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Background This study focuses on probing preservice technology teachers’ cognitive structures and how they construct engineering design in technology-learning activities and explores the effects of infusing an engineering design process into science, technology, engineering, and mathematics (STEM) project-based learning to develop preservice technology teachers’ cognitive structures for engineering design thinking. Results The study employed a quasi-experimental design, and twenty-eight preservice technology teachers participated in the teaching experiment. The flow-map method and metalistening technique were utilized to enable preservice technology teachers to create flow maps of engineering design, and a chi-square test was employed to analyze the data. The results suggest that (1) applying the engineering design process to STEM project-based learning is beneficial for developing preservice technology teachers’ schema of design thinking, especially with respect to clarifying the problem, generating ideas, modeling, and feasibility analysis, and (2) it is important to encourage teachers to further explore the systematic concepts of engineering design thinking and expand their abilities by merging the engineering design process into STEM project-based learning. Conclusions The findings of this study provide initial evidence on the effects of infusing the engineering design process into STEM project-based learning to develop preservice technology teachers’ engineering design thinking. However, further work should focus on exploring how to overcome the weaknesses of preservice technology teachers’ engineering design thinking by adding a few elements of engineering design thinking pedagogy, e.g., designing learning activities that are relevant to real life.

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This study applies the theory of planned behavior as a basis for exploring the impact of knowledge, values, subjective norms, perceived behavioral controls, and attitudes on the behavioral intention toward science, technology, engineering, and mathematics (STEM) education among Taiwanese preservice science teachers. Questionnaires (N = 139) collected information on the behavioral intention of preservice science teachers engaging in STEM education. Data were analyzed using descriptive statistics, path analysis, and analysis of variance. Results revealed that, in terms of direct effects, higher perceived behavioral control and subjective norms were associated with stronger STEM teaching intention. More positive attitude and greater knowledge were indirectly associated with higher subjective norms and perceived behavioral control, which resulted in stronger STEM teaching intention. Additionally, gender did not affect preservice teachers' intention to adopt STEM teaching approaches. However, preservice teachers whose specialization was in different fields tended to influence their knowledge and perceived behavioral control; these issues require further investigation.

This study combined virtual reality (VR) technology, the 6E (Engage, Explore, Explain, Engineer, Enrich, and Evaluate) model, and STEM (Science, Technology, Engineering, and Mathematics) education to develop a hands‐on activity aimed at helping students to achieve “learning by doing.” The participants were 162 tenth‐grade students, divided into the Experimental Group (hands‐on activity using VR technology) and the Control Group (hands‐on activity via lectures). Using sequential analysis, this study investigated how the hands‐on activity influenced the students' behavioral patterns in learning. The results showed that all of the students' learning performances and hands‐on abilities were enhanced. Moreover, the students who used VR technology achieved both significantly better learning performances and hands‐on abilities, indicating that VR might be able to help the students understand abstract scientific concepts and build mental models, which they used to internalize and organize knowledge structures. Furthermore, this study discovered that the students who learned using VR technology formed a cyclical learning pattern, starting with a group discussion (G), moving on to solving problems (S) and developing a product (D), and then going back to another group discussion. However, the students who learned via lectures produced a linear learning pattern in the order of G→S→D.