Education. Her research interests center on the concept of sense of belonging, peer and faculty interactions, and graduate education. ©American Society for Engineering Education, 2025 A Scoping Review on Non-Majority Students’ Sense of Belonging in Engineering and Computing Education: Uncovering the Barriers, Supports, and Contexts AbstractThis work-in-progress theory paper discusses the preliminary findings of a scoping literaturereview on non-majority students’ sense of belonging in engineering and computing education,focused on barriers, supports, and contexts. A substantial body of research underscores thesignificant impact of sense of belonging on
grounded inreality (isentropic efficiencies had be based on what real powerplants were currently using). Sincethis was solely a paper design assignment, the budget for this plant was assumed to be unlimited.Students were asked to provide at least a general idea of the size and footprint of their plant as wellas possible locations for it to be built. Adding a flare of competition to the project an additional 10points was awarded to the student(s) who designed the most efficient cycle each year. Studentswere also required to take the paper to the university student writing center. The goal of thisappointment was to help the students with the overall quality of their writing. Most students usedtheir appointment for help with overall structure
technical writing skills, which are often not demonstrated in traditional exams. We emphasized developing connections that can facilitate belonging. We focused on buildingconnections between students and four other factors: the professor, the course content, the peers,and the ChemBE major. Connection between students and the professor can be fostered throughthe professor’s display of care and support [17]. Understanding the relevance of the courseworkthrough real-world applications can promote connections with the course content and the major.Participating in cooperative learning can provide opportunities to interact with peers and facilitatepeer connections.Supportive Classroom in Cell Biology for Engineers During the course introduction, the
3 Course ObjectivesENGR 4150 is taken concurrently with ENGR 4350 (Fluid Mechanics; three-hour lecture format),and the main objective of ENGR 4150 is to supplement the lecture course. This is evidenced in thecourse’s catalog description: “This lab investigates the fundamental concepts of fluid mechanics with hands-on experiments in the areas of fluid statics, viscosity, buoyancy, Bernoulli’s equation, friction losses, and the concepts of lift and drag.”All course activities were designed with this description in mind. Three additional objectives arealso emphasized: technical writing, uncertainty analysis, and experimental design. The followingsubsections describe each of these
GPTZero and TurnItIn claim to identify whether a student’s writing was One key aspect of this paper is the distinction betweenproprietary and open-source large language models. Proprietary produced by generative AI, but they are highly inaccurate.models, such as OpenAI’s ChatGPT, are often considered less They tend to flag simple or predictable writing as AI-secure and privacy-invasive compared to open-source generated. Studies show that such false positives occur morealternatives like Meta’s Llama. Educating students on the frequently among certain groups, including
likely are you to consider participating in research activities if you are given the chance? (1-5 slider scale) 9. I can conduct scholarly research on a topic. (1-5 slider scale) 10.I can explain research findings in my own words. (1-5 slider scale) 11.I can cite references appropriately in my research. (1-5 slider scale) 12.I work well in project teams. 13.I am comfortable taking feedback on my work from my peers. (1-5 slider scale) 14.I am confident that I can name three campus resources that are available for me (1-5 slider scale) 15.I know what it means to be interdisciplinary. (1-5 slider scale)Survey Block 2: Writing Assignment 16.Rate the impact that you believe your course writing assignments will have
2 SpeakersEach speaker will introduce themselves [Name, position, academic training] 3This project is funded by the Archival Publication Authors Workshop.“The aim of the APA1 is to facilitate growth in manuscript writing skills and an understanding ofthe review process, leading to the development and refinement of new manuscripts that areintended to be submitted for publication in a peer-reviewed journal. The APA willinclude instructor-led sessions and panels and interactive breakout sessions with writing teamsand mentors. Specifically, the workshop was designed to:1.Use ASEE journal solicitations to contextualize content;2.Challenge teams to draft different
improve.Examination of the model’s utilization in empirical research may provide information about howresearchers interpret and draw upon of the publications, as well as the nature of the influence ofthe theoretical model [4], [5], [6]. The peer-reviewed publications will be analyzed for theirpurpose and relation to engineering education. The nature of the citation instances will beanalyzed for their primary purpose in empirical research. This analysis will explore theinterpretation and context of the theoretical model and its relations to mathematics andengineering education. Salient findings from the citation analysis may focus future researchconcerning the transition from high school mathematics to college mathematics.Summary of theoretical framework for
developing a growthmindset toward learning. It also includes examining methods to enhance preparation and reduceanxiety and stress by anticipating future obstacles. The remaining course-level outcome (C04) isrelated to peer study meetings, which occur throughout the entire semester. Peer study meetingsrequire students to organize small group study sessions in preparation for each of theirengineering, chemistry, and math exams. Teams of three are assigned to prepare and submitagendas for each study session. They then carry out their agendas on pre-scheduled class daysdesignated for peer study meetings.Table 1: Summary of concepts included in each unit of the course. Habits of Professionals Habits of Learning Habits of
with faculty affiliated with the program,and peer/near-peer mentoring. At the time of data collection, the program was in its third cohort.Participants and Recruitment: All participants in this study are first- or second-year MS studentsenrolled in an engineering field at the institution of focus in this study. All M.S. students arerequired to do research and write a Master’s paper or thesis. All participants for this study recruitedwere part of the SSTEM, although participation in this particular study was optional. IRB approvalwas obtained for the entire project and all data collection; the interviews collected and analyzed inthis study are part of the broader engineering education research plan in the funded SSTEM project.Six students
diminish students' ability to think critically and solve problemsindependently. Additionally, AI may not always provide the communication and decision-making. Assignmentscontextual understanding needed for complex decision-making, that promote peer engagement and knowledge sharingrequiring human judgment and expertise. As such, it is contribute to a more robust learning experience. Groupimportant to evaluate whether AI enhances or undermines the projects, case studies, and interactive discussionslearning experience within these courses. should encourage students to engage with each other
colonialism” [3, p. 19]? As settler engineeringeducation researchers based in the setter colonial nation now called Canada, we write this paperas a process of ‘pausing’ [9] to discuss the tensions we have experienced in ‘Indigenizing’ or‘decolonizing’ efforts in engineering education in our Canadian and American universityinstitutional experiences.We structure this paper as a dialogue between the first two authors, Jess Tran and Jessica Wolf, toreflect on our engineering education experiences, as recent Canadian and Americanundergraduate and current Canadian graduate students. This written dialogue is an artifact of themany dialogues we have engaged in wrestling with these tensions, including severalconversations we had as an author team. We reflect
scientificresearch, living in Sweden, Swedish culture (inside and outside the lab), AI, data science, andalgorithm bias. Four of the Zoom sessions in the training series are dedicated to student-ledjournal club discussions where students present a paper published by their host lab and fieldquestions from the PI and peers. The journal club activity is designed to teach IRES students themethods, background and vocabulary that serves as the basis for their summer research project.Asynchronous coding tutorials: All students admitted to the program have previous computerprogramming experience, but additional training materials is assigned to ensure student success.Given that students work with computational techniques specific to their projects
stakeholder groups.Introduction & Literature ReviewNationally, there are widely known, persistent inequities in STEM student outcomes. This studyhas its origins in concerns about inequities, but concerns were accompanied by a skepticismabout simplistic diagnoses of the problem. Inequitable student outcomes have strong associationswith race and family income, which can be proxies for access to quality secondary education andparental college achievement [1], but there are other factors at work. Students pursuing STEMmajors in college often suffer even worse outcomes than their non-STEM peers, with studentsfrom underserved groups experiencing much lower retention rates (i.e., retention in a STEMmajor and retention in college generally) and
evaluation andlearning assessment with peer students in ECE. As a proof of concept, this paper explored howstudent-led development of VR content and experience might offer a solution to a commonobstacle faced by many STEM educators who are interested in exploring VR, which is the lackof readily adoptable VR content. This study contributes to better understanding the role andimpacts of learner-as-creator/co-creator in engaging student learning in educational technology-integrated learning environments.1. Introduction & backgroundThe objective of this study was to explore student-led development of virtual reality (VR)applications as an alternative solution to enhance student learning and engagement in the field ofelectrical and computer
Stanford website were also examined [8]. Seeking to tailor the work to agraduate student population, the lead author also met virtually with Dr. Laura Schram, Directorof Professional Development & Engagement in the Rackham Graduate School at the Universityof Michigan (UM), who developed a 6-session optional, non-credit bearing course for doctoralstudents and postdoctoral scholars in any discipline at the UM [9]. Dr. Schram was instrumentalin selecting exercises from the DYL book, leading to pre-work and in-class activities for a 90-minute studio offering.Following a peer-to-peer approach, new instructors observed a more experienced instructor fortwo studios. New instructors may also engage in micro-teaching, where they teach one of thephases
the camera module to outputimages in the proper format and configuring the WiFi module to accept images over SPI. Then,the WiFi module is instructed to connect to the internet, and the program waits until theconnection is complete. After a connection is made, the firmware waits until a user connects tothe webcam streaming website (i.e. a client opens a websocket connection to the server). Oncethat happens, the firmware grabs images from the camera module, writes them to the WiFimodule, and streams them to the website.While all of these operations are looping, there is an asynchronous button that allows the camerato be provisioned to a new WiFi network. The firmware must detect this press at any time and putthe WiFi module into provisioning
. The research shows that using AR and gamificationimproves young children's learning, especially in alphabet writing [14]. Also,Thompson et al. conducted a comprehensive, multi-year study to identify andcharacterize educational Augmented Reality environments suitable for students ofvarious ages and skill levels. Throughout the research, the students, parents, andteachers actively collaborated to plan, construct, and enhance six AR prototypes. Basedon their student’s positive outcomes, these kinds of software can be used in classrooms.[15]. Students need to be active participants in their learning, fully engaged inexploring the various aspects of 21st-century education. Moreover, there is a necessityto enhance the demanded qualifications
students to explore and critically examine topics rarely addressed in traditionalcoursework. By engaging with readings about the history of engineering, students areempowered to re-evaluate their own positions within the field, recognize the diverse experiencesof others, and gain a broader understanding of the historical and societal contexts that shape theirwork. These discussions, combined with reflective writing and opportunities for personal andpeer-to-peer connections, facilitate deeper processing of the material. Without these interactiveelements, the impact of reading alone would be significantly diminished. Pláticas are
, “A strategic blueprint for the alignment of doctoral competencies with disciplinary expectations,” vol. 32, pp. 1759– 1773, Jan. 2016.[42] C. G. P. Berdanier, “Linking current and prospective engineering graduate students’ writing attitudes with rhetorical writing patterns,” J. Eng. Educ., vol. 110, no. 1, pp. 207–229, 2021, doi: 10.1002/jee.20368.[43] C. Hixson, W. Lee, D. Hunter, M. Paretti, H. Matusovich, and R. McCord, “Understanding the structural and attitudinal elements that sustain a graduate student writing group in an engineering department,” WLN J. Writ. Cent. Scholarsh., vol. 40, no. 5–6, pp. 18–26, Jan. 2016.[44] M. S. Artiles, N. Huggins, H. M. Matusovich, and S. G. Adams, “Advisors, peers, and
]. Each student works directlywith a faculty member throughout the entirety of a course, attending at least one class sessioneach week (in most cases in our program, they attend all class sessions). Additionally, they meetwith the instructor outside of class, either weekly or biweekly, and meet in groups with peers andprogram facilitators for mentorship, reflection, and guidance. Students are recruited primarily byword of mouth. This includes recommendations from instructors, students in the program, andstaff members who work directly with students and have attended presentations about theprogram (including our academic success center, academic advisors, and cultural center staff).When students express interest, we interview them to help them
course assignments are provided in Table 1.Table 1: Example projects completed by students in EF327/TPTE115 [adapted from 9] Project Description Examples Mini-Teach Students choose a topic and have 5 (1) An explanation of computer minutes to teach the class about their sorting algorithms chosen topic. Each student is provided (2) An overview of the with feedback from peers and instructors. engineering design process Community Students work in small groups to select (1) Think Like a Computer Outreach engineering-focused activities to use to activity developed for an
established research labs thatwould provide peer mentoring and a CoP for the incoming ECHS students. Leveraging existinglab infrastructure for professional, technical skill, and community development was ideal forremoving additional burden to those facilitating the program, both at the ECHS and universitylevels. The faculty mentors’ preparation and training played a critical role in creating an inclusive,effective research environment. For example, mentors tailored their feedback to meet students attheir developmental stage. They focused on practical skills like poster presentations, writing forresearch, and hands-on laboratory experimentation. One participant highlighted the value ofthese experiences: “This REU was significant in me feeling
focus of the literature. Within the first monthsof its launch, it was found that ChatGPT could pass law school exams, though it only managed aC+ [20]. This is just one example of the deluge of papers describing how large language modelscan perform reasonably well on traditional examinations (e.g., [21], [22], [23], [24], [25]). Thesemodels are trained using large and diverse sets of writing and employ statistical procedures topredict a response to a statement or question, which can lead to surprising coherence and theappearance of analytical reasoning.In STEM fields, where communication is less in written short responses and more often acombination of diagrams and equations, generative AI tools have seen uneven success in problem-solving. For
” requirement. Students are grouped into teams that design and execute collaborative experiments within their own kitchens and then pool the data to draw conclusions. This “science” work then forms the basis of individual students’ food engineering designs for new and improved food products. The course uses three iterations of this experiment-analysis-design loop as its primary instructional and assessment mechanism. This work is complimented by lectures and supplemental video material as well as reading and re ective writing. This paper describes the course outcomes, design, and delivery, and concludes with portable takeaways for those seeking to create similar courses at their own
focus groups. The two questions posed to thestudents were:Q1: While studying for the mid-term exams and completing homework assignments, whatresources did you find helped you the best?Q2: During the design portion, what resources did you use to reference theory & to troubleshootin BioWin?FindingsThe following are the results of the Course Feedback & Resources Survey. Each question wasrated using a Likert Scale ranging from 1 to 5, with 1 corresponding to 'Strongly Agree' and 5corresponding to 'Strongly Disagree'. This survey had an 86% response, with 19 students of 22from the cohort filling it.Mode of Instruction: The preferred mode of instruction was in-person, with most studentspreferring to work with their peers during class to solve
University. Dr. Ellis has a long-time interest in software engineering education and has been interested in student participation in Humanitarian Free and Open Source Software (HFOSS) since 2006. ©American Society for Engineering Education, 2025 What’s Your Why?Helping students define their explicit value proposition using a 3-minute pitchAbstractArticulating your value and defining identity within a learning community can be a challenge forundergraduate students. Developing appropriate communication skills and strategies to improvecan be taught using peer-, self- and faculty-feedback tools. This is done through providingopportunities to fail and iterate. An appropriate
relationships withpotential recommenders than their peers [3]. Even for students who do develop suchrelationships, there is no guarantee that their accomplishments will be viewed equally. Socialpsychologists warn implicit bias is ubiquitous, even among individuals who aim to treat otherswithout prejudice, and especially in circumstances that involve high-stakes decisions [4].Previous research on LORs, conducted primarily on small samples from medical residency andfaculty searches, suggests that the language used in LORs for qualified applicants from groupsunderrepresented in STEM can differ from groups than aren’t underrepresented in STEM. Forexample, using dictionaries of words and phrases with positive and negative associations, somefind that letters
toproduce peer-reviewed papers but to provide students with the experience of tackling open-ended, research-oriented questions, mirroring the challenges encountered in graduate-levelstudies.Examples of ChatGPT EnhancementsInitially, the curriculum did not include formal programming or MATLAB instruction, whichposed significant challenges for students. Many struggled with fundamental tasks such aspreparing datasets for analysis in MATLAB’s Regression Learner Toolbox. Data preprocessingtasks, including variable elimination and row or column manipulations, proved difficult andtime-consuming for both students and instructors. These bottlenecks consumed countless hours,diverting focus away from meaningful research and exploration of machine learning
outputs from recently developed AI tools is a quite newchallenge that research communities are just now forming to address [23]. An investigation ofAI accuracy found that ChatGPT 3.5 proved, “…generally good at writing concepttopics…”[24]. One reasonably classifies a literature survey task as a concept topic, suggestingthe potential for accurate results from AI. However, this work uses Gemini 1.5 Flash, notChatGPT 3.5. Verhulsdonck and coauthors introduce a subjective means of evaluating theaccuracy of AI generated content independent of the particular tool [24]. Their HEAT method,an acronym formed from Human experience, Expertise, Accuracy and Trust, attempts tosubjectively gage AI output credibility. In this work’s contents, the H and E terms