societal contexts. SO 5. an ability to function effectively on a team whose members together provide leadership, create a collaborative and inclusive environment, establish goals, plan tasks, and meet objectives. SO 7. an ability to acquire and apply new knowledge as needed, using appropriate learning strategies.The Engineering Professional Skill Assessment MethodThe EPSA method focuses on groups of students discussing a complex, real-world scenario. Thisdiscussion-based performance assessment has two components: (1) a student discussion guidedby a 1-2 page scenario that presents a contemporary multi-faceted engineering problem in acomplex societal and environmental context with no clear-cut solution along with a series ofquestions to prompt
? Why? • How would you explain the concept of neurodiversity now (Year 5)? Focus Course Interventions Example • What are some of the aspects of the course that you have redesigned? Questions • Why did you decide to implement these changes? • Have you changed, added, or removed anything about your redesigned course (since last year)? • What formats for delivering instruction have you used this year? Focus Course Redesign Process Example • How would you describe the process of planning inclusive instruction? Questions • What support or resources supported you in the redesign process? • What limits or
plug-and-play platform andaccompanying infrastructure to teach cybersecurity does not exist, unlike, for example, theubiquitous electronics lab bench used for teaching circuit design. As a result, there are few truevetted models of teaching cybersecurity, especially for supporting beginner-level students whoare just starting to interact with the field. Even seemingly simple tasks, such as planning in-classactivities, can be difficult to manage without extensive forethought and secure infrastructuredevelopment; hacking can get quite messy at times and could potentially pose security risks forthe university. Both faculty and staff must coordinate to find holes in the infrastructure and stopstudents from doing anything potentially dangerous
evaluate students’ use of LLMsduring the self-study task. We aimed to answer our research questions in the context of these tasksby designing an experiment in which task instructions were modified to permit or prohibit the useof generative AI during their completion. To answer RQ2 in particular, we categorize the assignedtask and the chatbot usage data using the Winne & Hadwin model of SRL [20]. 22.1 The Winne & Hadwin ModelThe Winne & Hadwin (W&H) model adopts the perspective of studying and learning as informa-tion processing tasks and proposes four basic, weakly recursive phases of learning: (1) task defini-tion, (2) goal setting and planning, (3) enacting study tactics and
Paper ID #46850Incorporating an Entrepreneurial Mindset in Online Introduction to EngineeringCourses: A Study of Value Creation ˜ Arizona State UniversityDr. Kristen Pena, In her role as Senior Program Manager, Learning Initiatives for the Ira A. Fulton Schools of Engineering (FSE) Learning and Teaching Hub (LTH), Kristen Pe˜na plans, develops, and supports a variety of faculty professional learning initiatives, including workshops, communities of practice, quick-reference guides, and other learning opportunities for engineering instructional staff and faculty. She also teaches undergraduate and graduate
gap.The laboratory provides them a chance to experiments with measurements of static and stagnationvalues of two important parameters, namely pressure and temperature, in high-speed flows and torealize that common temperature measurements are not always what they are supposed to representin theory.IntroductionA course in experimental methods was previously taught jointly for students in the mechanicalengineering and aerospace engineering programs. This second-year course provides anintroduction to experimentation in engineering. It aims to develop key skills such as test planning,understanding measurement chains, analyzing the metrological characteristics of instruments, aswell as identifying measurement errors and propagating uncertainties
—something especially valuable forthose who may feel their perspectives are not typically centered in academic spaces.Additionally, it is important to remain aware of how communication styles can inadvertentlysilence voices. When students have internalized that their contributions are undervalued, theymay speak less—not from lack of insight, but from prior learned restraint. Attuning to thisdynamic is key to creating environments where every student can participate meaningfully.2. Think in Terms of PossibilityIn collaborative planning sessions with new institutional partners, I often hear limitations surfacequickly: “We can’t because…” or “We don’t have the resources to…” These statements, thoughwell-intentioned, often reflect conditioned patterns
and all life on Earth,” (Planetary Health Alliance). InSeptember 2023, the United States Bureau of Labor Statistics updated the formal definition ofjob code 17-2081 Environmental Engineers. The prior definition noted that, environmentalengineering was defined as, “research, design, plan, or perform engineering duties in theprevention, control, and remediation of environmental hazards using various engineeringdisciplines.” The current definition now includes that, “environmental engineers use engineeringdisciplines in developing solutions to problems of planetary health.” The purpose of this panelpresentation is to discuss the meaning of planetary health, and how environmental engineerssolve the problems of planetary health by addressing two
performance. • Better Grades Due to Fewer Errors: o 58% of students strongly believed, and 16% believed that using MathCAD helped them avoid calculation errors and improve their grades. • Use in Other Courses: o After learning MathCAD in the MCS course, 74% of students used it in other classes (either multiple or individual courses). • Future Use: o 79% of students planned to use MathCAD in future studies or work, demonstrating a high level of satisfaction with the software and a desire to continue using it in professional practice. • Overall Satisfaction: o 74% of students liked the application of MathCAD in the class, while only 5
reasoning tends to be vastlydifferent. Mastering the material is frequently a means to an end and not an end in itself.Demonstration of mastery leads to job opportunities and paychecks. The student can be forgivenfor this; this focus has been part of the university's marketing plan since first contact with thestudent by advertising job placement rates, median mid-career salaries, and return on investmentmetrics. While the underlying motivation differs for precisely why learning the material isvaluable, at least the agreement remains.Then, it is incumbent on the instructor to assess the amount of learning that has occurred.Modern neuroscience tells us that learning is a change in the synaptic wiring of the brain.Connections are made or strengthened
thedatabase will also be provided.Task 3: Summary and Results Presentation: The project results will be communicated with theCT DOT. In addition, a research plan involving a long-range duration of data (e.g. over 10years) combined with other pertinent databases (e.g. environment) will be proposed andsubmitted to the CT DOT applying for external funding. The student will contribute to writingthis proposal and other research paper.The students will walk through each stage of this analytics pipeline that enables them to collect,clean, understand, model, and report data analyses. By paying close attention to data patterns,the stories behind outliers, relationships among data sets, and the external factors that may haveaffected the data, it is expected
students with the opportunity to independentlyconceptualize, build, and refine a circuit design to meet specified constraints, mimickingreal-world engineering tasks.Figure 2: The iterative lab progression framework emphasizes planning, simulation, and build-ing/testing phases, supported by analysis and communication.Data CollectionQuantitative DataThe ISE measurement tool developed by Carberry, Gerber, and Martin was utilized to collectself-reported quantitative data at both the beginning and end of the course [7]. This instrumentconsists of 29 items that comprise eight factors as shown in Table 2. Please refer to Appendix Afor the full measurement instrument. Exploratory factor analysis for this instrument showed factorloadings ranging from 0.715
children to evaluate the application's effectiveness in a real- world setting. Then, structured trials to collect data on the impact of the application on children's speech development. After collecting the data, we plan to refine the application to improve it. By leveraging the capabilities of AR and AI, this application aims to provide a novel, engaging, and effective tool for speech therapy, supporting the early development of speech skills in children with speech delay. 5 Conclusion This work in progress highlights the potential of using AR and AI to create innovative tools for speech therapy. By making speech practice interactive and fun, the application aims to motivate children with speech
evaluated one LLM (Claude 3.7 Sonnet). Future work shouldtest more models, explore hybrid human-AI feedback systems, and investigate long-term impactson learning. We also plan to develop better tools to help students interpret and apply LLMsuggestions effectively.References[1] Fagbohun O, Iduwe NP, Abdullahi M, Ifaturoti A, Nwanna OM. Beyond TraditionalAssessment: Exploring the Impact of Large Language Models on Grading Practices. J Artif IntellMach Learn & Data Sci 2024, 2(1), 1-8. DOI: doi.org/10.51219/JAIMLD/oluwole-fagbohun/19[2] Morris, W., Holmes, L., Choi, J.S. et al. Automated Scoring of Constructed Response Items inMath Assessment Using Large Language Models. Int J Artif Intell Educ (2024).https://doi.org/10.1007/s40593-024-00418-w[3
performed better than those who had traditionalassessments. This study is considered a work in progress, with plans for future investigations thatwill provide a more comprehensive analysis using both quantitative and qualitative methods tofurther explore the subject.Data collection and analysis were conducted using Qualtrics software to distribute the surveys,with the responses being imported into Excel for processing. A visual coding system was used tocategorize the open-ended responses, assigning colors to reflect the different tones of thestudents' opinions, such as green for positive, yellow for moderately positive, and red fornegative answers [51]. From this categorization, key ideas were identified to reflect the generalattitudes of students
suggestions. The majority of studentshad no suggestions, but among those who did, common themes included the following-flexibility in selecting the group members instead of having the instructor assign them randomly,incorporating peer grading to ensure fair assessment and accountability, and offering extra creditactivities to help strengthen group bonds.Conclusion In my experience, class family model has proven to be an effective strategy for fosteringcollaboration, improving learning outcomes, and building lasting relationships among students.While challenges like uneven work distribution can arise, they can be mitigated through clearguidelines and proactive communication. Based on these experiences, I plan to refine theapproach further and
and encourage integration into coursework. The evaluation plan willincorporate pre- and post-implementation surveys, grade distribution analysis, and focus groupsto assess changes in teaching practices, student understanding, and engagement.The anticipated outcomes include an increase in faculty adoption of lab models, measuredthrough survey results, and the development of at least three actionable recommendations forimproving the models and instructional materials. Additionally, we expect to see improvementsin student performance, as evaluated through grade distribution analysis in courses utilizing thelab resources. While exact percentages cannot be determined at this stage, the impact will bequantitatively assessed during and after
) database, for manufacturing operations. Theresults developed through this project potentially can be used in the “Manufacturing Automation”course to teach students concepts related to the MTConnect.The research team plans the future research as follows. 1) To further develop the software withdata analytics capabilities for other applications such as quality control, system monitoring, etc. 2)To scale up the current system from a single machine to a fleet of machines such as a combinationadditive and subtractive manufacturing machines. Ideally, the team visions to have all the CNCmachines and 3D printers in the School machine shop to be integrated using MTConnect and/orOPC UA standards. Such an integration provides a prototype of “Smart Factory
(APICS), the Transformation Team on the American Society of Engineering Education (ASEE), the Research Committee of Intermodal Freight Transport committee, Freight Transportation Planning and Logistics committee of Transportation Research Board (TRB) among others. Dr. Sarder chaired the Industrial & Systems Engineering Annual Conference in 2016 and 2017, and the Engineering Lean Six Sigma Conference (ELSS) in 2013. ©American Society for Engineering Education, 2025NSF RET: Empowering STEM Educators and Revitalizing Manufacturing in the U.S. MidwestAbstract The National Science Foundation (NSF) award (2206952) establishes a new ResearchExperiences for Teachers (RET
students, especially in large introductorycourses, which is where many underrepresented students who planned to major in engineeringdecide to leave the major. BME programs may be particularly susceptible to losing students inprerequisite coursework, as students must take prerequisite courses in the typical pre-engineeringareas, such as math and physics, in addition to extensive coursework in chemistry and biology.ResultsWe distributed a survey to 85 BME students and received 40 responses, including upper-divisionstudents already in our major and lower-division pre-major students who are currently enrolledin an introductory prerequisite course in a different department. Of these, 10 volunteered to sharerepresentative examples of their notes, and 4
courses.However, these skills are cognitively difficult, frustrating, and are sometimes not clearly linked tostudents’ perceptions of engineering[1], [2]. Self-efficacy and expectancy-value theories havebeen linked student persistence, achievement, and future plans[3]. Among engineering students,computing skills are a strong influencer of confidence and self-efficacy [4]. Prior research withstudents learning to program in required first-year university courses demonstrated that baselinemotivation for learning – specifically, their self-efficacy and utility value – varied significantly.One recent study demonstrates that students in computationally-focused majors have higher self-efficacy [5]. A multi-year explanatory mixed-methods project set out to
thinking aregiven by Figure 2. These dimensions include (1) an ability to produce multiple solutions to aproblem, (2) an ability to develop action plans, (3) self-confidence, (4) optimism, (5) persistence,(6) team-oriented thinking, and (7) future focus. 95.0% 90.0% 85.0% 80.0% 75.0% 2022 2023 2024 Yr 1 cohort Yr 2 cohort Figure 2 - Percentages of students from program years 1 and 2 reporting an association of "Strongly Agree" or"Agree", or "A lot" or "A
Fall 2021 100 3.310 0.646 570 3.216 0.605 1.412 0.158 Fall 2022 106 3.164 0.602 606 3.118 0.628 0.699 0.485 Fall 2023 114 3.285 0.563 529 3.170 0.594 1.891 0.059ConclusionsThe increase in sense of belonging among our LI students is promising. Student interviews mayprovide some insight into the reasons behind this. In addition, we plan to use data on GPA andretention statistics to investigate RQ2: Is sense of belonging and/or grit correlated with retentionand/or academic performance among our students?Future work also includes analysis of the longitudinal data collected from our scholars to addressand RQ3
. Thoseparticipants reported that they initially joined the NRT planning to complete a master’s degree;however, due to their positive experience with the UK NRT, particularly with transdisciplinaryresearch, they decided to pursue a doctorate.4. ResultsA total of five themes emerged from the analysis of the 10 interviews, namely: 1) the UK NRTinfluenced participants to change their education goals; 2) several UK NRT componentsprepared trainees for the job search and the workplace; 3) graduates cite the UK NRT as the mostinfluential factor behind their career successes and aspirations; and 4) the perspectives of hiringmanagers and supervisors on NRT graduates.4.1 The NRT influenced participants to change their education goalsMost trainees learned about the UK
career plans. Similarly, with respect to Engineering Identity, a 13-item surveycalled the Engineering Identity Scale (EIS) taken from Godwin, 2016 [3] was administered to 26 studentsin the Fall of 2022.Preliminary Findings and DiscussionDepicted below in Table 1 are percentages of students (N = 33) who either “agree” or “strongly agree”with various survey statements. As is evident from these responses, the S-STEM scholarship isinstrumental to help students reduce their job hours, and presumably enabling them to spend more time ontheir studies. Similarly, S-STEM scholarship has helped them in their professional preparation anddevelopment and in community building.Another survey indicates how the S-STEM program has benefitted them in other ways
was supported by the University of Louisville (UofL) and funded by NSF IUSE: EDU, Award #2335725.Nevertheless, any view, opinion, findings and conclusions or recommendations expressed in this material are those ofthe authors alone. Therefore, neither UofL or NSF does not accept any liability in regard thereto.References [1] V. Tinto, Leaving college: Rethinking the causes and cures of student attrition. University of Chicago press, 2012. [2] V. Tinto and J. Cullen, “Dropout in higher education: A review and theoretical synthesis of recent research,” Office of Education (DHEW), Washington, D.C. Office of Planning, Budgeting, and Evaluation, vol. 53, no. 9, p. 100, 1973. [3] J. Bean and S. B. Eaton, “The psychology underlying
Excellence in Teaching Award at Thayer. She recently co-designed and piloted a Foreign Studies Program focussed on green and sustainable engineering in collaboration with the German department at Dartmouth. At Thayer she furthermore leads an AAU funded Teaching Evaluation Project to develop, implement, and document a more effective and holistic teaching evaluation system. Petra has served as Associate Dean for Diversity and Inclusion at Thayer since 2020. In this role she plans, leads and oversees diversity and inclusion efforts at Thayer and in coordination with other organizations internal and external to Dartmouth. Thayer was recently recognized with the ASEE Silver Diversity Award for our progress in increasing
. • Facilitation of Course Learning Objectives (CLOs): Aligning EBIP strategies with course goals, whether syllabus-defined or personal teaching objectives. • Acclimation to EBIPs: Growing comfort and expertise in EBIP use.From these areas, themes and sub-themes emerged that reflect strategies and challenges in theEBIP adoption process. Key themes include: • Responsiveness: Adapting EBIPs to classroom dynamics through awareness, adaptive planning, and targeted support. • Succession: Sustained, varied use of EBIPs, often sequenced for greater impact. • Guidance: Scaffolding student learning through peer support, collective understanding checks, and clear instructions. • Organization: Proactive course structuring to
color palettes compatible with the needs of users with color vision deficiency (CVD), alongwith subtitles and audio narrations.Progress and ResultsThis 36-month research project commenced in September 2024. Currently, the research team isfocused on two key activities, both closely aligned with pedagogical and technologicalinnovations. The first activity involves designing the CeLens mobile application based onhuman-centered design principles. A preliminary prototype of the application has beendeveloped, and the team is now planning to engage users to finalize the platform’s design. Thesecond activity centers on preparing image and audio libraries of construction components tosupport the development of the image/audio analysis system. This task
greatly benefitedscholars. In the words of one of them: “I like the one-on-one meetings with my mentor whoprovide academic and professional guidance. Not only that, but being able to discuss my thoughtsand opinions on my career and topics related to my major. I am also grateful for the opportunitiesto be able to travel to different places such as the upcoming out-of-state conference in Chicago tomeet new people and get a sense of what the STEM realm has to offer.” As a result, the programhas become more popular, with an increase in the number of applicants every year.3 ResultsA confidential IMMERSE in STEM scholars feedback survey was administered in collaborationwith the Skyline College’s Office of Planning, Research, Innovation and