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Desktop manufacturing systems such as 3D printers and computer-controlled die cutters have recently become affordable in schools. Because this technology is evolving rapidly, considerable experimentation is occurring as teachers explore opportunities to enhance learning across a range of content areas. Central coordination and planning can facilitate effective use of digital manufacturing technologies in schools. Factors that should be considered include acquisition of technology, placement, and support of the technology, safety, alignment with educational standards and learning objectives

This entry describes technologies that support engineering education, such as 3D printing, computer-assisted design, electromechanical systems and instrumentation, and control systems. Engineering education is one of four disciplines within STEM (science, technology, engineering, and mathematics) education. While science and mathematics are commonly regarded as core subjects in schools, engineering has had a less prominent role in K–12 education. However, engineering is increasingly used to teach science in context. This can increase students’ depth of understanding, allowing them to apply

This paper describes the design and evaluation of a one-week App Inventor summer camp for middle school students with an explicit focus on addressing local community needs. The community focus of the camp was designed to appeal to a broad range of students. We conducted an in-depth interview study to examine its impact on students' attitudes and perceptions, and supplemented this with results from project evaluation. Our results indicate that students had positive experiences in learning and creating real apps for solving community problems. Focusing on local community needs can also help to

Data gathered from 325 middle school students in four U.S. states indicate that both male (p < .0005, RSQ = .33) and female (p < .0005, RSQ = .36) career aspirations for being a scientist are predictable based on knowledge of dispositions toward mathematics, science and engineering, plus self-reported creative tendencies. For males, strong predictors are creative tendencies (beta = .348) and dispositions toward science (beta = .326), while dispositions toward mathematics is a weaker (beta = .137) but still a significant (p < .05) predictor. For females, significant (p < .05) predictors ordered

This article and my career as an educational researcher are grounded in two fundamental assumptions: (a) that research and practice can and should live in productive synergy, with each enhancing the other, and (b) that research focused on teaching and learning in a particular discipline can, if carefully framed, yield insights that have implications across a broad spectrum of disciplines. This article begins by describing in brief two bodies of work that exemplify these two fundamental assumptions. I then elaborate on a third example, the development of a new set of tools for understanding and