The first years of teaching are crucial for novice teachers’ integration into and retainment in the education system. The support they receive from experienced teachers impacts their professional development. Science, technology, engineering, and mathematics (STEM) teachers require specialized support from domain-specific mentors. In this study, we examined how a three-level mentoring support system contributes to STEM novice teachers’ professional growth (PG) and to their mentors. The support system levels are individual mentoring, group mentoring, and mentoring networks. Based on the framework of teachers’ professional development, there are three PG dimensions: personal, professional, and social. Our research goal was to analyze teachers’ professional growth by the various mentoring level and dimension combinations. The study, conducted using a mixed methods approach, included 123 novice and 78 experienced STEM teachers. We examined the novice teachers’ perceptions of their teaching efficacy, the mentoring factors, correlations between the professional growth dimensions, and the contribution of each support level to the growth dimensions. We found that experienced teachers perceive novice teachers’ efficacy as lower than that perceived by the novice teachers. We identified gaps between the mentoring factors described by novice and experienced teachers and a strong correlation between the growth dimensions. All three mentoring support levels facilitate substantive personal, professional, and social growth. Individual mentoring contributes the most to all three growth dimensions, followed by mentoring networks. The contribution of this research is its elucidation of the intertwined support levels, which provide scaffolds for the novice teachers and facilitate the growth of the experienced teachers.

This study explores Science, Technology, Engineering and Mathematics (STEM) teachers’ perceptions of teaching and assessment methods. We investigated 125 STEM subject coordinators and teachers using interviews and questionnaires. We examined the most commonly implemented teaching and assessment methods, and the reasons teachers chose them. Then, we compared teachers from different school levels, subjects, teaching experience and cultural backgrounds. The teaching methods implemented the most were lectures and presentations, followed by class discussions and collaborative classwork. The most implemented assessment method was tests with open- and closed-ended questions, followed by project portfolios and experiment reports. Subject coordinators preferred methods that integrate formative assessment more than teachers. The study contributes to a better understanding of the teaching and assessment methods implemented in schools and the gap between recommendations and actual implementation. Conducted prior to the COVID-19 pandemic, this research sets a baseline for similar future post-COVID research.

Modeling and systems thinking skills, as well as scientific understanding, are necessary for comprehending complex, food-related processes. The aim of this research was to evaluate the effect of food-related learning units on graduate students’ systems thinking and modeling skills, as well as on their understanding of science, technology, engineering, and mathematics (STEM) issues. In this research, six STEM experts constructed a conceptual model of the codfish tracking process using Object-Process Methodology. Next, 15 STEM graduate students, who are prospective teachers, participated in a graduate course, which includes four online units on food production processes based on their respective models. Research tools included an expert focus group, student assignments, and questionnaires. Modeling and scientific understanding rubrics were adapted and validated for analysis of the assignments. We found a significant difference in the scores of systems thinking and modeling skills between students with modeling background and those without. Based of students’ feedback along the course, learning in context of food and sustainability also contributed to developing these skills. The contribution is the combination of food production and conceptual models for developing STEM teachers’ systems thinking and modeling skills, and their scientific understanding of food processes and sustainability issues.

We investigated the impact of project-based learning (PBL) on undergraduate food engineering students’ learning outcomes, focusing on food science, biotechnology, chemical knowledge, and thinking skills. The PBL course was offered in the department of biotechnology and food engineering at a research-intensive STEM university and emphasized context-based learning through the planning, design, and production of an innovative food product. Data were collected using a mixed-methods approach. The study included 68 students who completed questionnaires and presented scientific posters and final projects. We assessed students’ learning outcomes in four domains: (a) their ability to explain key concepts and processes (actual knowledge), (b) their self-confidence regarding these constructs, (c) their ability to identify the main subject of a paragraph in a scientific paper, and (d) their capacity to pose complex questions about the papers they had read. We further examined the transfer of theoretical and practical knowledge in designing and presenting a novel food product, as well as students’ monitoring of their knowledge along the cognitive–metacognitive spectrum. The findings revealed significant correlations between students’ knowledge and most of their skills, as well as between their knowledge and final project grades. This study contributes to the growing body of literature on undergraduate students’ cognitive and metacognitive development and offers a method to detect monitoring skills by comparing students’ actual disciplinary knowledge with their self-confidence in that knowledge.