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In Fall 2018 our small liberal arts university with a new engineering program was awarded an NSF S-STEM grant. Now with three cohorts admitted to the program, we present the retention data of students that have participated in the program versus a comparable control data set from the School of Engineering. The students under study range from those currently in their second year of undergraduate engineering to those that have graduated in the past two years. Thus, the data include those students that have both graduated and those that continue to seek a baccalaureate degree. In the analysis, the two comparable data sets are broken into demographics for comparison where appropriate, including race, ethnicity, GPA, starting university math course, and gender. We investigate the degree to which elements of the S-STEM program (faculty and peer mentoring, career services, and professional development trainings) yield higher retention data for the S-STEM group. With the analysis, we explore whether any of these demographic factors moderate the relationship between program participation and retention. 

A recent S-STEM award has allowed the engineering program in a rural, liberal arts institution to offer a need-based scholarship program for its students. The engineering program has a number of veteran, underrepresented minority, transfer, and nontraditional students. Many students are also first-generation college students. The institution and engineering program matriculate a number of under-served populations, students who may have needs that are not well understood in the typical engineering education literature. The scholarship program and its associated mentoring and activities will assist workforce development and will also incorporate a number of research avenues to better understand and serve the student population in this unique setting. To apply for the program, students must fill out an application with four 250 – 500 word essay responses relating to their academic progress, perceived barriers to degree completion, and how this award would help them to complete their degree. This study continues work using personas, a method used in human-centered design. Using the first round of scholarship application essays as a source, three personas were developed, one successful applicant, one unsuccessful applicant, and one general applicant. Personas are detailed profiles of a fake person who could reasonably be in each category of interest. In human-centered design, personas are detailed descriptions of likely clients or end-users, developed to help the engineers focus on who they might be designing for. The profiles developed in this study were used to gain insight into which students were likely to choose to apply and which students may be missing out on this opportunity. It is time for another round of applications for this grant and the use of personas will continue and expand as part of this study. Before reviewing applications, the committee will create two personas as ideal candidates instead of developing a standardized rubric. Subsequently, three personas will be developed from the Fall 2020 applications, one for all applicants, one for successful applicants, and one for unsuccessful applicants. These personas will then be compared to the personas created by the application review committee and the personas created from the Fall 2018 applicants. Similarities and differences across the persona groups will be explored to determine whether the applicants are what the reviewers expected and whether the pool of applicants has evolved or remained mostly the same throughout the scholarship program. Review committee members will also be interviewed in a focus group setting to discuss their experiences using common personas rather than standardized rubrics in the application review process. At this time, the applications are not yet due and the analysis has not yet begun. Initial interest for the grant has been strong and we anticipate at least thirty applications for the nineteen available grants. Results presented will include the student profiles and faculty experiences with the use of personas as a metric for reviewing student applications. 

This study focuses on a new engineering program in a rural, liberal arts university. The engineering program has a number of veteran, underrepresented minority, transfer, and nontraditional students. Many students are also first-generation college students. The institution and engineering program matriculate a number of under-served populations, students who may have needs that are not well understood in the typical engineering education literature. Due to the unique nature of this program, exploring the social capital networks of the students in the first four years of the program will offer insight into the students in this context. This study will use Lin’s model of social capital as a framework. Social capital can be defined as the resources that are gained from relationships, or “it’s not what you know, it’s who you know”. The knowledge that is found within a student’s social network are a form of capital. Students must not only have people within their network that provide cultural, economic, and human capital, but also be able to access those resources and be able to purposely activate those resources. The instrument used in this survey is based on Martin’s work with the Name and Resource Generator as adapted by Boone in work focusing on first-generation college students. In this instrument, students are asked to name up to eight people who have had an influence on their engineering-related decisions. They are asked to provide some background on each person, including their relationship, what they know of the person’s career and educational background, and how long they have known this person. Students may offer as little as one or as many as eight influencers. Additionally, students are asked to list relationships of people who have provided them with a number of resources related to engineering knowledge, activities, and advice. The department and especially the first-year curricular requirements and extracurricular offerings have been designed using a community of practice model. It is hoped that as part of the focus on creating this community within engineering that all students’ networks will expand to include faculty, peers, and others within the engineering community of practice. Faculty and peers within the school of engineering will be identified and will be an additional focus of this study. At this time, analysis has begun on a subset of the survey responses. Initial results are consistent with social capital literature, finding that first-generation college students are more likely to have smaller networks focusing on family, with one student in the study listing a single person as having an impact on their engineering decisions. Most students have also listed at least one faculty or peer at the university as well. Results presented will include typical network analysis to understand how the students in this unique context compare to published studies. We will also generate map of student networks focusing on department-specific connections including peers and faculty. Additional results of interest include discrepancies between the interview and the follow-up survey. 

A small liberal arts university in the south received an S-STEM grant in 2018 focused on the School of Engineering. Important factors in the program's success are applicant recruitment and cohort building. Our recruiting efforts targeted at-risk students who entered the University with less math preparation. In the first year, we met our goals for recruitment in terms of overall applicant numbers but not in terms of the number of at-risk students. In the second year, we had fewer overall applicants, but the proportion that were at-risk was higher. In the area of cohort building, feedback from the scholarship recipients indicated our programming did not build community or provide opportunities for them to meet students in the other years. In that first year, the project team organized and led professional development and social events. The social events had little structure, and attendance was poor. In the second year, we hired a consultant to provide sessions for students on topics such as value identification, gratitude, and mindfulness. The sessions had positive student feedback. In addition to providing professional development skills, the interactivity of the sessions helped build a stronger cohort. This paper reviews the lessons learned from the first two years and reports on the results of the third-year program implementation. 

A recent S-STEM award has allowed the engineering program in a rural, liberal arts institution to offer a need-based scholarship program for its students. The engineering program has a number of veteran, underrepresented minority, transfer, and nontraditional students. Many students are also first-generation college students. The institution and engineering program matriculate a number of under-served populations, students who may have needs that are not well understood in the typical engineering education literature. The scholarship program and its associated mentoring and activities will assist workforce development and will also incorporate a number of research avenues to better understand and serve the student population in this unique setting. To apply for the program, students must fill out an application with four 250 – 500 word essay responses relating to their academic progress, perceived barriers to degree completion, and how this award would help them to complete their degree. This initial study seeks to analyze the student applications to explore which students are applying for the new scholarship program and which students are successful in their applications. Responses to the application questions will be analyzed to develop an archetypical applicant, an archetypical successful applicant, and an archetypical unsuccessful applicant. Similar to the IDEO method of creating a specific client to design for, these profiles will not encompass all possible student responses; not all students who would be grouped with the archetype would see themselves in the archetype. Rather, these archetypes will help us to define students that we can use as a model when we are developing programs for the students in the scholarship program and the student body as a whole. These profiles will be presented and used to generate an understanding of which students are likely to choose to apply and which students may be missing out on this opportunity. At this time, the applications are not yet due and the analysis has not yet begun. Initial interest for the grant has been strong and we anticipate at least thirty applications for the nineteen available grants. Results presented will include the three student profiles as well as a report of the perceived barriers to graduation as reported by applicants in their application materials.