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1. Empowering Students to be Adaptive Decision-makers: Progress and Directions

   https://doi.org/10.18260/1-2--32205  

   Orr, Marisa K.; Martin, Baker A.; Rucks, Maya; Ehlert, Katherine M. (June 2019, 2019 ASEE Annual Conference & Exposition Proceedings)

   null (Ed.)

   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. 

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2. Development of an Academic Dashboard for Empowering Students to be Adaptive Decision Makers

   https://doi.org/10.18260/1-2--34454  

   Orr, Marisa K.; Martin, Baker A.; Spilka, Rebecca B.; Brotherton, Haleh Barmaki; Ehlert, Katherine M. (June 2020, 2020 ASEE Virtual Annual Conference Content Access Proceedings)

   null (Ed.)

   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. 

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3. Expanding and Refining a Decision-Making Competency Inventory for Undergraduate Engineering Students

   https://doi.org/10.1109/FIE43999.2019.9028391  

   Ehlert, Katherine M.; Rucks, Maya; Martin, Baker A.; Desselles, Mitzi L.; Grigg, Sarah J.; Orr, Marisa K. (October 2019, 2019 IEEE Frontiers in Education Conference (FIE))

   null (Ed.)

   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. 

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4. Students’ Decision-Making in a Product Design Process: An Observational Study

   https://doi.org/10.1115/DETC2019-98216  

   Shergadwala, Murtuza N.; Panchal, Jitesh H.; Ramani, Karthik (August 2019, ASME 2019 International Design Engineering Technical Conferences and Computers and Information in Engineering Conference)

   Abstract The objective of this study is to investigate students’ decision-making during the information gathering activities of a design process. Existing literature in engineering education has shown that students face difficulties while gathering information in various activities of a design process such as brainstorming and CAD modeling. Decision-making is an important aspect of these activities. While gathering information, students make several decisions such as what information to acquire and how to acquire that information. There lies a research gap in understanding how students make decisions while gathering information in a product design process. To address this gap, we conduct semi-structured interviews and surveys in a product design course. We analyze the students’ decision-making activities from the lens of a sequential information acquisition and decision-making (SIADM) framework. We find that the students recognize the need to acquire information about the physics and dynamics of their design artifact during the CAD modeling activity of the product design process. However, they do not acquire such information from their CAD models primarily due to the lack of the project requirements, their ability, and the time to do so. Instead, they acquire such information from the prototyping activity as their physical prototype does not satisfy their design objectives. However, the students do not get the opportunity to iterate their prototype with the given cost and time constraints. Consequently, they rely on improvising during prototyping. Based on our observations, we discuss the need for designing course project activities such that it facilitates students’ product design decisions. 

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5. Work in Progress: Developing a Procedure for Identifying Indicators of "Over-persistence"

   https://doi.org/10.18260/1-2--29151  

   Orr, Marisa K.; Anderson, Rachel K.; Rucks, Maya (June 2017, 2017 ASEE Annual Conference & Exposition Proceedings)

   null (Ed.)

   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? 

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