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This full research paper documents assessment definitions from engineering faculty members, mainly from Research 1 universities. Assessments are essential components of the engineering learning environment, and how engineering faculty make decisions about assessments in their classroom is a relatively understudied topic in engineering education research. Exploring how engineering faculty think and implement assessments through the mental model framework can help address this research gap. The research documented in this paper focuses on analyzing data from an informational questionnaire that is part of a larger study to understand how the participants define assessments through methods inspired by mixed method strategies. These strategies include descriptive statistics on demographic findings and Natural Language Processing (NLP) and coding on the open-ended response question asking the participants to define assessments, which yielded cluster themes that characterize the definitions. Findings show that while many participants defined assessments in relation to measuring student learning, other substantial aspects include benchmarking, assessing student ability and competence, and formal evaluation for quality. These findings serve as foundational knowledge toward deeper exploration and understanding of assessment mental models of engineering faculty that can begin to address the aforementioned research gap on faculty assessment decisions in classrooms. 

This paper reports on a project funded through the Engineering Education and Centers (EEC) Division of the National Science Foundation. Since 2010, EEC has funded more than 500 proposals totaling over $150 million through engineering education research (EER) programs such as Research in Engineering Education (REE) and Research in the Formation of Engineers (RFE), to enhance understanding and improve practice. The resulting archive of robust qualitative and quantitative data represents a vast untapped potential to exponentially increase the impact of EEC funding and transform engineering education. But tapping this potential has thus far been an intractable problem, despite ongoing calls for data sharing by public funders of research. Changing the paradigm of single-use data collection requires actionable, proven practices for effective, ethical data sharing, coupled with sufficient incentives to both share and use existing data. To that end, this project draws together a team of experts to overcome substantial obstacles in qualitative data sharing by building a framework to guide secondary analysis in engineering education research (EER), and to test this framework using pioneering data sets. Herein, we report on accomplishments within the first year of the project during which time we gathered a group of 13 expert qualitative researchers to engage in the first of a series of working meetings intended to meet our project goals. We came into this first workshop with a potentially limiting definition of secondary data analysis and the idea that people would want to share existing datasets if we could find ways around anticipated hurdles. However, the workshop yielded a broader definition of secondary data analysis and revealed a stronger interest in creating new datasets designed for sharing rather than sharing existing datasets. Thus, we have reconceived our second phase as one that is a cohesive effort based on an inclusive “open cohort model” to pilot projects related to secondary data analysis. 

In this Lessons Learned paper, we describe the implementation of an on-campus workshop focused on supporting faculty as they develop metacognitive interventions for their educational contexts. This on-campus workshop at Duke University included faculty from engineering as well as other faculty from campus and was developed and implemented by members of the Skillful Learning Institute Team. First, we describe the purpose and intent of the workshop by the host institution (Duke University) and the workshop development team (Skillful-Learning Institute Team). We then provide the workshop overview across the two day period, including a description of instruction provided and structured breakout sessions. Next, we provide a lessons learned section from the perspectives of the host institution and the workshop developers. Finally, we offer insights into how those lessons learned are being incorporated into the development of future workshops. By providing the two perspectives, our lessons learned should help those who invite speakers in for faculty development and those who are creating faculty development activities. 

Studies on graduate education have shown that underrepresented minorities finish PhDs in engineering at lesser rates and longer timeframes than their majority counterparts. While multiple interventions have been designed for students considering their decision to apply for graduate school or students completing their doctoral journey, few focus on the transition into those doctoral programs. To prepare minoritized doctoral students for this transition to the Ph. D., we developed and researched the Rising Doctoral Institute (RDI). The RDI is a four-day summer workshop for incoming doctoral students who identify as underrepresented in engineering and intend to begin graduate school in the Fall semester. This paper aims to discuss the process through which we developed the RDI and our initial research findings. We conclude with our plan to disseminate these workshops across multiple US institutions using a change-theory informed dissemination model. 

Barriers to broadening participation in engineering to rural and Appalachian youth include misalignment with family and community values, lack of opportunities, and community misperceptions of engineering. While single interventions are unlikely to stimulate change in these areas, more sustainable interventions that are co-designed with local relevance appear promising. Through our NSF ITEST project, we test the waters of this intervention model through partnership with school systems and engineering industry to implement a series of engineering-themed, standards-aligned lessons for the middle school science classroom. Our mixed methods approach includes collection of interview and survey data from administrators, teachers, engineers, and university affiliates as well as observation and student data from the classroom. We have utilized theory from learning science and organizational collaboration to structure and inform our analysis and explore the impact of our project. The research is guided by the following questions: RQ 1: How do participants conceptualize engineering careers? How and why do such perceptions shift throughout the project? RQ 2: What elements of the targeted intervention affect student motivation towards engineering careers specifically with regard to developing competencies and ability beliefs regarding engineering? RQ 3: How can strategic collaboration between K12 and industry promote a shift in teacher’s conceptions of engineers and increased self-efficacy in building and delivering engineering curriculum? RQ 4: How do stakeholder characteristics, perceptions, and dynamics affect the likelihood of sustainability in strategic collaborations between K12 and industry stakeholders? How do prevailing institutional and collaborative conditions mediate sustainability? In year one, we involved nine 6th grade teachers, three engineering companies, and over 500 students. In year two, we expanded to include 7th grade teachers in our partner schools and the new students moving up to 6th grade. Lessons aligned with students' everyday experiences and connected to industry. For example, students created bouncy balls and tested their effectiveness on materials produced from partner manufacturing facilities. From preliminary analysis of data collected in the first two years of the project (e.g, the Draw an Engineer Test and teacher interviews), we have begun to see evidence of positive student and teacher impact. Additionally, our application of collaborative theory to the investigation of stakeholder perceptions of the project has revealed implications for partnering with school systems and engineering industry. For example, key individuals at each organization may serve as important conduits for program communication and collaborative work. 

This research paper describes how engineering juniors and seniors perceive the influence of socializers on their post-graduation career planning. Grounded in Expectancy x Value Theory (EVT), this qualitative investigation is part of a sequential mixed-methods study that included two survey phases and an interview phase. An exploratory analysis of 72 interview excerpts revealed four dominant socializer groups, namely, family, peers, university related individuals, and work related individuals, as well as three distinct areas of socializer influence: thinking about specific jobs, job exploration in general, and choosing whether to pursue further education. A closer look showed that while parents, peers, professors, and supervisors were all important to students’ career plans, the type of influence each had tended to differ. In-depth examples of socializer influence and their impact on students’ job related decisions are shared in this paper. The results are insightful for researchers, university and industry stakeholders, and students. 

This paper provides an example of how an NSF-funded project, Professional Engineering Pathways Study [EEC-1360665, 1360956, and 1360958] or PEPS has incorporated a community of practice approach to disseminate the use of evidence-based decisions to design activities that assist engineering students in making career choices. The paper will discuss the elements of a community of practice, how it has been used in PEPS, and how other projects might use this approach to bring about other kinds of change. Key words: Community of practice, educational reform