echolocationbehavior of a bat. High school and undergraduate students are involved in the entire design,fabrication and flight process. The UAS will navigate an urban environment using only ultrasonicspeakers and microphones, a more cost-effective alternative to the expensive cameras typicallyused in UASs. The vehicle features a 3D-printed bat head, modularly attached, containing anultrasonic speaker in the mouth and two microphones in the ears to capture reflections from thesound waves emitted. As part of the design, casings for the electronic speed controllers (ESCs),which regulate the motor speeds, as well as the bat head, are designed and fabricated.Throughout the development process, several challenges are encountered. Minimizing dead weightand drag
. Wechose to not rely on an ethical framework for reference, because we have found thatmany students have interpreted ethical frameworks in absolute terms.The exercise began with a briefing about the differences between ethics and morals, withexamples of typical moral themes, followed by individual reflection about what thestudents knew about themselves. The participants were then assigned to ad-hoc teams inorder to compare their moral priorities to those of other team members. Finally, eachteam formed a set of moral priorities for their own hypothetical engineering company.In order to assess the outcomes of this activity, we sought to answer the followingquestion: How did this exercise bring out multiple competing moral standpoints and
modify the base values for voltage and current to a new set ofvalues. If the per-unit system is implemented correctly, changing the base values shouldautomatically update all the per-unit quantities while leaving the physical quantities unchanged.This consistency demonstrates the utility and flexibility of the per-unit system in power systemsanalysis. Students are encouraged to experiment with different base values and reflect on theresults, discussing any patterns or observations that arise from changing the base quantities.3.2 Python Exercise 2: Transmission Line Bundling and Power Factor CorrectionIn this exercise, students develop a Python program to analyze the impact of conductor bundlingon a power system. The line data provided includes
delineate the curriculumdevelopment process of the program, detailing its evolution from version 1.0 to 5.0, and 2) to sharecomprehensive evaluation data that reflects the reception of the curriculum across the last threeiterations. By providing an in-depth look at both the progressive refinement of the curriculum andthe empirical outcomes associated with each version, this paper provides valuable insights toenhance ongoing pre-college engineering education efforts.MethodsProgram ContextLarge-scale pre-engineering programs tend to appeal to students who may already be planning tostudy engineering in college. These programs serve a purpose in helping engineering studentsprepare for college. However, these programs often fail to appeal to students
improve their self-concept [9, 11]. To theauthors’ knowledge, our storytelling workshop format and public performance aspect are novel.4. MethodologyOur work is grounded in theories of narrative identity [14], reflection [15], and cognitiveconsistency [16]; our focal outcomes are guided by three basic human needs of Self-determinationTheory (SDT): autonomy (identity), relatedness (belongingness), and competence (imposterfeelings) [17]. We employ a mixed-methods sequential explanatory design [18] and followprinciples of Design-based Research [19-20] with input from multi-institutional/disciplinaryfaculty, non-profit partners from The Story Collider, and STEM graduate student participants.In this project, we iteratively develop, evaluate, and
pattern described above wasgenerally adequate to the needs of the students working as peer mentors. Yet, about one-fifth ofthe peer mentors felt that too little time had been spent training them while over half felt too littletime was spent in direct interaction with students. In fact, one informant stated in a follow-on querythat s/he had received no training. As is the case in most programming with a broad implementationfootprint, there would have been individual variation in the general approach taken. There alsowould have been a range of preferences for level and types of support or interaction among thestudents recruited to be peer mentors. These circumstances appear to be reflected in the surveyresults including one party noting not being
. Thisperception largely stems from students enrolling to fulfill a requirement rather than out ofgenuine interest. A traditional lecture-based teaching approach has been identified as a key factorcontributing to student disengagement. This research reflects the instructor's ongoing efforts toredesign course content, aiming to enhance student engagement and improve their perceptions ofintroductory EE courses in the civil and environmental engineering curriculum.Active learning has been extensively studied across various disciplines. Prince (2004) defines itas instructional methods that engage students in the learning process, requiring them to activelyparticipate rather than passively receive information [4]. Key techniques include think-pair-share
for Undergraduates at the University of Nebraska–Lincoln. His research interests include engineering identity, reflective learning, and innovative teaching practices. ©American Society for Engineering Education, 2025Exploring Integrated Peer and Reverse Mentoring in Engineering Education:A Work in Progress.AbstractThis Work-in-Progress (WIP) paper examines the introduction of integrated peer and reversementoring for first-year engineering students at a Hispanic Serving Institution (HSI). In thismentoring program, near-peer mentors—upperclassmen with relevant academic knowledge of thecourse—met weekly with mentees to provide guidance, share experiences, and address academicchallenges. These near-peer
andcollaborative learning models, to enhance the COIL experience. For example, incorporatingstructured collaborative scripts and promoting positive interdependence among student groups hasbeen identified as a critical factor in fostering productive engagement and learning outcomes. Keyfindings from the analyzed case studies highlight the importance of preparing educators tonavigate technological and cultural complexities. The authors propose implementing pre-COILtraining workshops, providing templates for course design, and creating a repository of bestpractices to support educators. Additionally, the guide underscores the significance ofstudent-centered approaches, including reflective exercises, to deepen learning and interculturalunderstanding.This
engineeringsoftware. Only some groups calculated the volume of a hollow canoe. Calculations did notnecessarily reflect the highest level of math preparation by one member of the team. Somecomplex solutions were performed by students enrolled in Trigonometry and by those in LinearAlgebra, while some simple solutions were performed by students in Pre-Calculus. All teamswere able to produce a final calculation for the size of their canoe. These findings indicate thatcivil and construction engineering and construction management students, even with their variedmath backgrounds, can come up with creative approaches to solve ill-structured problems basedon their existing preparedness
studentsformulated cohesive solutions that integrated multiple ROS2 packages. By the time they reachedthis final assignment, most learners had developed a solid framework of fundamentalcompetencies that could be extended to their final, open-ended projects.Rationale for Key ChangesFrom the outset, the lab sequence was devised with progressive complexity in mind, graduallylayering new tools and concepts to reduce cognitive overload. This scaffolded approach helpedstudents steadily build confidence, ensuring each new skill—such as command-line proficiency orROS2 control—was reinforced before introducing more demanding tasks. Additionally, hands-onintegration with simulated environments and (for some students) real hardware reflected howrobotics is typically
strategies herein reflect an intentional commitment to Educatethe Whole Engineer by promoting an academic advising model that would both complement thecurricular experiences and align with the evolving personal and professional aspirations ofstudents towards career readiness. The approaches described offer valuable insights for both newand existing engineering programs seeking to transform their advising practices to better serve anincreasingly diverse student population. There is urgency in this work for the betterment ofhigher education and engineering education.I. INTRODUCTIONThe value of higher education is under attack and the criticisms are many: cost, inadequatepreparation for job-readiness, outdated and inflexible curricula and degrees
as necessary to alignwith their pedagogical goals and institutional standards. After redesigning the course, facultydocumented their reflections, including the advantages and challenges of using AI in coursedevelopment.Survey Design and AdministrationTo evaluate students’ perceptions of AI, an end-of-semester survey was distributed. The surveyconsisted of: 1. Likert-Scale Questions: Students rated their agreement with statements regarding the reliability, accuracy, and utility of AI tools in their coursework. 2. Open-Ended Questions: Students elaborated on their experiences with AI tools, including specific examples of how they used these tools for problem-solving and their concerns or reservations.Survey questions
declare their major in March of their second semester, while taking theirsecond selected introductory engineering course. Intro ChemE, offered each Fall (≈50 students)and Spring (≈25 students), primarily enrolls undeclared first-years, reflecting the institution’sbroader demographics, with Hispanic/Latino and BIPOC groups underrepresented. The keylearning outcomes for the course are to develop skills in data analysis, material balances, anddetermining state properties.Intro ChemE meets for five hours weekly: three hours of lectures, one hour of lab, and one hourof recitation. Recitation sessions involve small groups working on structured exercises or casestudies—known as recitation problems [25], [26]—based on the material covered in the
importanttechnique for system isolation while debugging is the use of a digital twin, a programmablesimulation that reflects a physical system [25]. The use of digital twins for separation ofconcerns in error correction is commonplace in the engineering industry [25], and has growingacceptance in undergraduate education, but it is unusual in K-12 [26]. Some digital twinsystems are being explored as a way to serve educational communities that do not have readyaccess to hardware [26]; for analysis of systems too large, long, or complex to analyze in aclassroom context [27]; or for systems that are not visible by other means [28]. Few are beingused for the educational purpose of easing the transition to a hardware system that has its ownset of issues beyond
aforementioned research in mind, the EME was developed to enhance inclusion andautonomy, and thus motivation, in a third-year required civil engineering course (CE 3311:Geotechnical Engineering), rooted in EML course outcomes. Two specific course outcomes aswritten in the course syllabus, which are assessed as part of the project grade and reflection, areas follows: Create connections between class content, and create value for general audience science communication, via a museum exhibit group project. Function effectively in a team environment by establishing goals, assigning tasks, and meeting objectives.The project and its ties to EML are outlined below, with student motivation analysis using self-determination theory
applyengineering design to produce solutions that meet specified needs with consideration of publichealth, safety, and welfare, as well as global, cultural, social, environmental, an societal contexts”(ABET, 2021, p. 8). Both ABET’s student outcomes (s/o) and CEAB’s graduate attributes (g/a)also require graduating students to have the ability to communicate well with colleagues as wellas non-engineers (ABET s/o 3, CEAB g/a 7), possess effective teamwork and leadership skills(ABET s/o 5, CEAB g/a 6), be able to appreciate the impact of their work on society and theenvironment (ABET s/o 4, CEAB g/a 9), and make decisions that reflect the ethical requirementsof the profession (ABET s/o 4, CEAB g/a 8,10)(ABET, 2021; CEAB, 2022). The presence of user-focused
that frequently find textbooksfavor technical and procedural knowledge over alternative approaches, portray fields as fixedbodies of knowledge, and minimize the positionality of disciplinary experts in defining andshaping disciplinary knowledge [4], [5], [6], [7], [8]. When narratives remain unchanging andmonolithic, they not only obscure the dynamic, inquiry-driven nature of disciplinary work butalso risk marginalizing students whose experiences and identities are not reflected in dominantepistemic assumptions [9]. Further, by recognizing and addressing these limitations, educatorsand researchers can promote curricular materials that more accurately represent the evolvingcharacter of knowledge in engineering education and foster a learning
“special education” classrooms in secondary school due to a lack of teachertraining and resources to integrate students into classrooms, which can significantly hamperpreparations for the academic demands of university STEM programs [9]. Thisunder-representation is not merely a reflection of broader societal challenges but also highlightsspecific barriers that DHH students face in STEM higher education, such as the limitedavailability of accessible learning materials and real-time communication tools [10].The World Health Organization estimates that over 5% of the world’s population—approximately430 million people—experience hearing impairment, with this number expected to rise to over700 million by 2050 [11]. Within this population, DHH students
engineering program at the time of enrollmentin the study. Participants completed a survey and interview at the end of each semester over thecourse of two years. During the interviews, participants were asked to reflect on theirexperiences and involvement in mathematics, science, and engineering. Questions in theinterview were geared towards understanding the participants’ identity and affect. Theseinterviews tended to last between 1 and 3 hours depending on the depth of the participants'responses.Preliminary AnalysisInterviews were professionally transcribed, and then the transcripts were analyzed using thematiccoding and discourse analysis. The transcripts were first coded for expression and regulation ofemotions regarding math, science and
TA, akin to a traditional apprenticeship. Others have college-leveltraining programs, conducted in condensed workshops, facilitated by a team of staff, andpresented to hundreds of TAs per semester. Others have ongoing programming throughout theyear with a larger sustained time commitment. Each approach requires differing levels ofresources and reflects the differences between institution types.Given the variability of TA training models, the authors sought to gain insight into the currentstate of training across multiple institutions. In doing so, we demonstrate that there may not beone universally applicable approach to train our teaching assistants, but there is value in sharingknowledge of possible strategies, content and models to
¯ and y¯ are their means, and n is thetotal number of students. The value of r ranges from -1 to 1, where r = +1 indicates a strongpositive alignment, meaning that as quiz scores increase, final grades also increase. An r value of0 suggests no alignment, indicating no linear relationship between quiz scores and final grades.Conversely, r = −1 represents a strong negative alignment, where higher quiz scores areassociated with lower final grades.This analysis helps determine which quiz generation method more accurately reflects students’overall learning performance, thereby addressing RQ2.3.3.3 Quantitative Analysis using Surveys Survey Questionnaire Q1 How relevant were the quiz questions to the topics covered in class? Q2 How
study.In the questions related to Construct 7 (C7, Q67–69), students shared their opinions on the university'sengagement with sustainability issues (Figure 4). Lower scores were again observed among Geologystudents. This construct had the highest overall average (3.972). For both study programs, the itemwith the lowest score (Q69) was related to the existence of a sustainability policy at the university.The item with the highest score (4.157) reflected students' importance of sustainability for training,academic development, and professional growth (Q68). Regarding the item where students considerthat sustainability initiatives are implemented at their university (Q67), the average score was 3.934.Unlike other constructs, differences were observed
their writing in sustained or long-term writing projects[13, 14]. Due to thismodule, the majority of students were optimistic towards using AI in future assignments forwriting. However, students who use ChatGPT to write tend to run into common pitfalls such asambiguous writing, bias reinforcement, and “hallucinations”[15]. This shift reflects the need toprovide clear guidance on appropriate AI usage in educational settings. This work highlights thegrowing recognition that fostering AI literacy is a crucial educational practice in modernclassrooms.To investigate the ways students respond to AI literacy efforts and how they may change theiruse of genAI in these situations, we introduce structured usage of AI in one lecture to increase AIliteracy
emotions such asfrustration and confusion [11]. These emotions are particularly pronounced when studentsengage with complex problems that lack clear solutions, requiring them to exercise creativity andresilience [12-13]. Despite these challenges, negative emotions served as powerful learningopportunities. Research suggested that experiencing and overcoming frustration fosteredpersistence and adaptability—skills essential for success in engineering professions [15].Moreover, environments that encourage students to articulate and reflect on their emotionsenhance collaboration and self-regulation, which are critical for effective teamwork andproblem-solving [9][17]. For example, educators who explicitly addressed emotional experiencesduring
in an outcome” [31], [32,p. 5]. This connection is further forged by the theoretical framework’s use of categories tounderstand the various ways individuals move through a transition; narrative analysisunderstands that individuals are not consciously living life event-by-event, rather they reflectback and pull events from the larger structure that is their life [33]. For this study specifically,the narrative of mid-career transition to engineering is the focus of Mac’s story. Mac provided anoral history; he reflected on the events that make up his transition to engineering, their causes,and their effects [31].Study Participant While the defining population of interest for this work is mid-career individuals whotransitioned to an
adjustments clarified guidance,reduced ambiguity, and supported inquiry-based, student-driven projects.During the 2023-2024 academic year, ECS-WL was piloted in five classrooms within the MPSdistrict, involving 242 students who created and submitted 755 unique web pages using 41distinct HTML tags. Assessments of student submissions on the first two assignments revealed awide array of topics reflecting personal interests and unique perspectives. Students createdwebsites about local, chain, and fictional restaurants representing various ethnic cuisines, and adiverse selection of books and movies. The Linguistic Inquiry and Word Count (LIWC) toolshowed that students added more personal content, authenticity, and references to theirmotivations and
instruction; they need opportunities to apply these strategies acrossdiverse contexts. This includes instructors modeling how to recognize when specific strategiesare useful and providing ongoing feedback (Wingate, 2007). Some instructors embed learningstrategies into course activities without explicitly explaining how or why they work. While thisapproach may help students see the relevance of these strategies within specific contexts, it oftenfails to support their transfer to novel situations. Successful transfer of learning requires thedevelopment of reflective expertise (van Merrienboer et al., 1992)—a form of metacognitiveskill that enables students to not only execute a strategy but also understand its underlyingprinciples. This expertise
should progress during their time in the program. We described the process of developing learning progressions across a sequence of three required aerospace engineering courses (one in each of years two, three, and four of the program) and collecting preliminary data to begin investigating the presence of activities and content related to these progressions in the classrooms. Data collection included the pilot survey, ethnographic classroom observations, and written individual reflections from students. These efforts also included developing a new design-for-requirement mini-project, now referred to as the glider-catapult project [15]. The progressions focused on the following six competencies
prompt taxonomy. Jamieson’s LLM Prompt Taxonomyis a three-level classification system for LLM prompts based on existing research and presented in[12]. The taxonomy consists of: 1. LLM Shot Type [13] • zero-shot: Prediction without specific training [14] • few-shot: Prediction with example actions [15] • multi-shot: Multiple separate actions, can combine with other types [16, 17] 2. LLM Reasoning of Thought • nothing-of-thought (NoT): Baseline without reflection • self-improved of thought (SoT): Reflects and improves on the prompt [18, 19] • chain of thought (CoT): Linear steps with reasoning [20] • tree of thought (ToT): Branching paths for alternatives [21] • graph of thought