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1. Social responsibility views in science and engineering: An exploratory study among engineering undergraduate researchers

   Fernandez, K. ; Rivera-Jimenez, SM. ( July 2023 , American Society for Engineering Education, 2023)

   In 2017, the report Undergraduate Research Experiences for STEM Students from the National Academy of Science and Engineering and Medicine (NASEM) invited research programs to develop experiences that extend from disciplinary knowledge and skills education. This call to action asks to include social responsibility learning goals in ethical development, cultural issues in research, and the promotion of inclusive learning environments. Moreover, the Accreditation Board for Engineering and Technology (ABET), the National Academy of Engineering (NAE), and the National Science Foundation (NSF) all agree that social responsibility is a significant component of an engineer’s professional formation and must be a guiding force in their education. Social Responsibility involves the ethical obligation engineers have to society and the environment, including responsible conduct research (RCR), ethical decision-making, human safety, sustainability, pro bono work, social justice, and diversity. For this work, we explored the views of Social Responsibility in engineering students that could provide insight into developing formal and informal educational activities for future summer programs. In this exploratory multi-methods study, we investigated the following research question: What views of social responsibility are important for engineering students conducting scientific in an NSF Research Experiences for Undergraduates (REU)? The REU Site selected for this study was a college of engineering located at a major, public, comprehensive, land-grant research university. The Views of Social Responsibility of Scientists and Engineers (VSRoSE) was used to guide our research design. This validated instrument considers the following major social responsibility elements: 1) Consideration of societal consequences, 2) Protection of human welfare and safety, 3) Promotion of environmental sustainability, 4) Efforts to minimize risks, 5) Communication with the public, and 6) Service and Community engagement. Data collection was conducted at the end of their 10-week-long experience in Summer 2022 using Qualtrics. REU students were invited to complete an IRB-approved questionnaire, including collecting demographic data, the VSRoSE-validated survey, and open-ended questions. Open-ended questions were used to explore what experiences have influenced positive student views of social responsibility and provide rich information beyond the six elements of the VSRoSE instrument. The quantitative data from the VSRoSE is analyzed using SPSS. The qualitative data is analyzed by the research team using an inductive coding approach. In this coding process, the researchers derive codes from the data allowing the narrative or theory to emerge from the raw data itself, which is great for exploratory research. The results from this exploratory study will help to strategically initiate a formal and informal research education curriculum at the selected university. In addition, the results may serve as a way for REU administrators and faculty to create metrics of impact on their research activities regarding social responsibility. Finally, this work intends to provoke the ethics and research community to have a deeper conversation about the needs and strategies to educate this unique population of students. 

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2. Summer Bridge Programming for Incoming First-Year Students at Three Public Urban Research Universities

   Howland Cummings, M. ; Darbeheshti, M. ; Ivey, S. ; Stewart, C. ; Russomanno, D. ; King, D. ; Goodman, K. ; Campbell, J. ; Altman, T. ; Jacobson, M. ; et al ( August 2022 , ASEE Annual Conference proceedings)

   This Complete Evidence-based Practice paper will describe how three different public urban research universities designed, executed, and iterated Summer Bridge programming for a subset of incoming first-year engineering students over the course of three consecutive years. There were commonalities between each institution’s Summer Bridge, as well as unique aspects catering to the specific needs and structures of each institution. Both these commonalities and unique aspects will be discussed, in addition to the processes of iteration and improvement, target student populations, and reported student outcomes. Finally, recommendations for other institutions seeking to launch or refine similar programming will be shared. Summer Bridge programming at each of the three institutions shared certain communalities. Mostly notably, each of the three institutions developed its Summer Bridge as an additional way to provide support for students receiving an NSF S-STEM scholarship. The purpose of each Summer Bridge was to build community among these students, prepare them for the academic rigor of first-year engineering curriculum, and edify their STEM identity and sense of belonging. Each Summer Bridge was a 3-5 day experience held in the week immediately prior to the start of the Fall semester. In addition to these communalities, each Summer Bridge also had its own unique features. At the first institution, Summer Bridge is focused on increasing college readiness through the transition from summer break into impending coursework. This institution’s Summer Bridge includes STEM special-interest presentations (such as biomedical or electrical engineering) and other development activities (such as communication and growth mindset workshops). Additionally, this institution’s Summer Bridge continues into the fall semester via a 1-credit hour First Year Seminar class, which builds and reinforces student networking and community beyond the summer experience. At the second institution, all students receiving the NSF S-STEM scholarship (not only those who are first-year students) participate in Summer Bridge. This means that S-STEM scholars at this institution participate in Summer Bridge multiple years in a row. Relatedly, after the first year, Summer Bridge transitioned to a student-led and student-delivered program, affording sophomore and junior students leadership opportunities, which not only serve as marketable experience after graduation, but also further builds their sense of STEM identity and belonging. At the third institution, a special focus was given to building community. This was achieved through several means. First, each day of Summer Bridge included a unique team-oriented design challenge where students got to work together and know each other within an engineering context, also reinforcing their STEM identities. Second, students at this institution’s Summer Bridge met their future instructors in an informal, conversational, lunch setting; many students reported this was one of their favorite aspects of Summer Bridge. Finally, Summer Bridge facilitated a first connect between incoming first-year students and their peer mentors (sophomore and junior students also receiving the NSF S-STEM scholarship), with whom they would meet regularly throughout the following fall and spring semesters. Each of the three institutions employed processes of iteration and improvement for their Summer Bridge programming over the course of two or three consecutive years. Through each version and iteration of Summer Bridge, positive student outcomes are demonstrated, including direct student feedback indicating built community among students and the perception that their time spent during Summer Bridge was valuable. Based on the experiences of these three institutions, as well as research on other institutions’ Summer Bridge programming, recommendations for those seeking to launch or refine similar Summer Bridge programming will also be shared. 

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3. Engagement in Practice: Lessons Learned Partnering with Science Educators and Local Engineers in Rural Schools

   Lesko, H. L. ; Grohs, J. R. ; Matusovich, H. M. ; Kirk, G. R. ; Carrico, C. ; van Montfrans, V. ; Gillen, A. L. ; Paradise, T. ; Blackowski, S. A. ; Baum, L. M. ( June 2018 , ASEE Annual Conference proceedings)

   Our NSF-funded ITEST project focuses on the collaborative design, implementation, and study of recurrent hands-on engineering activities with middle school youth in three rural communities in or near Appalachia. To achieve this aim, our team of faculty and graduate students partner with school educators and industry experts embedded in students’ local communities to collectively develop curriculum to aim at teacher-identified science standard and facilitate regular in-class interventions throughout the academic year. Leveraging local expertise is especially critical in this project because family pressures, cultural milieu, and preference for local, stable jobs play considerable roles in how Appalachian youth choose possible careers. Our partner communities have voluntarily opted to participate with us in a shared implementation-research program and as our project unfolds we are responsive to community-identified needs and preferences while maintaining the research program’s integrity. Our primary focus has been working to incorporate hands-on activities into science classrooms aimed at state science standards in recognition of the demands placed on teachers to align classroom time with state standards and associated standardized achievement tests. Our focus on serving diverse communities while being attentive to relevant research such as the preference for local, stable jobs attention to cultural relevance led us to reach out to advanced manufacturing facilities based in the target communities in order to enhance the connection students and teachers feel to local engineers. Each manufacturer has committed to designating several employees (engineers) to co-facilitate interventions six times each academic year. Launching our project has involved coordination across stakeholder groups to understand distinct values, goals, strengths and needs. In the first academic year, we are working with 9 different 6th grade science teachers across 7 schools in 3 counties. Co-facilitating in the classroom are representatives from our project team, graduate student volunteers from across the college of engineering, and volunteering engineers from our three industry partners. Developing this multi-stakeholder partnership has involved discussions and approvals across both school systems (e.g., superintendents, STEM coordinators, teachers) and our industry partners (e.g., managers, HR staff, volunteering engineers). The aim of this engagement-in-practice paper is to explore our lessons learned in navigating the day-to-day challenges of (1) developing and facilitating curriculum at the intersection of science standards, hands-on activities, cultural relevancy, and engineering thinking, (2) collaborating with volunteers from our industry partners and within our own college of engineering in order to deliver content in every science class of our 9 6th grade teachers one full school day/month, and (3) adapting to emergent needs that arise due to school and division differences (e.g., logistics of scheduling and curriculum pacing), community differences across our three counties (e.g., available resources in schools), and partner constraints. 

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4. Partnering to Develop a Coordinated Engineering Education Program Across Schools, Museum Field Trips, and Afterschool Programs

   Harlow, D. ( January 2020 , Connected science learning)

   Engineering Explorations are curriculum modules that engage children across contexts in learning about science and engineering. We used them to leverage multiple education sectors (K–12 schools, museums, higher education, and afterschool programs) across a community to provide engineering learning experiences for youth, while increasing local teachers’ capacity to deliver high-quality engineering learning opportunities that align with school standards. Focusing on multiple partners that serve youth in the same community provides opportunities for long-term collaborations and programs developed in response to local needs. In a significant shift from earlier sets of standards, the Next Generation Science Standards include engineering design, with the goal of providing students with a foundation “to better engage in and aspire to solve the major societal and environmental challenges they will face in decades ahead” (NGSS Lead States 2013, Appendix I). Including engineering in K–12 standards is a positive step forward in introducing students to engineering; however, K–12 teachers are not prepared to facilitate high-quality engineering activities. Research has consistently shown that elementary teachers are not confident in teaching science, especially physical science, and generally have little knowledge of engineering (Trygstad 2013). K–12 teachers, therefore, will need support. Our goal was to create a program that took advantage of the varied resources across a STEM (science, technology, engineering, and math) education ecosystem to support engineering instruction for youth across multiple contexts, while building the capacity of educators and meeting the needs of each organization. Specifically, we developed mutually reinforcing classroom and field trip activities to improve student learning and a curriculum to improve teacher learning. This challenging task required expertise in school-based standards, engineering education, informal education, teacher professional development, and classroom and museum contexts. 

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5. Intelligence Augmentation for Collaborative Learning

   Roschelle, Jeremy ( January 2021 , HCI International)

   null (Ed.)

   Today’s classrooms are remarkably different from those of yesteryear. In place of individual students responding to the teacher from neat rows of desks, one more typically finds students working in groups on projects, with a teacher circulating among groups. AI applications in learning have been slow to catch up, with most available technologies focusing on personalizing or adapting instruction to learners as isolated individuals. Meanwhile, an established science of Computer Supported Collaborative Learning has come to prominence, with clear implications for how collaborative learning could best be supported. In this contribution, I will consider how intelligence augmentation could evolve to support collaborative learning as well as three signature challenges of this work that could drive AI forward. In conceptualizing collaborative learning, Kirschner and Erkens (2013) provide a useful 3x3 framework in which there are three aspects of learning (cognitive, social and motivational), three levels (community, group/team, and individual) and three kinds of pedagogical supports (discourse-oriented, representation-oriented, and process-oriented). As they engage in this multiply complex space, teachers and learners are both learning to collaborate and collaborating to learn. Further, questions of equity arise as we consider who is able to participate and in which ways. Overall, this analysis helps us see the complexity of today’s classrooms and within this complexity, the opportunities for augmentation or “assistance to become important and even essential. An overarching design concept has emerged in the past 5 years in response to this complexity, the idea of intelligent augmentation for “orchestrating” classrooms (Dillenbourg, et al, 2013). As a metaphor, orchestration can suggest the need for a coordinated performance among many agents who are each playing different roles or voicing different ideas. Practically speaking, orchestration suggests that “intelligence augmentation” could help many smaller things go well, and in doing so, could enable the overall intention of the learning experience to succeed. Those smaller things could include helping the teacher stay aware of students or groups who need attention, supporting formation of groups or transitions from one activity to the next, facilitating productive social interactions in groups, suggesting learning resources that would support teamwork, and more. A recent panel of AI experts identified orchestration as an overarching concept that is an important focus for near-term research and development for intelligence augmentation (Roschelle, Lester & Fusco, 2020). Tackling this challenging area of collaborative learning could also be beneficial for advancing AI technologies overall. Building AI agents that better understand the social context of human activities has broad importance, as does designing AI agents that can appropriately interact within teamwork. Collaborative learning has trajectory over time, and designing AI systems that support teams not just with a short term recommendation or suggestion but in long-term developmental processes is important. Further, classrooms that are engaged in collaborative learning could become very interesting hybrid environments, with multiple human and AI agents present at once and addressing dual outcome goals of learning to collaborate and collaborating to learn; addressing a hybrid environment like this could lead to developing AI systems that more robustly help many types of realistic human activity. In conclusion, the opportunity to make a societal impact by attending to collaborative learning, the availability of growing science of computer-supported collaborative learning and the need to push new boundaries in AI together suggest collaborative learning as a challenge worth tackling in coming years. 

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