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The Multiple Institution Database for Investigating Engineering Longitudinal Development (MIDFIELD) has been developed over many years with substantial investment by the National Science Foundation through Engineering Education and Centers in the Engineering Directorate and the Division of Undergraduate Education in the Education and Human Resources Directorate. This project is focused on transitioning MIDFIELD to the American Society for Engineering Education (ASEE). The current team of MIDFIELD researchers continues to support this project including helping others learn to use the database. We have developed detailed tutorials in R that introduce MIDFIELD, key metrics, and example scenarios. We have also designed and facilitated workshops. In year 2, we offered the MIDFIELD Institute, an online three-day workshop to help researchers learn about and use MIDFIELD effectively. Attendees included graduate students, early career faculty, senior faculty, and an NSF program officer. Results from the 2023 offering of the MIDFIELD Institute are described in this paper. Dissemination and products are also summarized. 

Multiple stakeholders are interested in measuring undergraduate student success in college across academic fields. Different metrics might appeal to different stakeholders. Some metrics such as the fraction of first-time, full-time students who start in the fall who graduate within six years, the graduation rate, are federally mandated by the U.S. Department of Education, Integrated Postsecondary Education Data System (IPEDS). We argue that this calculation of graduation rate is inherently problematic because it excludes up to 60% of students who transfer into an institution, enroll part-time, or enroll in terms other than the fall. By expanding the starters definition, we propose a graduation rate definition that includes conventionally excluded students and provides information on progression in a specific program. Stickiness is an even more-inclusive alternative, measuring a program’s success in graduating all undergraduates ever enrolled in the program. In this work, programs are grouped into six academic fields: Arts and Humanities, Business, Engineering, Other, Social Sciences, and STM (Science, Technology, and Mathematics. Stickiness is the percentage of students who ever enroll in an academic field that graduate in the same field. We use the Multiple Institution Dataset for Investigating Engineering Longitudinal Development (MIDFIELD) 2023 which contains unit-record data for over 2 million individual students at 19 institutions. For the academic fields studied, Engineering has the highest graduation rate and third highest stickiness. Social Sciences and Business also have higher graduation rates and stickiness than the other fields. We also track the relative fraction of students migrating to and from each academic field. This paper continues our work to derive better metrics for understanding student success. 

Abstract We present a visual, quantitative analysis of the academic pathways of Black men and women who enroll in Electrical Engineering (EE) or Mechanical Engineering (ME) at any point during their undergraduate experience (N=4816). Our research provides evidence that more Black students choose EE than ME, in contrast to national data for all races that show that more students major in ME than EE. While more Black students initially enroll in EE overall, ME attracts a larger proportion of its Black students from other majors and retains a larger fraction. Black women are particularly persistent in ME (58%). Most Black students who leave EE or ME leave the institution without a degree. Seventy-eight percent of Black men and 65% of Black women who leave ME leave the institution without a degree. Of those leaving EE, 74% of Black men and 64% of Black women leave the institution without a degree. This examination of quantitative differences between disciplines lays a foundation for qualitative study through in depth student interviews of Black students in these majors.