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Abstract As generative artificial intelligence (GenAI) tools such as ChatGPT become more capable and accessible, their use in educational settings is likely to grow. However, the academic community lacks a comprehensive understanding of the perceptions and attitudes of students and instructors toward these new tools. In the Fall 2023 semester, we surveyed 982 students and 76 faculty at a large public university in the United States, focusing on topics such as perceived ease of use, ethical concerns, the impact of GenAI on learning, and differences in responses by role, gender, and discipline. We found that students and faculty did not differ significantly in their attitudes toward GenAI in higher education, except regarding ease of use, hedonic motivation, habit, and interest in exploring new technologies. Students and instructors also used GenAI for coursework or teaching at similar rates, although regular use of these tools was still low across both groups. Among students, we found significant differences in attitudes between males in STEM majors and females in non-STEM majors. These findings underscore the importance of considering demographic and disciplinary diversity when developing policies and practices for integrating GenAI in educational contexts, as GenAI may influence learning outcomes differently across various groups of students. This study contributes to the broader understanding of how GenAI can be leveraged in higher education while highlighting potential areas of inequality that need to be addressed as these tools become more widely used. 

This Work-In-Progress research paper presents preliminary results and next steps of a study that aims to identify institutional data and resources that instructors find helpful in facilitating learning in large foundational engineering courses. The work is motivated by resource-driven compromises made in response to increasing engineering student populations. One such compromise is teaching some courses (usually foundational courses taken by students across multiple disciplines) in large sections, despite research suggesting that large class environments may correspond with unfavorable student learning experiences. Examples of courses often taught in large class environments are mathematics, physics, and mechanics. We are currently working with a cohort of instructors of foundational engineering courses as part of an NSF Institutional Transformation project. We have collected qualitative data through semi-structured interviews to explore the following research question: What data and/or resources do STEM faculty teaching large foundational classes for undergraduate engineering identify as being useful to enhance students' experiences and outcomes a) within the classes that they teach, and b) across the multiple large foundational engineering classes taken by students? Our inquiry and analysis are guided by Lattuca and Stark's Academic Plan Model. Preliminary analysis indicated that instructors would like more opportunities to interact and collaborate with instructors from other departments. These results will inform activities for our Large Foundational Courses Summit scheduled for Summer 2018 as part of the project. 

Abstract BackgroundCalls to improve learning in science, technology, engineering, and mathematics (STEM), and particularly engineering, present significant challenges for school systems. Partnerships among engineering industry, universities, and school systems to support learning appear promising, but current work is limited in its conclusions because it lacks a strong connection to theoretical work in interorganizational collaboration. Purpose/HypothesisThis study aims to reflect more critically on the process of how organizations build relationships to address the following research question: In a public–private partnership to integrate engineering into middle school science curriculum, how do stakeholder characterizations of the collaborative process align with existing frameworks of interorganizational collaboration? Design/MethodThis qualitative, embedded multiple case study considered in‐depth pre‐ and post‐year interviews with teachers, administrators, industry, and university personnel during the first year of the Partnering with Educators and Engineers in Rural Schools (PEERS) program. Transcripts were analyzed using a framework of interorganizational collaboration operationalized for our context. ResultsResults provide insights into stakeholder perceptions of collaborative processes in the first year of the PEERS program across dimensions of collaboration. These dimensions mapped to three central discussion points with relevance for school–university–industry partnerships: school collaboration as an emergent and negotiated process, tension in collaborating across organizations, and fair share in collaborating toward a social goal. ConclusionsTaking a macro‐level look at the collaborative processes involved enabled us to develop implications for collaborative stakeholders to be intentional about designing for future success. By systematically applying a framework of collaboration and capitalizing on the rich situational findings possible through a qualitative approach, we shift our understanding of collaborative processes in school–university–industry partnerships for engineering education and contribute to the development of collaboration theory. 

his project is supported by an NSF BPE grant. Career choices, such as engineering, are influenced by a number of factors including personal interest, ability, competence beliefs, prior work-related experience, and financial and social supports. However, financial and social support, a particularly significant factor for rural students’ career decisions, is often overlooked in the literature exploring career choice. Moreover, little work has explored how communities serve as key influencers for supporting or promoting engineering as a career choice. Therefore, the goal of this study is to explore the ways in which communities provide support to students deciding to pursue engineering as a college major. To better understand how students from selected rural area high schools choose engineering as a major, we conducted focus group discussions consisting of 4-6 students each from selected schools to talk collectively about their high school experiences and their choice to major in engineering. Choosing focus group participants from different schools enabled us to elicit tacit perceptions and beliefs that may not be evident when students from the same community talk with one another. That is, as students share their experiences across schools, they may recognize differences in their experiences that, though otherwise unconscious or unacknowledged, proved significant in their choice of college and major. We expect that certain community programs and the individuals involved will have some influence on students’ decisions to study engineering at [University Name]. We anticipate that the results will yield two key outcomes: 1. A holistic understanding of the communities that effectively support and encourage engineering major choice for rural students. 2. Locally driven, contextually relevant recommendations for policies and programs that would better enable economically disadvantaged, rural schools in southwestern Virginia to support engineering as a career choice for high school students. By understanding the ways some economically-disadvantaged rural communities support engineering as a career choice and linking a broad spectrum of rural communities together around this issue, this project will broaden participation in engineering by increasing support for students from these areas. By shifting our focus from students to communities, this research broadens our understanding of career choice by capturing the perspectives of community members (including not only school personnel, but also community leaders, students’ families, business owners and others) who often play a key role in students’ decisions, particularly in rural communities. Our research will bring these voices into the conversation to help scholars learn from and respond to these essential community perspectives. In doing so, we will provide a more nuanced model of engineering career choice that can then be explored in other rural contexts. This work thus contributes to the research on career choice, rural education, and engineering education. © 2018 American Society for Engineering Education 

Abstract BackgroundDetermining the root causes of persistent underrepresentation of different subpopulations in engineering remains a continued challenge. Because place‐based variation of resource distribution is not random and because school and community contexts influence high school outcomes, considering variation across those contexts should be paramount in broadening participation research. Purpose/HypothesisThis study takes a macroscopic systems view of engineering enrollments to understand variation across one state's public high school rates of engineering matriculation. Design/MethodThis study uses a dataset from the Virginia Longitudinal Data System that includes all students who completed high school from a Virginia public school from 2007 to 2014 (N= 685,429). We explore geographic variation in four‐year undergraduate engineering enrollment as a function of gender, race/ethnicity, and economically disadvantaged status. Additionally, we investigate the relationship between characteristics of the high school and community contexts and undergraduate engineering enrollment across Virginia's high schools using regression analysis. ResultsOur findings illuminate inequality in enrollment in engineering programs at four‐year institutions across high schools by gender, race, and socioeconomic status (and the intersections among those demographics). Different high schools have different engineering enrollment rates among students who attend four‐year postsecondary institutions. We show strong associations between high schools' engineering enrollment rates and four‐year institution enrollment rates as well as moderate associations for high schools' community socioeconomic status. ConclusionsStrong systemic forces need to be overcome to broaden participation in engineering. We demonstrate the insights that state longitudinal data systems can illuminate in engineering education research.