Conference Session

Evaluation and Assessment for Engineering Leadership Programs

Collection

2025 ASEE Annual Conference & Exposition

Authors

Pamela Edith Campos Valles, University of Texas at El Paso; Stephanie Jimenez, University of Texas at El Paso; Lori Houghtalen, University of Texas at El Paso; Meagan R. Kendall, University of Texas at El Paso

Tagged Divisions

Engineering Leadership Development Division (LEAD)

Paper ID #45683Using Q-Sort to Prioritize Concepts for Inclusion in an Engineering LeadershipDevelopment Assessment Instrument: A Work in ProgressPamela Edith Campos Valles, University of Texas at El Paso Pamela E. Campos Valles is a master’s research assistant in the Department of Engineering Education and Leadership at The University of Texas at El Paso. She is pursuing a MS of Engineering with concentrations in biomedical engineering and engineering education. Her research focuses on the development of an assessment instrument to evaluate engineering leadership development, drawing on the perspectives of engineering

Conference Session

First-Year and Experiential Learning for Women Engineers

Collection

2025 ASEE Annual Conference & Exposition

Authors

Lorne S. Joseph, Rutgers, The State University of New Jersey; Lydia Q Prendergast, Rutgers, The State University of New Jersey

Tagged Topics

Diversity

Tagged Divisions

Women in Engineering Division (WIED)

Conference Session

Student Success and Support Mechanisms in Engineering Education

Collection

2025 ASEE Annual Conference & Exposition

Authors

James Finn Morton, University of Georgia; Taiwo Raphael Feyijimi, University of Georgia; Sarah Jane Bork, University of Georgia

Tagged Topics

Diversity

Tagged Divisions

Student Division (STDT)

engineering coursework can be in high school [3]. Therefore,it is important to consider why aspects of engineering may resonate with this specific populationcompared to others.The following sections will first detail the framework we used to guide our study. We then detailthe Q-methodology, the method used in this study. We will present our current progress(development of Q-statements) before discussing our conclusions and future work. We will thenend with a self-reflection of the first author’s experience doing this work.Guiding Theoretical FrameworkThis work was guided by Eccle’s Expectancy Value’s Theory and Subjective Task Values (EVT-STV). EVT provides a robust framework for analyzing how students’ beliefs about their abilityto succeed

Conference Session

ME Division 14: From M&Ms to Air Quality: Engaging Students in Energy and the Environment

Collection

2025 ASEE Annual Conference & Exposition

Authors

Haifa Salman El-Sadi, Wentworth Institute of Technology; John Peter Voccio; ADAM PAYNE, Wentworth Institute of Technology

Tagged Divisions

Mechanical Engineering Division (MECH)

helping the students understand the concept of climate change from both a theoretical and practical perspective, allowing them to make a better, more-informed judgement. Table 3. Summary of 17 third-year student responses. MECH2250, 23 enrollments Third year student responseQuestions Yes May be NoQ#1: Do you thinkglobal warming will be NA 58% 42%solved in your lifetime?Q#2: Is carbon dioxidethe only greenhouse NA 5% 92%gas?Q#3: Do allgreenhouse gases 25% 17

Conference Session

Tech Session 4: Embedding Engineering for One Planet (EOP) Framework in Engineering Education

Collection

2025 ASEE Annual Conference & Exposition

Authors

Pranshoo Solanki P.E., Illinois State University; Ali Barenji, Illinois State University; Matthew Aldeman, Illinois State University

Tagged Divisions

Environmental Engineering & Sustainability Division (ENVIRON)

and improvements in these areasafter the completion of the redesigned curriculum. This before-and-after approach allowed for adirect comparison of students’ progress, providing insights into the effectiveness of integratingsustainability concepts into the course [[8].The specific survey questions are as follows:1. General Understanding of SustainabilityQ-1 I understand the concept of sustainability in my field of study (engineering technologyand/or construction management).Q-2 To what extent do you agree that sustainability should be one of the core focuses on yourfield of study?2. Environmental SustainabilityQ-3 I understand the concept of life cycle assessment (LCA) in evaluating the sustainability ofproducts.Q-4 To what extent do you agree

Conference Session

Curriculum Development and Pedagogical Innovations

Collection

2025 ASEE Annual Conference & Exposition

Authors

Sonia Bansal, Duke University; Kat M Lazar, Duke University; Jaron Shoemaker, Rensselaer Polytechnic Institute; Elizabeth Feeney, Duke University

Tagged Divisions

Biomedical Engineering Division (BED)

(few optional questions, zero points).Table 1: Points and number of questions on each lab protocol in total and by type of question. Hypotheses and Data acquisition Figures and Total Mechanisms and observations statistics Points (questions) Points (questions) Points (questions) Points (questions) Lab 1 30 (20 Q) 12 (7 Q) 12 (10 Q) 6 (3 Q) Lab 2 20 (12 Q) 10 (5 Q) 4 (4 Q) 6 (3 Q) Lab 3 10 (10 Q) 5 (5 Q) 3 (3 Q) 2 (2 Q) Lab 4 0

Conference Session

Mechanical Engineering Division (MECH) Poster Session

Collection

2025 ASEE Annual Conference & Exposition

Authors

Sean Stephen Tolman, Utah Valley University; Matthew J Jensen, Utah Valley University; Israd Hakim Jaafar, Utah Valley University; Amanda Bordelon, Utah Valley University; Bennington J Willardson, Utah Valley University

Tagged Topics

Diversity

Tagged Divisions

Mechanical Engineering Division (MECH)

:______________________________ Date:____________________Annual Student Survey: Annual NSF CAM Scholarship Recipient SurveyQ.1 Hello, this is__________ from {Removed} University's Office of Institutional Research. May I speak with [ANSWER TO Q. 36]?Q.2 We are calling students who have participated in XXU’s CAM Scholarship program which was funded by the National Science Foundation’s Scholarships in STEM program. As a reminder of the Informed Consent Letter you have previously signed, your responses will help us improve the program and report on its successes as we apply for future scholarship opportunities. Your participation is completely voluntary. You may choose not to answer a question or are free to withdraw consent and discontinue

Conference Session

ME Division 12: Innovative Approaches to Thermodynamics

Collection

2025 ASEE Annual Conference & Exposition

Authors

Sean Sloan, Oregon Institute of Technology

Tagged Divisions

Mechanical Engineering Division (MECH)

. ©American Society for Engineering Education, 2025 Thermo for KeepsAbstractThermodynamics is often the most hated course in the mechanical engineering curriculum.Why? Because when you add up all the possible combinations of applied equations, they becomeoverwhelming, with often subtle differences that are hard to remember. To counter this, four keyprinciples become a foundation. If these are well understood, simple math operations on thesemay create the rest. These principles are: 1. Q = mC∆T, 2. Understanding latent heat, 3.Understanding P∆V work, and 4. Law of the Turbine (an artifice for student discussionestablishing constant entropy across a turbine, in a piston, etc). Even the confusing differencebetween

Conference Session

Engineering Management Pedagogy: Teaching for Real-World Impact

Collection

2025 ASEE Annual Conference & Exposition

Authors

Majid Nabavi, University of Nebraska - Lincoln; Jena Shafai Asgarpoor, University of Nebraska - Lincoln

Tagged Divisions

Engineering Management Division (EMD)

normal distribution. Exhibit 3 shows a Q-Q plot of residuals to visualize theskewness of grade distribution to show the data non-normality.Exhibit 3 – Q-Q plot for assignment grade distribution.Additionally, we performed a Levene’s test to inspect the homogeneity of variances. The p-valueof 0.25 indicates no statistically significant difference between the variances of all classes.Although the normality of sample distributions for ANOVA has been a point of discussionamong statisticians [7], we decided to repeat the test of means using the nonparametric, Kruskal-Wallis test. A test of all classes returned a p-value of 1.31e-11 indicating significant differencesamong the means for at least one class among the samples. After removing the outlier

Conference Session

Computers in Education Division (COED) Track 2.C

Collection

2025 ASEE Annual Conference & Exposition

Authors

Mahmoud K Quweider, The University of Texas Rio Grande Valley; Liyu Zhang, University of Texas Rio Grande Valley; Jorge Castillo, The University of Texas Rio Grande Valley; Ala Qubbaj, The University of Texas Rio Grande Valley

Tagged Divisions

Computers in Education Division (COED)

(Summary & Resources)Cybersecurity Engineering with CYBI- 4336ML/AI Fall 2024Module 1 SummarySummary: What is ML/AI, Applications in Cybersecurity (CS) Module 1 Introduces ML/AI. It introduces AI/ML Applications in CS.Readings/ Module 01 Slides.Watching: Video Lecture.Resources: • Module 01 Notes [Power Point Slides]/Video Lecture.Deliverables/ 1. Description: Set up Anaconda with CPU/GPU.Assignments: 2. Participate in the discussion Q/A session with your TA Module 02 (Summary & Resources)Cybersecurity Engineering with CYBI

Conference Session

Engineering Technology Division (ETD) Technical Session 4

Collection

2025 ASEE Annual Conference & Exposition

Authors

Marilyn Barger P.E., FLATE (Florida Advanced Technological Education Center of Excellence); Richard Gilbert, University of South Florida; Sidney E Martin III, Saint Petersburg Junior College; Ron Eaglin, Daytona State College

Tagged Divisions

Engineering Technology Division (ETD)

, integrating emerging skills, college ET degree program design,NSF & ASEE interests, and Industry sector support in identifying ET Skill Sets needed for ETtechnician success, promotion, and career advancement is the next phase of this project.Bibliographyhttps://www.industrialsafetysolution.com/labeling/industrial_environments.phphttps://www.google.com/search?q=Engineering+Technology+community+of+practicehttps://www.google.com/search?q=asee+%26+et+%26+as+degree&sca_https://www.nsf.gov/funding/opportunities/ate-advanced-technological-educationhttps://www.google.com/search?q=Engineering+Technology&scahttps://www.bridgevalley.edu/academics/technology/electrical-engineering-technology.htmlhttps://catalog.csn.edu/preview_program.php?catoid=14

Conference Session

Mechanics Division (MECHS) Technical Session 3

Collection

2025 ASEE Annual Conference & Exposition

Authors

Xiaobin Le, Wentworth Institute of Technology; Masoud Olia P.E., Wentworth Institute of Technology; Gloria Guohua Ma, Wentworth Institute of Technology

Tagged Divisions

Mechanics Division (MECHS)

demonstrations to help students begin using the software. We also held a Q&A session to address any issues. The following topics were covered during the lecture, as shown in Figure 1: o Creating objects with different shapes and determining the position of their centers using the Shape toolbar. o Specifying links between objects using the Joint toolbar. o Specifying constraints between objects and the ground using the Constraint toolbar. o Adding external forces, velocity, rotation, springs, pulleys, and other functions using the Function toolbar. o Modifying properties such as mass, velocity, and position using the "Properties" tab under the "Window" menu. o Creating

Conference Session

NSF Grantees Poster Session I

Collection

2025 ASEE Annual Conference & Exposition

Authors

Merideth Frey, Sarah Lawrence College; Dedra Demaree, Blue Ridge School; David Gosser; Colin David Abernethy

Tagged Topics

NSF Grantees Poster Session

implementation examples below demonstrate how modules can beintegrated throughout the standard undergraduate science curriculum or used as science outreachfor high schoolers or early college programs.Evaluation methodologyIn consultation with our external evaluator, Dedra Demaree, we have evaluated our projectobjectives through the collection and analysis of both quantitative and qualitative data collectedover multiple implementations of the modules at Sarah Lawrence College and The City Collegeof New York. Project evaluation included well-established surveys of science identity(STEM-PIO-1 [10]), expert-like mindset (E-CLASS [11], URSSA [12], SALG [13]), studentperceptions of doing authentic research (Q-Sort [14]), focus group interviews with students

Conference Session

Mechanics Division (MECHS) Technical Session 1A

Collection

2025 ASEE Annual Conference & Exposition

Authors

Ryan Carr, U.S. Air Force Academy; Phillip Cornwell, U.S. Air Force Academy

Tagged Divisions

Mechanics Division (MECHS)

. • In a problem involving a spider walking across a rotating platform, the chatbot correctly identified the location and velocity of the spider but could not correctly identify the components of the spider’s acceleration.While these examples are illuminating, a more formal approach to evaluate chatbot performanceis required. Assessments for AI algorithms exist in the literature for a wide variety of topics, andresults scored by various chatbots are published with regularity. Some noteworthy examples are:MMLU - Measuring Massive Multitask Language Understanding [5]GPQA - A Graduate-Level Google-Proof Q&A Benchmark [6]MATH500 – A collection of 500 math problems [7]HumanEval - A collection of coding problems for testing AI [8]These

Conference Session

ECE-Student Learning and Academic Performance

Collection

2025 ASEE Annual Conference & Exposition

Authors

Iman Shayegani, University of Cincinnati; Gregory Warren Bucks, University of Cincinnati; Ibrahim Nihad Awartani, University of Cincinnati; So Yoon Yoon, University of Cincinnati

Tagged Divisions

Electrical and Computer Engineering Division (ECE)

eachconcept inventory. For the two concept inventories that were acquired from the PhysPort website[25], the student level was informed by PhysPort. As for other four concept inventories, theperceived student level was determined by studies using the concept inventory for students.Table 3 also includes the availability of administration directions and answer keys.Table 3. Characteristics of the Six Concept Inventories on Circuits Used in This Study Concept Student Level #Q Question Type Time Directions Inventory Limit & Answer (Minutes) Key ECCE High School

Conference Session

Mechanics Division (MECHS) Technical Session 3

Collection

2025 ASEE Annual Conference & Exposition

Authors

Thomas Golecki, University of Illinois at Urbana - Champaign; Mikayla R Hoyle, University of Illinois at Urbana - Champaign; Melany Denise Opolz, University of Illinois at Urbana - Champaign; Jean-Christophe Raymond-Bertrand, University of Illinois at Urbana - Champaign; Nikhil Chandra Admal, University of Illinois Urbana-Champaign; Wayne L Chang, University of Illinois Urbana-Champaign; Kellie M Halloran, University of Illinois Urbana-Champaign; Callan Luetkemeyer, University of Illinois at Urbana - Champaign; Brian Mercer, University of Illinois at Urbana - Champaign; Matthew West, University of Illinois Urbana-Champaign; Mariana Kersh, University of Illinois at Urbana-Champaign

Tagged Divisions

Mechanics Division (MECHS)

]. This example emphasizes the needfor clear communication of fundamental decisions, such as the orientation of the angularreference frame.Example 6: Rigid Body VelocityAfter kinematics and kinetics of particles, the course transitions to rigid body dynamics.The combination of translational and rotational motion means that each point on a movingrigid body can experience a different total velocity as shown in Equation 5. ⃗ × ⃗rP Q ⃗vQ = ⃗vP + ω (5) Here, the velocity vector at point Q, ⃗vQ , is defined as the sum of the velocity vector at point P , ⃗vP , and the cross product of the rotational speed, ω

Conference Session

New Engineering Educators (NEE) Technical Session 1 - Maximizing Student Interaction and Engagement

Collection

2025 ASEE Annual Conference & Exposition

Authors

Garrett Weidig, Michigan State University; Geoffrey Recktenwald, Michigan State University

Tagged Divisions

New Engineering Educators Division (NEE)

primary objective of this study was to determine if Friday attendance can beincreased in a senior level, mechanical engineering class using a combination of threeapproaches to incentivization.MethodsA novel Friday teaching schedule was introduced for a senior level, mechanical engineeringControl Systems (CS) class. Friday lectures rotated between 1) in person quiz with lecture (Q),2) in person homework study session where the instructor helped students work on assignedhomework problems (HW), and 3) synchronous, virtual lecture over Zoom (Z). For Z lectures,students could earn bonus points towards quizzes by answering poll questions- if the studentattended each Z lecture and answered all poll questions, they would recoup one quiz grade(worth 5

Conference Session

Instrumentation Methods and Techniques

Collection

2025 ASEE Annual Conference & Exposition

Authors

Bradley Lane Kicklighter P.E., University of Southern Indiana

Tagged Divisions

Instrumentation Division (INST)

describes a version of the Boolean finite-state machine implementation in ladderlogic for a final project using a fluid process rig [3].Structured Text ImplementationsTwo structured text implementations are taught in the course.One structured text implementation is similar to the ladder diagram primitives implementa-tion where states are Boolean values and the If-Then-Else statement is used. The followingis a generic FSM example implemented in ST using If-Then-Else statements: // Input Conditioning R_TRIG_1(Input1_In); Input1 := R_TRIG_1.Q; R_TRIG_2(Input2_In); Input2 := R_TRIG_2.Q; // States ... // State1 IF State0 AND Input1 THEN State1 := TRUE; ELSIF State2 THEN State1 := FALSE; END_IF; // State0 IF __SYSVA_FIRST_SCAN OR (State4 AND Input2) THEN

Conference Session

Focus on the First Year

Collection

2025 ASEE Annual Conference & Exposition

Authors

Elin Jensen, Lawrence Technological University

Tagged Divisions

Civil Engineering Division (CIVIL)

studentworking on the redevelopment of a multi-system transit center from Year 2.The Q-Q (quantile-quantile) plots of the Prelim mind map scores and the Final mind map scoresare shown in Figure 2. The plots suggest that both the Prelim scores and Final scores canpractically be modeled by a normal distribution. The minor deviations at the tails are mostpronounced in the cases where a few mind maps scored higher. The skewness to the right isslightly higher in scores of the Final mind map compared to the Prelim mind map. Overall, it isstatistically appropriate to assume that both datasets are approximately normally distributed.Figure 2. Q-Q plots of the scores representing the Prelim and Final mind map. N = 26.A paired t-test was performed on the data sets

Conference Session

ME Division 8: Measuring What Matters: Concept Inventories, FE Exam, and Learning Skills

Collection

2025 ASEE Annual Conference & Exposition

Authors

Ibrahim Nihad Awartani, University of Cincinnati; David Allen Evenhouse, University of Cincinnati; Iman Shayegani, University of Cincinnati; So Yoon Yoon, University of Cincinnati

Tagged Divisions

Mechanical Engineering Division (MECH)

-acceleration [28]. We also focused on the latest completeversion of each inventory found during our analysis, only referring to earlier versions in twocases: When important information such as psychometric data were solely available for thoseversions, or when assessing the use of that inventory through its various literary citationsexcluding of self-citations.IV. ResultsTable 3. Topic Coverage of the Concept Inventories Relevant to Statics FCI FMCE SSI CATS IBCM ASCI PMT TRCV # Topic #Q % #Q % #Q % #Q % #Q % #Q % #Q % #Q % 1 Static 9 30 7 15 4 12 2 20 4 9

Conference Session

Computers in Education Division (COED) Track 4.B

Collection

2025 ASEE Annual Conference & Exposition

Authors

Arezou Harraf; Yuetong Lin, Embry-Riddle Aeronautical University - Worldwide; A. Mehran Shahhosseini, Indiana State University

Tagged Divisions

Computers in Education Division (COED)

Strategies in Global Supply Chains. International Journal of Production Economics, 248, 108455. https://doi.org/10.1016/j.ijpe.2023.108455 • Chen, Y., & Wang, X. (2023). AI-Driven Decision-Making in Supply Chain Bidding Processes: An Empirical Study. Computers & Industrial Engineering, 175, 108860. https://doi.org/10.1016/j.cie.2023.108860 • Patel, R. K., & Mehta, S. (2024). Predictive Analytics and AI in Supply Chain Bid Optimization. European Journal of Operational Research, 305(1), 121-135. https://doi.org/10.1016/j.ejor.2023.09.012 • Liu, H., Zhang, W., & Li, Q. (2023). Risk-Aware AI Systems for Supply Chain Bidding: A Machine Learning Approach. Decision Support Systems, 165, 113834. https

Conference Session

Computers in Education Division (COED) Poster Session (Track 1.A)

Collection

2025 ASEE Annual Conference & Exposition

Authors

Peter Jamieson, Miami University; Ricardo Ferreira, Universidade Federal de Viçosa; José Nacif, Universidade Federal de Viçosa

Tagged Divisions

Computers in Education Division (COED)

Google Colab. Using claude.ai [18] the response is: Response - Claude 3.5 This Python script: 1 import svgwrite 2 from I P y t h o n . d i s p l a y i m p o r t d i s p l a y , HTML 3 import ipywidgets as widgets 4 from I P y t h o n . d i s p l a y i m p o r t c l e a r o u t p u t 5 c l a s s DFlipFlop : 6 def init ( self ) : 7 s e l f . s t a t e = 0 # Output Q 8 self . prev clock = 0 910 def update ( s e l f , clock , data ) :11 # U p d a t e s t a t e on r i s i n g e d g e o f c l o c k12 i f c l o c k == 1 and s e l f . p r e v c l o c k == 0 :13 s e l f . s t a t e = data14

Conference Session

MATH - Works in Progress for Mathematics Education

Collection

2025 ASEE Annual Conference & Exposition

Authors

Poornima Jayasinghe, University of Calgary; Placida Amali Dassanayake, University of Calgary; Andre Oliveira, University of Calgary; Anthony Starr Kroll, University of Calgary; Irushi Jayathunga, University of Calgary

Tagged Divisions

Mathematics Division (MATH)

, students expressed that the use of applicationsand real-world examples significantly improved their understanding of numerical methods. Theyalso felt that context-based learning enhanced their exam performance. As a result, they areconfident in their ability to apply theoretical knowledge to solve complex problems. Q#6 I found that applications, real-world Q#7 Context-based learning has effectively examples, and problem-solving in SUSE 307 prepared me for solving questions in my helped understand numerical methods exams and assignments in the course more clearly. compared to other math concepts. Q#8 Based on your experience, would you like Q#9

Conference Session

Computers in Education Division (COED) Poster Session (Track 1.A)

Collection

2025 ASEE Annual Conference & Exposition

Authors

Zifeng Liu, University of Florida; Yukyeong Song, University of Florida; Qimao Yang, University of Florida; Wanli Xing, University of Florida; Jing Guo, University of Florida

Tagged Divisions

Computers in Education Division (COED)

No significant results reported[20] 2020 Undergraduate major in CS Software-oriented approach using Q# No significant results reported[11] 2021 Users with programming experience Virtual reality (VR)-based tool for QC programming No significant results reported[14] 2021 Undergraduate students Comparison of Qiskit (IBM), PyQuil (Google), Q# (Microsoft), etc. Descriptive: QC understanding ↑; Interest in QC learning →[21] 2021 Undergraduate major in engineering Qiskit (IBM), PyQuil (Google), Q# (Microsoft), etc. Descriptive: Satisfaction with the course[10] 2023 Everyone: Massive

Conference Session

Software Engineering Division (SWED) Technical Session 2

Collection

2025 ASEE Annual Conference & Exposition

Authors

Mike Borowczak, University of Central Florida; Andrea Carneal-Burrows Borowczak, University of Central Florida

Tagged Divisions

Software Engineering Division (SWED)

contentserves to keep students engaged and returning to the course content even when one topic presents amore difficult challenge to student mastery than another topic. The overall structure and sequenc-ing is presented in Table 1.Week # Cycle Concepts Lab Available Quests 1 C 1: Hello World 2 R Storing and Manipulating Data 2: Cash Register 3 Q Quest A 4 C 3: Collatz Numbers 5 R Controlling Flow and Process 4: RPS Retake Quest A 6

Conference Session

ERM Technical Session: Broadening Methodological Impacts

Collection

2025 ASEE Annual Conference & Exposition

Authors

Amirreza Mehrabi, Purdue Engineering Education & Electronic and Computer Engineering; Jason Morphew, Purdue University at West Lafayette (PPI)

Tagged Divisions

Educational Research and Methods Division (ERM)

misconceptions among engineeringstudents in foundational STEM courses, focusing on physics concepts assessed through the ForceConcept Inventory (FCI). Misconceptions, defined as systematic and deeply rooted alternativeunderstandings, hinder students’ ability to master complex topics and apply knowledgeeffectively. Traditional models such as Item Response Theory and Cognitive Diagnostic Modelsare limited in their ability to track misconceptions over time, failing to capture how theseerroneous beliefs evolve or persist across assessments. To address this gap, we employ aTransition Diagnostic Classification Model (TDCM) that incorporates a Q-matrix to mapmisconceptions to test items and monitor their transitions as distinct cognitive attributes

Conference Session

ECE-Grading Approaches and Assessment Practices

Collection

2025 ASEE Annual Conference & Exposition

Authors

Christopher Cischke, Michigan Technological University

Tagged Divisions

Electrical and Computer Engineering Division (ECE)

........ Grading Scheme ■- 't-~ 'b-§' Q '< 't-~ 'b-§' Q '< .,_~ 'br§' V '?Jr§'V

Conference Session

NSF Grantees Poster Session II

Collection

2025 ASEE Annual Conference & Exposition

Authors

Shana Lee McAlexander, Duke University; Catherine Brinson, Duke University; Richard J. Sheridan, Duke University; Junhong Chen, University of Chicago; Jennifer Nolan, University of Chicago

Tagged Topics

NSF Grantees Poster Session

. Table 1. Timeline for rapid proposal design activity Activity TimeTeam Organization Select roles: timer, scribe, speakers 15 min Member introductions: sharing research interests and methodsRapid Proposal Design Brainstorm research ideas Screening/identify top ideas 45 min What could you accomplish together to have the greatest impact? Develop top idea and prepare 1-slide visualPresentations Practice presentation 45 min Speakers share-out 3 min each + Q&AReflection and wrap-up

Conference Session

NSF Grantees Poster Session I

Collection

2025 ASEE Annual Conference & Exposition

Authors

Amber F Young-Brice, Marquette University; Allison Murray, Marquette University; Somesh Roy, Marquette University

Tagged Topics

NSF Grantees Poster Session

in my mind. And I think a lot of the material kind of relies on previous experience, which I didn't have a whole lot of.Of interest when integrating study findings, although there was noted change in awareness andintegration, qualitative data analysis revealed difficulty in extrapolating learning theory examplesfrom different fields of study. Some faculty evidenced a lack recall of the learning theoriescovered in the summer program, as well as a desire to develop a better understanding of the data,evidence, and practical applications, which would support and encourage their use of learningtheories in engineering courses. Min stated, I wish there’s more examples like solutions like Q&A, lots of Q&A, so I can ask

Conference Session

Minorities in Engineering Division(MIND) Technical Session 5

Collection

2025 ASEE Annual Conference & Exposition

Authors

Animesh Paul, University of Georgia; Kevin Jay Kaufman-Ortiz, Purdue University/Cornell University; Crystal Alicia Nattoo, Stanford University; Yeswanth (Yash) Tadimalla, University of North Carolina at Charlotte

Tagged Topics

Diversity

Tagged Divisions

Minorities in Engineering Division(MIND)

was being discussed.In this study, field notes were particularly valuable in capturing nuanced reflections and emergentthemes. After the focus group, two of the authors wrote the findings for this work-in-progresspaper, while the other two reviewed the findings for accuracy. This collaborative approach ensuredthat the analysis was thorough, reflective, and representative of the shared experiences and identitiesof the participants. The focus group protocol questions we asked each other are as follows: 1. Q: How have your LGBTQ+ identity and engineering identity evolved during your PhD journey? 2. Q: Are there any specific moments during your PhD or professional interactions with faculty, peers