related foci. Encouragingly, PSTs came to recognize sustainability in terms ofenvironmental stewardship and social responsibility, consistent with the EOP framework (TheLemelson Foundation, 2022) and as emphasized in the stories. When writing the stories, wehighlighted what motivates sustainable engineers to carry out their work (Gottschall, 2012; Raoet al., 2020). PSTs also formed more detailed understandings of sustainability (Gannon et al.,2022), gained related self-efficacy (Menon et al., 2024), and planned to use stories in their ownfuture classrooms. The stories supported PSTs’ disciplinary literacy (Silvestri et al., 2021).Our work thus far indicates promising areas for further exploration and scaling up. As wecontinue to implement the
holds a B.S. in Biological Engineering from the same institution, where she developed a strong interest in inclusive teaching practices and STEM outreach. Her research focuses on accessibility and the inclusion of individuals with disabilities in engineering, informed by her personal experiences with chronic illness. She has eight years of research experience in biomaterials and pharmaceuticals, with publications in peer-reviewed journals and presentations at national conferences. Peterson has also served in multiple teaching assistant roles and is committed to engaging students through creative methods such as visual tools, humor, and analogies. She is an active member of the Society of Women Engineers and a
collect for pursuing or obtaining a STEMdegree under an LSAMP fellowship have moved them upward in the socioeconomic status ladder.More of them have medical insurance (18.75% better than before), and the participants perceivetheir socioeconomic status as better than before they started working with their highest STEMeducation degree. While the researcher is still working on the qualitative part of the data, mostparticipants mentioned their perception of moving upward compared with their peers who did notpursue STEM degrees or did not have LSAMP support. 3Study 2 split the results of the student transcripts into four subgroups: the students who
repetition, social cognitivetheory considers the agency of the student and the social aspects of learning. The primaryassumption of SCT is that students are active participants in the learning process, acquiring anddisplaying knowledge, skills, and behaviors that align with their goals through a process calledtriadic reciprocal causation, illustrated in figure 1. In this process, according to SCT, the three factors to consider are the students’ goals andvalues, their behavior (in this case an indicator of their knowledge) and their environment, whichincludes not only the classroom and their available tools, but student peers and their instructors.Through group activities using the hardware we have dubbed desktop learning modules, orDLMs
says,” Leah explains. Despite excelling academically,her visa status has restricted her access to internships, jobs, and other professional opportunitiesthat her peers take for granted. “It’s hard to hear everyone else doing all these things that I’mlegally not allowed to do. It’s a constant reminder of what I’m up against.” Leah reflects on the challenges of finding community within the Middle Eastern diasporain the U.S. She notes the heightened fear of visibility due to political tensions and the potentialconsequences of being associated with student organizations affiliated with her home country.“There’s always this undercurrent of fear. Even if you’re just gathering to eat snacks from backhome, you’re wondering if it’s too extreme
semesterincluded four engineering students, described in additional detail in the participants section, andtwo instructors. During the planning phases of this pilot, the research team conducted a literature reviewand found a significant amount of literature on learning in engineering coops and internships,often focused on professional skill development (e.g. communication, writing, teamwork) [8].Due to the focus of integrating engineering work and curriculum, the team also searched forliterature on technical learning in engineering coops and internships and was surprised to findsignificantly fewer publications in this area. In a search of ASEE Proceedings from 2000-2023,the authors found a single paper focused on technical learning, a study by
seniordesign project team struggling with interpersonal conflicts and miscommunication during a peerassessment session, which led to unresolved tensions and stalled progress on their websiteredesign project for a local non-profit. The case highlights challenges in team dynamics,including feedback mismanagement and differing conflict styles. After reading the case studentswere required to write a 300–500-word essay, to analyze the conflict, identify the styles anddynamics involved, and propose strategies for resolution. The goal of the reflection is to assessthe students in terms of their understanding of the module’s concepts and their practicalapplication in resolving conflicts. Students answer the following reflection questions: • Why are things
utilize sensors to 'see' their environment and adeptly navigateobstacles. Figure 3: mBot platform used in the workshop activities.The activity was divided into four different tasks to make sure students could independentlyprogress on the different tasks at their own pace. Hands out were provided with clear instructionson the steps and on how to use block coding to perform the required tasks. • Task 1 Start up!: The first activity consisted in connecting the mBot to the laptop via USB and connect it the desktop • Task 2 Obstacle Avoidance: Students started writing the code to enable mBot to move forward, to stop for 2 seconds when an obstacle was at distance less than 20 centimeters and move backwards
finally resignedly accepted ownership of the new DEI design course, due to beingthe instructor most consistently assigned to teach it. She decided to completely redesign thecourse to deliberately separate the technical and social elements. Diana writes about this process: A history of poor student evaluations has led us to be less bold with these justice topics than they deserve. We have developed a hesitance towards highlighting the justice focus of this course, and rather ‘trick’ students into thinking the course is more technically focused by couching these topics within the premise of user- centered design… The line that we toe is convincing students that the course content is valuable to them while not
improve students’ learning outcomes at scale,improve diversity within STEM disciplines, reduce failure rates, and support skilldevelopment [1], [8]–[12]. Active learning involves engaging students directly in the learningprocess through activities and discussions, rather than passively listening to a lecture. Itemphasizes higher-order thinking and often includes collaborative exercises such as problem-solving, peer teaching, and group work [13] and can vary widely, from brief interactiveactivities within lectures to entirely problem-based learning courses [14]. This method iscontrasted with traditional lecture-based instruction by encouraging students to activelyparticipate and reflect on their learning. By involving students in active
contributions of microfluidic systems in the visual system. She received the 2023 AIMBE Professional Impact Award for the inclusion of Health Disparities within under/graduate training and was honored as the 2024 Plenary Speaker to the BMES Council of Chairs for integration of health disparities in Biomedical Engineering curricula. She is an executive committee member for the Rutgers Connection Network that develops inclusive forms of peer mentoring for mid-career faculty as well as new faculty.Kelsey Watts, University of Virginia Kelsey Watts is a postdoc at the University of Virginia in Biomedical Engineering. She is committed to developing more inclusive teaching and research practices
culturalexpectations within East-Asian communities. These experiences offer a nuancedperspective on participants' challenges, enabling an empathetic and culturallysensitive approach.My position as both a researcher and an insider enables me to build rapport and trustwith participants, fostering a safe and open environment for sharing authenticexperiences. At the same time, I am critically aware that my positionality mightinfluence how I interpret and represent their narratives. To actively address potentialbiases, I will employ several strategies. First, I will maintain a reflexive journal todocument my assumptions, emotional responses, and potential influences on theresearch process. Second, I will seek regular feedback from peers, mentors, andadvisors who
(WIP) paper, we propose investigating why students who initiallyindicate interest in STEM are not enrolling in a STEM major using a detailed interview protocoland an analysis of enrollment data.At our small liberal-arts college, students declare a major in their second year. However, in thesummer preceding their arrival they declare academic interests and are matched to advisors in thedisciplines they self-selected. Throughout their first year, students take a common first-yearseminar, a first-year writing course (of their selection), and STEM students take 1-3 introductorySTEM courses. Several years of data shows that a large proportion of the students who initiallyexpressed interest in STEM declare a non-STEM major in their second year. We
these three individuals, as appropriate, to reach saturation of our themes.Analysis Procedures. Coding of data was conducted in a first round of open coding, usinggerund codes to describe mechanisms of identity development and contextual codes to describeelements of faculty development environments. Author B and Author C coded the data in thisphase with peer debriefing after each code was applied to build strong consensus on which codeswere emerging from the data and to ensure interrater reliability moving forward. A second roundof coding was then conducted with the final set of codes to apply them to the full dataset.Axial coding was begun in a third round to form an initial framework for this paper. We plan tore-examine the framework and
refine ideas through observation. Their drawings reveal a cognitive process thatmerged visual thinking with tactile engagement. Later artists, such as Vincent van Gogh andEdvard Munch, engaged in repetitive and expressive mark-making that mirrored their emotionalstates. For them, sketching became a means of reflection and emotional processing. In bothtraditions, the act of drawing or writing by hand created a bridge between physical action andmental focus. This integration of hand movement, attention, and emotion represents an embodiedform of cognition—one that supports clarity, emotional regulation, and creative insight.MethodsTo address our research questions, we identified three sets of keywords and conducted searchesusing IEEE Xplore, SCOPUS
and digital engineering notebooks play vital roles in pre-collegeengineering education by enabling students to document their design processes and reflect ontheir progress. Physical notebooks have long been favored for their simplicity and ability tosupport cognitive engagement through writing and sketching, which research shows enhancesmemory retention and understanding [4]. They are also accessible and affordable, making them apractical option in schools with limited digital resources. Despite advancements in digitaltechnology, many students and professionals still opt for the physical notebook format due to itsease of access and use without having to deal with the complexities of accessing expensiveequipment (hardware and software) and
Paper ID #48943BOARD # 213: Perspectives of Junior Scholars: Calculus Learning Outcomesfrom Middle School Students After Use of an Educational Video Game (Workin Progress)Alex Gonce, Texas A&M University Alex Gonce is an undergraduate researcher at the LIVE Lab at Texas A&M University, where they study Computer Engineering with a minor in Neuroscience. They have worked at the lab for over a year, leading a research team and collaborating on multiple projects focused on gamification in education. In addition to their research, they serve as a Peer Teacher for the College of Engineering, where they support instruction
stipend opportunities within the IEC network, • Collecting and reviewing student applications, • Interviewing candidates, and • Selecting recipients and integrating them into the 2TO4 network.Beyond financial support, the program fosters a community of scholars by: • Hosting Professional Growth webinars, • Organizing virtual meetings for scholars to share academic and internship experiences, • Establishing a Student Ambassador Program for peer mentoring and outreach, and • Offering opportunities for students to deepen their ECE knowledge while enhancing the learning environment for others.The project also includes a research component to better understand barriers and opportunitiesimpacting CC-to-4-year transitions
details with peers, supervisors, reports, and clients[9], [21]. Engineers often rely on inscriptions: domain-specific sketches, figures, diagrams, and charts to think through and communicate their ideas,[22]and interpret noisy data in a way that allows them to productively progress in the project[9]. he oral assessments were designed to replicate authentic engineering practice. In the first oralTassessment, students had to draw a possible mold for the yogurt cup and use it to communicate design attributes. They also had to weigh the tradeoffs of different design decisions and make suggestions based on their understanding of process parameters, design attributes, and their own engineering
many workplace plans and initiatives togrind to a screeching halt. This curriculum renewal initiative of the mechanical engineeringprogram at Ohio State University was no exception. Over the course of 2020-2022, slowprogress was made on writing specific program goals to match each of the six guiding areasdeveloped during the 2019 retreat. Next, progress was made on developing the student learningoutcomes that would comprise each program goal. Starting in 2022, the curriculum committeewas finally able to move the project off the back burner and work with more focus and purposeto build out the student proficiencies, which are the fine-grained skills that make up studentlearning objectives.By the beginning of the 2023-2024 academic year, the
largedatasets generated by the built environment, including air quality, structural health, and energyconsumption data. The field has been further disrupted by the emergence of powerful generativeAI (GenAI) tools in the last few years, such as OpenAI’s GPT-4 which powers the popularChatGPT chatbot. These large language models can perform sophisticated tasks like interpretinglarge datasets, writing code for wrangling and analyzing data, brainstorming ideas, and explainingcomplex statistical and mathematical concepts in ways that closely mimic natural humanlanguage. In CEE education, GenAI holds the potential to make data analysis and programmingmore accessible to students who may lack a strong background or interest in these areas. However,this raises
applications. To evaluate the impact of the redesigned CS 101 course, a CS1assessment was developed to measure students’ understanding of programming fundamentals,pseudocode interpretation, and Python-specific skills. Future work will focus on incorporatinggroup activities into lab sessions, expanding mini-project offerings, and refining the assessmenttools to further align with the needs of engineering students.1 IntroductionIntroductory computer science (CS) courses, commonly known as CS1 [1], serve a critical role inequipping students with important computational skills, including error handling strategies [2, 3],code-writing proficiency and syntactic accuracy [4, 5], and the development of viable mentalmodels for problem-solving [6, 7, 8]. While
predefined outputs [42]. Unsupervisedlearning in education is used to group students by factors such as engagement and learningbehavior [43, 44, 45], academic performance and outcomes [46, 47], student reflections [48], andbehavioral states [49]. While not predicting success directly, these methods guide personalizedteaching strategies and targeted interventions.Generative AI - Focus of ApplicationStudent-Focused ApplicationsDespite concerns about the impact of ChatGPT on student learning, generative AI offers valuableopportunities in academia, including personalized learning paths [50, 51], peer collaboration [52],and additional tutoring support beyond classroom hours [53]. Leveraging these capabilities cancreate more dynamic and engaging
formidable communicative, embodied resources forgrounding principles in STEM. Discussing torsion, a student may enact angular deformation bygesturally communicating their emerging understanding to peers (see Figure 1). Gestures canindicate a students’ reasoning processes as sensorimotor activity is engaged in problem solvingand analysis [7; see Figure 1]. In engineering, students and instructors often produce gestures whilereasoning about physical and mathematical phenomena [9] and carry nonverbal information thatcomplements verbal reasonings [10]. Grondin and colleagues [10] catalogued the gestures engineering students produced in anengineering lab as they mechanically reasoned about the concept of torsion. These gestures oftendepicted the
tryexperimenting with other AI-powered techniques that are likely to become more common inengineering education and higher education at large.IntroductionThe rise of ChatGPT, and other generative AI tools, has led to a number of debates in educationas to what this means for teaching and learning. From early on in its release, multiple newsarticles point out the many ways students are using it in classes and how instructors have had toadapt—from changing how and where students write drafts or shifting to oral exams [1], tofocusing on thinking processes or return to pen and paper [2]—and the debate around its use inhigher education has intensified with continued uncertainty. The Digital Education Council(DEC) Global AI Student Survey, which ran in 2024
and identifying as people of color. This paper attempts to shedlight in this area.Conceptual FrameworksOur conceptual framework is underpinned by the hidden curriculum and funds of knowledgetheories with intersectionality to elevate systems-driven implications.Hidden curriculum. Villanueva et al. write “Within educational and professional environmentsand settings, individuals don’t just learn ‘what is formally being presented . . . but alsoaccumulate other hidden lessons in the process’ [27, p. 1550]. The hidden curriculum inengineering is likely a significant factor in enculturating and socializing people into themeritocratic, hegemonic, and masculine norms of engineering [27]. Hidden curriculum duringgraduate education is receiving
(mean = 37.6) and post-measure (mean = 83.2) on a 100-point scale, a significant increase.Despite the large increase in self-efficacy, increases in self-reported identity as a “maker” or“engineer” did not achieve significance, whereas a small but significant increase in sense ofbelonging was observed. Students’ ability to successfully build a circuit with no assistance basedon its schematic in a lab practical exercise did not correlate with student-reported self-efficacy,suggesting that students may factor in social support from peers as part of their ability toapproach future electronics projects. This work provides insight into an understudied group inengineering education: non-majors in an elective course. This sort of outreach course is
meeting room, with moveable chairs and tables, a projector andFigure 1. The Bioengineering, Society & Policy lab at ASU screen, a large white board, and – importantly – a coffee machine and snacks. This space servesmany purposes: project meetings with colleagues and student researchers, a classroom (when classsizes are small), a venue for hosting faculty writing groups, occasionally a space for doing yoga.Having spent 10 years “alongside” BME colleagues [18], Author 2 has had many informal andlong-running conversations about the ups and downs of running a lab. Over the years, somecommon features across PIs and career stages seem
analysis [25, 26]. Specifically, we engaged insix phases of thematic analysis, including (1) data familiarization, (2) generating codes, (3)constructing themes, (4) reviewing themes, (5) defining themes, and (6) writing up the results toguide data analysis. We executed our analysis by reading through each semi-structured interviewtranscript and open-ended survey response and then rereading to identify quotes of interest. Next,we engaged in two rounds of coding using our conceptual framework (e.g., the ECSJ pillars) as apriori codes. We used thematic analysis as a guide rather than a prescriptive method. Initialcodes and transcript quotes were documented using a spreadsheet software program individually.Then, we discussed them through peer