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Manufacturing is undergoing rapid changes due to the demands of product complexity and variety, and therefore factories are demanded to become smarter and more efficient. This transformation is known as advanced manufacturing and will require a new generation of skilled employees. There is a huge lack of qualified personnel in advanced manufacturing stemming from a lack of student interest compounded with a lack of experienced teachers who usually motivate students. This paper describes the findings of an NSF RET project at an US university that successfully addresses the common need to produce STEM graduates in the advanced manufacturing area. We recruited fifteen high school and community college STEM educators for a six-week immersive summer research experience in the state-of-the-art robotics laboratory. At the end of their research workshop, they developed customized hands-on advanced manufacturing curricula for their students. This project produced fifteen competent high school and community college educators, who are capable of blending research with educational activities at their institutions, motivating students for STEM degrees, and building long-term collaborative partnerships in the region. This paper will share some of their successful research projects, how they translated their research into actionable curriculum modules, and some lessons learned from implementations. This paper will also explain the evaluation process and share the results. In view of the pre-survey and post-survey data analyses, it can be concluded that educator participants of the program increased their knowledge and research experiences at very high-quality research facilities and under expert guidance. 

Classical mechanics courses are taught to most engineering disciplinary undergraduate students. Due to the recent advancements of multiscale analysis and practice, necessary reforms need to be investigated and explored for classical mechanics courses to address the materials’ mechanics behaviors across multiple length scales. This enhanced understanding is needed for engineering students to consider materials more broadly. This paper presents a recent effort for the development of a multiscale materials and mechanics experimentation (M3E) module that can be potentially implemented in undergraduate mechanics courses, including Statics, Dynamics, Strength of Materials, and Design of Mechanical (Machine) Components. The developed education module introduces the concepts of multiscale materials behavior and microstructures in the form of micro and macro-scales. At the micro-scale, both 3D printed aluminum and cold-rolled aluminum samples were characterized using scanning electron microscope. Microstructures, including grains, grain boundaries, dislocation, precipitates, and micro-voids, were demonstrated to students. At the macro-scale, experiments following ASTM standards were conducted and full strain fields carried by all the samples were analyzed using digital image correlation method. The experimental data were organized and presented to the students in the developed M3E module. The implementation of the developed module in undergraduate mechanics classes allows students to not only visualize materials behavior under various load conditions, but also understand the reasons behind classical mechanics properties. To assess the effectiveness of the developed M3E education module, an evaluation question was developed. Students are required to classify key mechanics, materials, and processing concepts at both micro and macroscales. More than 40 fundamental concepts and keywords are included in the tests. The study outcomes and effectiveness of the M3E education module will be reported in this paper. 

Engineering programs, in general, do not explicitly address the need to enhance divergent thinking. To a certain extent this is due to a lack in knowledge on the cognitive and neural mechanisms underlying divergent thinking, and creative ideation more generally. We hypothesize that we can help enhance our students’ divergent thinking and creative processing outcomes by investigating the impacts of carefully selected methods and tools enabled by developments in the robust analysis of engineering ideation performance, and neurocognitive responses to creativity. In this paper, we present an experiment using the Event-Related brain Potentials (ERP) technique and creative language use (funded by Core R&D Programs). More specifically, we collected ERP responses to literal, nonsense, and novel metaphorical sentences that were either referring to engineering knowledge or general knowledge, testing engineering and non-engineering students. Following Rutter et al. [1], sentences differed in verb only and had been classified in prior sentence norming studies as highly unusual and highly appropriate (novel metaphors), low unusual and highly appropriate (literal sentences), and highly unusual and low appropriate (nonsense sentences). Participants read sentences while their EEG was recorded, and after reading the sentence made judgments about its unusualness and appropriateness. The findings indicate that prior knowledge modulates novel metaphor processing at the stage of lexico–semantic access, indexed by the amplitude of N400 component. Specifically, N400 amplitudes to novel metaphorical sentences are significantly reduced and pattern with literal sentences in engineers; in nonengineers, by contrast, we observed increased N400 amplitudes to novel metaphorical sentences that pattern with anomalous sentences. This mirror effect on the N400 corroborates recent findings demonstrating a strong impact of prior experience and expertise on meaning ambiguity resolution, which may in turn have implications for creative cognition. 

Creativity is the driver of innovation in engineering. Hence, assessing the effectiveness of a curriculum, a method, or a technique in enhancing the creativity of engineering students is no doubt important. In this paper, the process involved in quantifying creativity when measured through the alternative uses task (AUT) is explained in detail. The AUT is a commonly used test for divergent thinking ability, which is a main aspect of creativity. Although it is commonly used, the processes used to score this task are far from standardized and tend to differ across studies. In this paper, we introduce these problems and move towards a standardized process by providing a detailed account of our quantification process. This quantification process takes into consideration four commonly used dimensions of creativity: originality, flexibility, fluency, and elaboration. AUT data from a preliminary case study were used to illustrate how the AUT and the quantification process can be used. The study was performed to understand the effect of the stereotype threat on the creativity of 25 female engineering students. The results indicate that after the stereotype threat intervention, participants generated more diverse and original ideas. 

Abstract Novel metaphorical language use exemplifies human creativity through production and comprehension of meaningful linguistic expressions that may have never been heard before. Available electrophysiological research demonstrates, however, that novel metaphor comprehension is cognitively costly, as it requires integrating information from distantly related concepts. Herein, we investigate if such cognitive cost may be reduced as a factor of prior domain knowledge. To this end, we asked engineering and nonengineering students to read for comprehension literal, novel metaphorical, and anomalous sentences related to engineering or general knowledge, while undergoing EEG recording. Upon reading each sentence, participants were asked to judge whether or not the sentence was original in meaning (noveltyjudgment) and whether or not it made sense (sensicalityjudgment). When collapsed across groups, our findings demonstrate a gradual N400 modulation with N400 being maximal in response to anomalous, followed by metaphorical, and literal sentences. Between‐group comparisons revealed a mirror effect on the N400 to novel metaphorical sentences, with attenuated N400 in engineers and enhanced N400 in non‐engineers. Critically, planned comparisons demonstrated reduced N400 amplitudes to engineering novel metaphors in engineers relative to non‐engineers, pointing to an effect of prior knowledge on metaphor processing. This reduction, however, was observed in the absence of a sentence type × knowledge × group interaction. Altogether, our study provides novel evidence suggesting that prior domain knowledge may have a direct impact on creative language comprehension.