unreliable11) How would you evaluate ChatGPT 4.0's explanations of mechanics problems? a. Excellent, very clear and detailed b. Good, mostly clear and detailed c. Neutral d. Poor, unclear or missing details e. Very poor, confusing or incorrect12) Would you recommend using ChatGPT 4.0 for mechanics-related problems to otherstudents? a. Yes b. No13) Do you plan to continue using ChatGPT 4.0 for learning engineering concepts in the future? a. Yes b. No14) What are your suggestions for improving the use of ChatGPT 4.0 in solving mechanicsproblems?15) What specific learning goals or objectives do you aim to achieve when using ChatGPT 4.0for engineering-related topics?16) Do you find that ChatGPT 4.0 helps you achieve a deeper
devising a search plan,preliminary searching was undertaken using Google Scholar to better understand the terms usedto describe evidence synthesis services and service development. Once the preliminary resultswere reviewed, the team determined that they would search general literature databases,engineering literature databases, and library and information studies literature databases forfurther results. The team determined search assignments based on each member’s ability toaccess databases at their institution. The databases searched were: • Dimensions* • Web of Science • Scopus • Engineering Village, including Compendex and Inspec • Library Literature and Information Science Full Text • Library, Information Science and
week). Thus, we have been positioned to compare their baseline skills and career against where they ended, to assess change over time, mindful that part of learning in these research internships also seems to involving at times higher expectations for what they should know to be considered skilled in engineering competencies. The evaluation team including the second author gathered (a) students’ self-ratings of their perceived competence and engineering identity, (b) responses to a hand-written affirmation exercise on sense of belonging see [12] [13], and (c) individual interviews with interns to investigate their research internship experiences and future education and career plans. These occurred each year, with each cohort of
Paper ID #46433Novel Testbench and Controller for Teaching Python and Robotics in MechatronicsEngineering Education (Complete Paper)Dr. Mohamed Gharib, Texas A&M University Dr. Mohamed Gharib is an associate professor and program chair for the Mechatronics Engineering Technology and STEM Education programs at the School of Engineering at Texas A&M University. He is an expert in designing, prototyping, modeling, and simulation of robotic systems. Also, he is a STEM education specialist and program developer, including planning, developing, integrating, and teaching STEM programs for K-12 students through university
, this structure would allow for much easier scaling, discussed inSection 3.4, as it takes much less coordination between graders to gauge just three levels ofcomprehension.As a further validation of the efficacy of the Deep Dives, a long-term study of knowledgeretention would be necessary. Such a study would require at least two sections of this introductoryclass being taught, one with the Deep Dives, and one without. Then, a longitudinal study could becreated to track knowledge retention at various points in the future.Finally, this form of assessment opens the door to much further study, which will requiresignificant rigor and planning. For example, there is a necessary conversation to be had regardingassessment in the age of ChatGPT [19] and
thanmemorized answers. Additionally, comparing exam outcomes when a CodeWriting CA isassigned as homework versus when it is not, may provide useful insights into how prior exposureinfluences mastery and retention.We aim to explore how scaffolded, auto-graded activities can better support students withvarying levels of engagement and preparedness. While our current approach effectively aidsproactive learners, we recognize the need to address the challenges faced by students who maystruggle to engage independently. One potential improvement is to incorporate more explicitfeedback mechanisms that encourage students to seek help when needed, reinforcing thatreaching out for clarification is part of the learning process. Additionally, we plan to examinehow
participants achieving their communication goals and80% noting increased task efficiency. The application’s intuitive design also received a 90%positive rating for usability and interface clarity. Comparative analysis with traditional PECSbooks shows that PictoConecta provides a slight performance advantage, particularly for usersrequiring less support.Keywords: Autism Communication, planning activities, Mobile Application, Pictograms,Technology Acceptance Model, Artificial Intelligence (AI)IntroductionAutism Spectrum Disorder is a developmental disability characterized by deficits in socialinteraction or communication and the presence of restricted interests or repetitive behaviors [1].According to the World Health Organization (WHO), it is estimated
using the vehicle provided in the virtualenvironment. A drone, accessible from the trunk, offers aerial views for closer observation.Players must capture photos of failure signs, report them promptly to the Project Manager(through the in-game phone), and provide detailed descriptions. Figure 1 illustrates keymoments from the Project Manager’s Briefing. The screenshots provide a visual representationof the briefing interface. Throughout the mission, players are evaluated on six educational targets: observationquality, reporting thoroughness, severity assessment accuracy, communication clarity,understanding of failure mechanisms, and mitigation planning. The mission concludes with aperformance review on a virtual scoreboard
significant implications for traditionally conservative fields, including civilengineering [4].In CEE, AI has begun to shift to long-standing methods of infrastructure planning, construction,and maintenance, offering powerful tools to tackle pressing challenges such as aginginfrastructure, resource constraints, and climate resilience. For example, AI-driven predictivemodels allow engineers to forecast material performance or structural demands under varyingconditions with unprecedented accuracy [4], [5]. The adoption of generative design algorithmsenables accelerated optimization of infrastructure layouts while considering multi-dimensionalconstraints like cost, sustainability, and environmental impact [6]. Advanced computer visionsystems now
careful planning to adaptthe framework to different contexts while preserving its core principles.This initiative demonstrates the transformative potential of integrating HCD principles acrossengineering curricula. Students emerged with a holistic understanding of engineering design,equipped to address societal, environmental, and ethical challenges. Faculty collaboration wasenhanced through the Faculty Learning Circle, which provided a model for fostering professionaldevelopment and cross-disciplinary exchange. Finally, the initiative offers a replicableframework for other institutions seeking to incorporate HCD into their engineering programs,setting a strong foundation for continued innovation in engineering education.7. Broader Implications
. Following the success of the SoSTeMintervention, the engineering faculty has adopted pre-training sessions as a standard practice forall engineering students before internships. This institutional shift ensures that students gainexperiential learning more effectively during their placements. The study's contribution lies inproviding a replicable framework for aligning academic training with industry expectations,setting a precedent for future improvements in engineering education and workforce readiness inresource-constrained settings.Future workFuture work will focus on refining internship frameworks by integrating structured mentorship,reflective practices, and problem-based learning. Additionally, plans include developingscalable, sustainable
believes thecoursework is valuable for their future engineering competence.As for application, our results suggest that aspects of the current class sessions do encourageattendance, and could be further emphasized according to the primary motivations identified inthis study, especially aspects that encourage intrinsic motivation through supporting competence,relatedness, and autonomy. For example, we could more explicitly encourage collaborationamong students during lab sessions, or implement class policies that more specifically supportautonomy, such as assignment choice (or options within assignments). We also plan to continueto employ TAs, and further study may be warranted on the role and student perceptions of TAs,especially how the
social roles, capabilities, rights, and responsibilities (p. 791)" Tradition "represents respect for traditional values including hard work, non- materialism, benevolence, social consciousness, morality, and respect for one’s heritage (p. 792)" Prudence "represents planning, perseverance, thrift, and future orientation (p. 790)"
, enableresearchers to make comparisons across different groups and broaden the use of theseinstruments across various disciplines. Additional work is needed to identify crucial next steps inthis project, including completing the CFA again with populations beyond first-year engineeringclasses. While this was the original population tested with this assessment instrument for theEFA and CFA, the assessment instrument was created with a broader population in mind.Therefore, the plan is to conduct extended testing of the instrument across multiple institutions,courses, and years. As validity can only be assessed for a specific context, it is important tocomplete this validation step. Current efforts are underway to find collaborators for this next stepin
between a function and its derivative (3) Applying Conducting a procedure Taking the derivative of a function (4) Analyzing Organizing material into palis and Differentiating integrals from then· detennining their relationships approximation methods ( 5) Evaluating Making judgments using criteria Perfo1ming a sanity check whether a or experience solution makes sense (6) Creating Generating or planning something Creating a function that reflects an novel observed behavior Figure 1. Annotated Taxonomy Table [12].Effective learning objectives for practice problems and
]), introduction to CAD tools,basics of design-for-manufacturing and 3D Printing are part of the course content. Each week,two 50 minutes lectures are followed by a 3-hour lab session. Figure 1. The proposed mentorship-model intervention structureBasic concepts of the course content are introduced in the lectures with relevant tutorialsfollowed by extended hands-on lab activities in Lab. Students also work on Team projects in thefirst-year design course. Three to five-member teams collaborate on the ideation, sketching,planning, designing, modeling, assembly and functional animations of proposed largeengineering structures. Students divide the overall assembly into a manageable number ofsubassemblies, and delegate tasks so that each member
imaginehow students would find the web-based activity more usable and useful. Engineering students areknown for having demanding course schedules. Extra effort is required by students who used theVR version of ThermoLab. While the web users likely only needed to click a link from theirinstructor to get started, the VR users needed to reserve a timeslot, travel to the facility to checkout a device, and more often than not, learn a new and entirely new interface. Combined, theseextra steps required more planning, thinking and time.Enjoyment scores, on the other hand, were very close between the different versions ofThermoLab and both were significantly higher than the traditional written assignment. In bothcases, the virtual lab was found to be more
methods, and student mentoring strategies. They collaborated todesign all aspects of the course. The faculty member supported the peer instructor by beingpresent at each class and by meeting at least once a week to reflect and debrief on the previousweek’s class and to plan future class activities. The undergraduate instructor then led class andoffice hours sessions, graded student work, and supported students through their courseexperiences.The course learning objectives were based on skills needed to successfully join a research lab.The four course learning objectives were (1) to recognize what undergraduate research is, howundergraduate research works, and identify the value of undergraduate research; (2) to gain adeeper understanding of lab
2 0 3 A- 1 0 2 0 2 B+ 2 1 3 0 1 B 2 1 3 0 0 B- 2 1 4 0 0 C+ 3 2 4 1 0 …2.3 Capstone design course at UNLVThe final semester capstone course, taken in the last semester of undergraduate study, engagesstudents in the civil engineering design and construction process from project planning throughproject objectives, collection
technical skills anddecision-making: Talking to these people, getting input from them—if I write a test plan or report, what’s their feedback? What’s their criticism? Where did I make mistakes? Even at 14 years in, I’d say my knowledge is still relatively limited compared to someone who’s been doing this for 40 years. Mentoring under people with more experience is invaluable.This mentorship experience highlights how direct mentoring bridges generational knowledgegaps, fosters professional confidence, and preserves institutional expertise, ultimately enablingengineers to address complex technical challenges more effectively.Jordan’s experience with peer mentoring further illustrated how structured mentoring programsfoster
Assistant (WTA): Understanding What Type of Cases are Served Through a Categorization Analysis,” in 2024 ASEE Annual Conference & Exposition Proceedings, ASEE Conferences, 2024. doi: 10.18260/1-2--48300.[9] J. W. Creswell, “Educational research: Planning, conducting, and evaluating quantitative and qualitative research,” in Climate Change 2013 – The Physical Science Basis, 4th ed., Pearson Education, 2012. doi: 10.1017/CBO9781107415324.004.[10] Y.-X. Wang and Y.-J. Zhang, “Nonnegative Matrix Factorization: A Comprehensive Review,” IEEE Trans Knowl Data Eng, vol. 25, no. 6, pp. 1336–1353, Jun. 2013, doi: 10.1109/TKDE.2012.51.[11] J. B. Ullman and P. M. Bentler, “Structural Equation Modeling,” in
[21]. In future phases,the research team plans to conduct interviews and focus groups with current program participantsto validate and expand the blueprint. Additionally, the data informing this study are primarilyself-reported by mentors and staff, introducing the potential for bias in interpretation.To advance this work beyond its current WIP status, the research team will conduct additionalrounds of blueprint development that include direct feedback from current first-year students.These data will support further refinement of the blueprint and allow for more robust analysis ofthe connections between specific program features and retention outcomes. The team also plansto develop a streamlined, integrated platform for mentor reporting and
featuring some notable articles onperovskite solar cells (PSCs):Additionally, when AI tools are used to generate or process documents, questions of intellectualproperty arise—particularly concerning ownership and copyright of AI-generated content whichwe plan to address during our session.Reference List in IEEE Style on Perovskite Solar Cells (PSC)Journal Article:[19] M. Green, A. Emery, D. H. Lee, and W. Warta, "Solar cell efficiency tables (version 44),"Progress in Photovoltaics: Research and Applications, vol. 24, no. 1, pp. 3-12, Jan. 2016.Review Article:[20] H. J. Snaith, "Perovskite solar cells: An emerging technology," Journal of PhysicalChemistry Letters, vol. 4, no. 21, pp. 3623-3630, Nov. 2013.Research Article:[21] S. K. R. M. K. Choi, A
. This allows them to get real hands-on experience, expand their network, and buildlasting friendships with fellow students, faculty members, and mentors, which could lead tofuture career opportunities. Additionally, these teams provide an ideal environment for studentsto learn and practice leadership skills. Project managers work with team members to create abudget plan, secure funding, manage finances, establish work schedules, train less-experiencedmembers, and coordinate with team officers, advisors, administrators, suppliers, and sponsors toobtain the necessary resources and successfully deliver the final product [1] - [2]. Since studentsvoluntarily join competition teams, this provides a unique opportunity for the study ofengineering
within civil engineering, addresses thecomplexities of modern projects through a combination of technical, managerial, andorganizational skills. It refers to various tasks, from planning, coordinating, and budgeting tocontrolling and monitoring construction projects through the project lifecycle. The constructionindustry is evolving rapidly due to urbanization, technological advancements, and increasedproject complexity, leading to a significant demand for effective management practices. Thistrend is evident in the growing number of academic programs and student enrollments in CMthat are aligned with the industry’s demand. According to the recent US Bureau of LaborStatistics report, the “employment of construction managers is projected to grow 9
directions.First, we plan to conduct a deeper examination of the LED curriculum itself, including its designlogic, its embedded pedagogical features, and how these were intentionally structured to disruptdominant engineering norms. We will expand the data sources to also include facilitator notes,lesson structures, and moments of interaction to better understand how the LED programfunctioned as a reimagined figured world of engineering.Second, we will explore more explicitly the relationship between the LED program’s structureand the trajectories of the youth. Rather than treating identity negotiation as solely internal orpersonal, we are interested in how it is actively shaped by relational, material, and pedagogicalconditions. This includes studying how
persistence, while the expectanciesand values are influenced by “task-specific beliefs such as ability beliefs, the perceived difficultyof the different tasks, and individuals’ goals, self-schema, and affective memories.” This theoryincludes four different types of achievement values, defined by [12], which are attainment value(“the importance of doing well on a task”), intrinsic value (“the enjoyment one gains from doing atask”), utility value (“how a task fits into an individual’s future plans”), and cost (“how thedecision to engage in one activity limits access to other activities”).EVT has begun to be applied to engineering education and other STEM fields as a way topredict students’ choices, effort, persistence, and success in these fields [13
inconcrete experience, reflective observation, abstract conceptualization, and activeexperimentation to engage in learning.In this development and testing phase, the labs were offered as an additional one-credit moduleto all students. A total of 23 students enrolled in the course. For each lab, students were firstformed into teams and presented with a challenging open-ended question. As a team, they wereasked to plan their strategy for data collection, collect data with relevant equipment, analyze theirdata with chemical engineering theory, and communicate their results. This active learningframework motivates students by encouraging them to connect their course knowledge to theproblem and challenging them to collaborate, gain, and disseminate new
to AIM feedback are discussed, AIM feedback is prone tothe same sort of negative effects as end-of-semester surveys. Organizing and planning AIM feedback within a specific course requires some forethought.AIM feedback, much like any student-centric assessment, is prone to bias [27]. AIM feedbackin particular can be influenced by recent events. Student responses may vary wildly based on thelecture immediately prior to the survey, or if the most recent homework or exam was too difficult.While this can be somewhat mitigated (by allocating certain questions to those assignments) anynegative sentiment may bleed into the open-ended questions and lead to overall negative commen-tary. Much like end-of-semester surveys, there might be a series
-depth explanations as well as detailed diagrams and open-source code. Wealso include lecture slides, exercises, and labs and have used these to teach two types of courses:an advanced course that covers the entire textbook and a lower-level course that taught computerarchitecture and processor design only. Using the book, users are able to understand computerarchitecture and SoC design topics, including a detailed understanding of the theory andimplementation of each building block needed to design an SoC. The open-source code for thefully functional and configurable Wally SoC provides a platform for hands-on learning andexperimentation with the concepts taught in the textbook. In the future, we plan on expanding thetextbook and Wally’s