Surface area is consistently identified as a curriculum standard for K-12 students and it regularly appears on national and international assessments. Recently, many schools began acquiring digital fabrication and advanced manufacturing equipment. The growing use of digital fabrication in classrooms raises the question of whether or not this technology can be used to improve students’ understanding of surface area. The specific question we explore in this paper is: How did participation in a digital fabrication-augmented surface area unit affect 5th grade students’ ability to solve surface

Desktop digital fabrication technologies provide students with access to concrete and virtual manipulatives, which have both been identified as useful instructional tools to support student learning in a variety of different content areas, such as mathematics. In particular, these technologies can be used to help support students' development of conceptual understandings of three-dimensional measurement. This article describes how a digital fabrication-augmented unit supported the teaching and learning of surface area. Our goal was to see how working with both virtual and concrete

The Laboratory School for Advanced Manufacturing (Lab School) was established to identify and develop effective educational practices for advanced manufacturing technologies in schools. The Lab School is grounded in the premise that students can learn through the design and fabrication process. Students of all ability levels from a diverse population participate in the program with the goal of increased diversity in the STEM pipeline. The advent of digital fabrication technologies such as desktop 3D printers now offers students an opportunity to see their ideas and concepts realized in

Missing data are a common and significant problem that researchers and data analysts encounter in applied research. Because most statistical procedures require complete data, missing data can substantially affect the analysis and the interpretation of results if left untreated. Methods to treat missing data have been developed so that missing values are imputed and analyses can be conducted using standard statistical procedures. Among these missing data methods, Multiple Imputation has received considerable attention and its effectiveness has been explored, for example, in the context of

Propensity score (PS) methods provide viable strategies for reducing selection bias in non-experimental (observational) studies. An NSF funded project previously used propensity score analysis to examine the impact of special educational programs on advanced mathematics course enrollment (Rodriguez de Gil, et al., 2012). Results indicated that students who enrolled in career academies were almost twice as likely to enroll in a Calculus course. Encouraged by the findings from the previous study, we are currently using PS and discrete-time survival analyses to investigate rigorous high school

The purpose of this research was to develop and test a model of factors contributing to science, technology, engineering, and mathematics (STEM) learning and career orientation, examining the complex paths and relationships among social, motivational, and instructional factors underlying these outcomes for middle school youth. Social cognitive career theory provided the foundation for the research because of its emphasis on explaining mechanisms which influence both career orientations and academic performance. Key constructs investigated were youth STEM interest, self-efficacy, and career

Lifelong learning is a beautiful phrase, full of ambition while remaining conveniently vague. Everyone claims they’re a lifelong learner. But what does that mean, and what does it look like in practice?The second event in a three-part Dialogues with Gensler series—held March 26, 2015 in Chicago—explores what a proactive approach to lifelong learning might look like in both the workplace and in academia. How do we challenge traditional paths to educational success? And how can we promote spaces in our everyday lives that foster collaboration, discovery, and professional development?New

A multidisciplinary project from the University of Arizona aims to encourage elementary students to consider careers in science, technology, engineering and math (STEM) by involving them in research involving their own sleep patterns.

In middle school, children either develop an affinity for math and science or begin believing they do not possess the mental agility necessary to succeed in subjects such as algebra and geometry.Those subjects are important early entry points if youth are to eventually become nurses, physicians, software developers, engineers, business intelligence analysts and other high-in-demand specialists.A University of Arizona team is working to circumvent that lost interest, targeting students before they even reach middle school — and involving their families — while also addressing another pervasive

Article on marine technology program.