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Abstract — In this Full Research Paper, we propose a new definition of overpersistence in an engineering discipline and investigate its implications at one institution. Precisely defining overpersistence in both a conceptual and operational sense is a critical step in predicting overpersistence and identifying indicators that will allow for personalized guidance for students at risk of overpersisting. We have previously identified our population of interest as students who enroll at the institution as first-time-in-college students for at least one year, attend full time, have had six years to graduate, and have enrolled in only one degree-granting program. Within this group, we operationalized overpersistence by identifying students as overpersisters if they either (i) left the university without a degree or (ii) enrolled in the same major for six years and did not graduate. In this work, we revisit our definition of overpersistence using more recent data by reconsidering two groups of students in particular – those who spend only a short time in the discipline before leaving the institution (formerly classified as overpersisters), and those who spend a long time in the discipline but eventually switch majors (formerly excluded from the initial population). We conclude that the most appropriate definition of overpersistence at an institution with a first-year engineering program is when a student spends three or more semesters in their first discipline-specific major and does not graduate in that major within six years of matriculation to the institution. These results will be useful for researchers and practitioners seeking to identify alternative paths for success for students who are at risk of overpersisting in a major. 

The main objective of this project is to help students learn to make decisions that lead to academic success. Our first goal is to map curriculum pathways, which begins by studying overpersistence (when a student persists in a particular major but does not make timely progress toward a degree). We seek to identify curriculum-specific indicators of overpersistence and corresponding alternative paths that could lead to success. Our second goal is to improve the structure of the Decision-Making Competency Inventory (DMCI) so that it can explain student's decision-making competency in more detail and in congruence with the Self-Regulation Model of Decision-Making. This instrument will be used to map decision-making competency to academic choices and outcomes. The third goal is to develop an Academic Dashboard as a means for sharing relevant research results with students. This will allow students to have access to the strategies, information, and stories needed to make and implement adaptive decisions. This paper highlights our progress in the fifth year of the project and our plans going forward. 

This research paper discusses the process of refining and expanding the Decision-Making Competency Inventory developed by Miller and Byrnes. Byrnes is the author of the Self-Regulation Model of Decision-Making (SRMDM), which posits that that self-regulated decision-makers spend time in three phases: generation of options, evaluation of options, and learning from the results. Additionally, adaptive decision-makers are aware of moderating factors (such as stress or lack of information) and work to overcome them. A revised instrument is presented. 

This paper provides a summary activities and accomplishments of an NSF CAREER project, “Empowering Students to be Adaptive Decision-Makers.” We discuss our progress on (1) identifying indicators of poor academic fit in engineering majors; (2) examining relationships between the measures of theoretical constructs (Decision-Making Competency Inventory, DMCI) with the real-world, academic behaviors (major choice and major change); (3) revisions to the DMCI; and (4) development of the Academic Dashboard for putting students in the driver’s seat of their education. A prototype of the Academic Dashboard and its functionality are described. 

This Full Research Paper discusses ongoing work to develop a survey instrument to reliably assess undergraduate engineering student self-regulated decision-making. This work focuses on a second round of item expansion and refinement to the Decision-Making Competency Inventory (DMCI) to develop items related to learning from past decisions. The refined instrument was distributed to first-year engineering students enrolled in a large, public, land-grant institution located in the southeastern United States in the Fall of 2018. Of the approximately 1,200 students in first-year engineering courses, 883 valid surveys were randomly split into two separate samples for exploratory factor analysis (EFA) and confirmatory factor analysis (CFA). EFA results indicated a viable four-factor solution, which was explored with the CFA. The CFA results also indicated a four-factor model was appropriate. Improving this instrument will help researchers document and understand students’ decision-making skills and how they relate to observed decisions like initial choice of major or change of major. A decision-making instrument will also be valuable in evaluating the effectiveness of interventions to help students build their decision-making competency and make adaptive choices. 

The objective of this EEC project is to help students learn to make academic decisions that lead to success. The research goals are to: 1) identify curriculum-specific patterns of achievement that eventually lead to dropout and corresponding alternative paths that could lead to success; and 2) advance knowledge of self-regulation patterns and outcomes in engineering students. The education goals are to develop curricula and advising materials that help students learn how to effectively self-regulate their decision processes through contextual activities and story prompting. This poster will present current progress and future directions of the project. We will summarize accomplishments on the development of the Self-Regulated Decision-Making instrument, mapping of pathways, and development of the academic dashboard. 

This complete research paper documents how confidence in choice of intended major and self-regulated decision-making competency influence whether a student changes their intended major while participating in a compulsory first-year engineering (FYE) program. Initial major, confidence in that major choice, and self-regulated decision-making competency were documented in the Fall of 2017 for students matriculating into a FYE program. Student enrollment in a major in the Fall of 2018 was connected to this data. Retention in any engineering major and in the student’s intended major were analyzed using logistic regression. 

In this work-in-progress study, the engineering identities of students enrolled in a first-year engineering (FYE) program were surveyed to investigate whether students identify with engineering (in general or with a specific engineering major) during their first year and how differences in identities impact intent to persist in engineering. Literature suggests a strong engineering identity is linked to student retention and can positively impact a student’s trajectory within an engineering program. To investigate these interactions, a survey was distributed at a large public institution in the southeast at the beginning and end of the Fall semester. Most students reported they had decided on a specific engineering major even in the beginning of their first engineering course. While students are relatively confident in that major choice at the beginning of the year, their confidence increased by the end of the semester. Future work will invite students for interviews to elucidate understanding in how a student’s views of the engineering profession affect their FYE experience and the role the FYE curriculum has in their anticipated engineering major and themselves as engineers. 

This work-in-progress paper represents our initial approach to developing a procedure for identifying indicators of “overpersistence.” This approach is one facet of a larger NSF CAREER project, “Empowering students to be adaptive decision-makers,” to model student pathways using a ground-up curriculum-specific approach with the ultimate goal of helping students choose more strategic paths to graduation. We define “overpersisters” as those students who enter college with a specific major in mind and never sway from that choice, nor graduate in a timely manner. While persistence in and commitment to a major choice are generally viewed positively, some students become fixated on a major that may not be the best fit for them. These overpersisters often spend years in a degree program and eventually leave the institution with no degree, but potentially with a substantial amount of debt. Identifying academic events that cause these students to eventually withdraw from school is the first step towards creating better strategies through which they can persist and succeed in their undergraduate studies. The concept of overpersistence is defined relative to a particular major, so a student who tries a different major before leaving the institution would not be considered an overpersister. We selected the discipline of Mechanical Engineering as a starting point because of its large enrollment and the first author’s familiarity with the discipline. Our goal is to begin developing a procedure that will identify indicators of overpersistence and provide a foundation that will help to answer the larger research question: In Mechanical Engineering, what academic events commonly lead to late dropout without changes in academic major?