There is an urgent need for young people to prepare for and pursue engineering careers. Engineering occupations comprise 20% of the science, technology, engineering, and math (STEM) jobs in the U.S. (Bureau of Labor Statistics, 2017). The average wage for STEM occupations is nearly double that of non-STEM occupations, with engineers commanding some of the highest salaries in STEM (Bureau of Labor Statistics, 2017). Moreover, engineering occupations are expected to be some of the fastest growing occupations in the U.S. over the next 10 years (Occupational Outlook Handbook, 2018); yet, there are current and projected shortages of workers in the engineering workforce so that many engineering jobs will go unfilled (Bureau of Labor Statistics, 2015) Native Americans are highly underrepresented in engineering (NSF, 2017). They comprise approximately 2% of the U.S. population (U.S. Census Bureau, 2013), but only 0.3% of engineers (Sandia National Laboratories, 2016). Thus, they are not positioned to attain a high-demand, high-growth, highly rewarding engineering job, nor to provide engineering expertise to meet the needs of their own communities or society at large. The purpose of this study was to examine factors that encourage or discourage Native American college students’ entry into engineering. Using Social Cognitive Careermore »
ASSISTments Longitudinal Data Mining Competition Special Issue: A Preface.
This special issue includes papers from some of the leading competitors in the ASSISTments Longitudinal Data Mining Competition 2017, as well as some research from non-competitors, using the same data set. In this competition, participants attempted to predict whether students would choose a career in a STEM field or not, making this prediction using a click-stream dataset from middle school students working on math assignments inside ASSISTments, an online tutoring platform. At the conclusion of the competition on December 3rd, 2017, there were 202 participants, 74 of whom submitted predictions at least once. In this special issue, some of the leading competitors present their results and what they have learned about the link between behavior in online learning and future STEM career development.
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- Journal of educational data mining
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- National Science Foundation
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POSTER. Presented at the Symposium (9/12/2019) Abstract: The Academy of Engineering Success (AcES) employs literature-based, best practices to support and retain underrepresented students in engineering through graduation with the ultimate goal of diversifying the engineering workforce. AcES was established in 2012 and has been supported via NSF S-STEM award number 1644119 since 2016. The 2016, 2017, and 2018 cohorts consist of 12, 20, and 22 students, respectively. Five S-STEM supported scholarships were awarded to the 2016 cohort, seven scholarships were awarded to students from the 2017 cohort, and six scholarships were awarded to students from the 2018 cohort. AcES students participate in a one-week summer bridge experience, a common fall semester course focused on professional development, and a common spring semester course emphasizing the role of engineers in societal development. Starting with the summer bridge experience, and continuing until graduation, students are immersed in curricular and co-curricular activities with the goals of fostering feelings of institutional inclusion and belonging in engineering, providing academic support and student success skills, and professional development. The aforementioned goals are achieved by providing (1) opportunities for faculty-student, student-student, and industry mentor-student interaction, (2) academic support, and student success education in areas such as time managementmore »
Partnering Middle School Teachers, Industry, and Academic to Bring Engineering to the Science ClassroomDespite limited success in broadening participation in engineering with rural and Appalachian youth, there remain challenges such as misunderstandings around engineering careers, misalignments with youth’s sociocultural background, and other environmental barriers. In addition, middle school science teachers may be unfamiliar with engineering or how to integrate engineering concepts into science lessons. Furthermore, teachers interested in incorporating engineering into their curriculum may not have the time or resources to do so. The result may be single interventions such as a professional development workshop for teachers or a career day for students. However, those are unlikely to cause major change or sustained interest development. To address these challenges, we have undertaken our NSF ITEST project titled, Virginia Tech Partnering with Educators and Engineers in Rural Schools (VT PEERS). Through this project, we sought to improve youth awareness of and preparation for engineering related careers and educational pathways. Utilizing regular engagement in engineering-aligned classroom activities and culturally relevant programming, we sought to spark an interest with some students. In addition, our project involves a partnership with teachers, school districts, and local industry to provide a holistic and, hopefully, sustainable influence. By engaging over time we aspired to promote sustainability beyond this NSF projectmore »
In this paper, we describe our solution to predict student STEM career choices during the 2017 ASSISTments Datamining Competition. We built a machine learning system that automatically reformats the data set, generates new features and prunes redundant ones, and performs model and feature selection. We designed the system to automatically find a model that optimizes prediction performance, yet the final model is a simple logistic regression that allows researchers to discover important features and study their effects on STEM career choices. We also compared our method to other methods, which revealed that the key to good prediction is proper feature enrichment in the beginning stage of the data analysis, while feature selection in a later stage allows a simpler final model.
Understanding the experiences of successful diverse science, technology, engineering, and math (STEM) faculty can facilitate the development of programming that counteracts barriers and weaknesses from multiple angles. The challenges that students and professionals report can be broadly identified as either identity-based or institutional. The lack of diversity in STEM fields in academia can result in narrow viewpoints, limited student diversity, and missed opportunities to address today’s societal challenges. It is clear that we must consider programming that has positively impacted successful STEM faculty in academia in order to create effective programming to recruit and retain future diverse STEM faculty. Our phenomenological study sought to add to the literature related to the role that socialization plays in preparing individuals for success in faculty roles by conducting in-depth interviews with early-career STEM faculty members in under-represented groups. The phenomena under investigation were experiences leading to early-career STEM faculty members’ successful career pathways. Seven early-career STEM faculty from multiple institutions described unique paths to their current faculty position with some commonalities, including participation in undergraduate or postdoc research and having some industry experience. The suggestions, advice, and guidance offered by the participants fell into categories that, while mirrored in the literature, serve asmore »