Thus, research and education must evolve in step with these trends. Despite growing advocacy for microbiology in high school curricula, a significant gap remains in understanding how its teaching aligns with these broader developmental goals. This disconnection is particularly evident in Europe, where STEM engagement among youth remains low. As an experimental and accessible science, microbiology offers unique pedagogical strategies that address not only the cognitive dimensions of STEM but also the skills and attitudes needed for a complex, digital and interdependent world. By integrating microbiology into secondary education, teachers can bridge the gap between scientific literacy and future readiness, empowering students to build a generation capable of shaping a sustainable and innovative future. In this discourse, we describe examples of topics and strategies that could be implemented at the secondary education level, as well as at other educational levels, including university. This work highlights how microbiology education can empower secondary school students with critical and systems thinking, fostering STEM literacy, overcoming barriers and preparing informed, responsible global citizens for a sustainable, digital and interconnected world.

Background Prominence of Science, Technology, Engineering, and Mathematics (STEM) competencies has transcended mere academic achievements, contributing cross-cuttingly to individual, societal, and global development. Despite consensus that STEM-related outcomes are largely shaped by complex and interconnected factors, key determinants of STEM competencies remain insufficiently explored. Guided by Dynamic Model of Education Effectiveness (DMEE), the current study draws on Programme for International Student Assessment (PISA) 2022 dataset to identify key determinants of STEM competencies. Methods This study leverages data from 522,802 fifteen-year-old adolescents across 66 economies using six machine learning models, including Naïve Bayes, Decision Tree, Logistic Regression, Random Forest, AdaBoost, and XGBoost, to identify factors contributing to STEM competencies. In addition, this study examines model effectiveness by assessing predictive accuracy of each classifier. Results This study identified a key set of variables that predict STEM competencies, including home possessions, student part-time employment, gender, cognitive activation for reasoning, and mathematics anxiety. Model evaluation indicated that XGBoost classification outperformed other classifiers, with an average test accuracy of 78.3%. Conclusions Findings illuminate the complex interplay of student-, family-, and school-level factors in determining STEM competencies, suggesting the need to consider multifaceted, non-linear interactions across intra- and inter-personal levels, and design targeted interventions.

With solely academic knowledge, it appears challenging for today's students to find a place for themselves in the business world where they will operate in the future. Therefore, it is crucial to provide students with a variety of abilities, such as problem-solving, critical thinking, creativity, collaboration, and analytical thinking, in addition to academic knowledge. The STEM education approach is one of the approaches that aims to equip students with the knowledge and abilities they need in the fields of science, technology, engineering, and mathematics while also educating them as persons with 21st-century competencies. In this context, it is the teachers who will provide students with these knowledge and skills and apply STEM education. In this sense, it is thought that teachers' knowledge and competencies in STEM teaching are significant. In this study, it was aimed to determine the STEM teaching competencies of pre-service teachers studying in the last year of education faculties. The case study design, one of the qualitative research methods, was used in the research. The study group of the research consists of 45 final year science and classroom teaching students studying at 21 different universities in Turkey. The data of the research was obtained by the \"STEM Teaching Competencies Questionnaire\" developed by the researchers. The obtained data were analyzed simultaneously by three different researchers using content analysis. During the analysis process, codes, categories and themes were created. As a result, it can be claimed that pre-service teachers have theoretical knowledge of STEM education, but they do not think of themselves as highly competent. They require more hands-on education and wish to use it when they begin their careers, but they need practice-based education for this

Mathematical modeling is a high-leverage topic, critical for college and career readiness, participation in STEM education, and civic engagement. Mathematical modeling involves connecting real-world situations, phenomenon, and/or data with mathematical models, and in this way applies across various STEM disciplines, including mathematics, engineering, and science. Although research has begun to explore mathematical modeling instruction in the elementary grades, questions remain about how to assess student learning at the elementary level. We addressed this need by designing an assessment of mathematical modeling competencies for students in grades 3 through 5. Informed by international research, our assessment includes a hybrid structure to assess mathematical modeling competencies holistically (as students engage in the complete modeling process) and atomistically (as students engage in different components of the modeling process, including making sense of phenomena and real-world situations, setting up and operating on mathematical models, and interpreting results in relation to the real-world context). We conducted student interviews, followed by two rounds of pilot testing to inform item development and ensure acceptable psychometric properties. The final assessment included 13 items (9 multiple choice, 3 open-response, and 1 complete modeling task). We describe our assessment development process, and provide sample assessment items and detailed coding rubrics. We summarize quantitative analyses which established high reliability and low standard error for our assessment, supporting its use for grades 3 to 5. Implications of our framework and assessment for mathematical modeling instruction and future research on STEM learning are discussed.

Purpose This paper aims to propose and examine the relationship between students’ perception of service quality and dimensions and their academic achievement. Design/methodology/approach Based on the resource-based view, a conceptual relationship between service quality and dimensions and academic achievement is proposed and tested with a sample of 380 STEM university students who attended secondary schools in a region of Spain. Findings Service quality and four of its dimensions (i.e. empathy, reliability, responsiveness and assurance/confidence) could contribute to students’ academic achievement. The expected effect of tangible elements on academic achievement was not supported by the data. Results were controlled for student’s personal factors that have proven important in explaining academic achievement in previous studies (i.e. need for cognition, need for emotion and self-efficacy). Originality/value Previous research has extensively studied factors affecting students’ academic achievement. However, the direct relationship between service quality and student’s academic achievement has been rarely proposed and examined. Service quality has been mostly viewed as a precursor of student satisfaction and loyalty. This research views service quality as a school higher-order capability that supplements students’ capabilities.