]. The plat-form’s Python-based code editor, combined with ROS2 and Gazebo for simulation, en- 2ables students to apply programming concepts directly in a robotics context, bridgingthe gap between abstract coding exercises and real-world applications. One of the key motivations behind the development of the FORE platform is the needfor a flexible and scalable educational tool that can adapt to the varying needs of students.For beginners, the platform provides structured lessons that gradually introduce corerobotics concepts such as motion control, sensor integration, and path planning. For moreadvanced students, the platform offers opportunities to explore more complex roboticalgorithms and systems
Teamwork in Collaborative Learning Environments: Team Learning Beliefs and Behaviors,” Small Group Res., vol. 37, no. 5, pp. 490–521, Oct. 2006, doi: 10.1177/1046496406292938.[3] N. C. Byrom, L. Dinu, A. Kirkman, and G. Hughes, “Predicting stress and mental wellbeing among doctoral researchers,” J Ment Health, vol. 31, no. 6, pp. 783–791, Nov. 2022, doi: 10.1080/09638237.2020.1818196.[4] C. Spooner, L. Lavey, C. Mukuka, and R. Eames-Brown, “Multi-Institution Research Centers: Planning and Management Challenges,” J. Res. Adm., vol. 47, no. 2, pp. 32–48, 2016.[5] R. C. Bindler, B. Richardson, K. Daratha, and D. Wordell, “Interdisciplinary health science research collaboration: strengths, challenges, and case
Thermodynamics 9 Nuclear and radiation 1 Manufacturing 8 Aero structures 1 Materials 8 Energy systems 1*Included a topic on “Vibrations and acoustics”4.3 Techniques for evaluating early-stage doctoral candidatesWe identified multiple assessment techniques, types, and formats of mechanical engineeringpreliminary examinations (Table 4). All 25 programs in our sample required course completionwith varying criteria (e.g., GPA requirements, specific versus flexible course plans) as part oftheir evaluation process. All but one program (24, 96%) conducted a preliminary exam outside ofcoursework
. Theynoted that applying the rubric to one student at a time significantly improved clarity andemphasized the value of repeated viewings to capture subtle dynamics, especially among shy FIGURE 1. DRAFT RUBRIC FOR THE OBSERVABLE BEHAVIOR PRESENTED AT KNC2025.students. This rubric is part of a planned EM Behavior Field Guide currently under developmentthat includes behaviors and performance levels, identifies evidence sources, and tags existingEngineering Unleashed activities that may help develop the behaviors. Once a draft of the FieldGuide is completed, the authors will partner during the 2025-2026 academic year with faculty atNetwork institutions selected through an application process to beta-test the materials ineducational settings
time. While we believe these findings independently add value to theexisting body of literature by summarizing the breadth and depth of existing literature andproviding several areas to emphasize for future research, our later presentation of this work willextend these findings. Continued plans for this study include analyzing the coincidence ofcategorical codes (e.g., identifying and considering the number of papers that were longitudinaland had a sample > 250 participants,) and quantitative clustering of existing papers throughbipartite network projection and subsequent clustering [18], [43], [44]. Finally, we will developrecommendations for efficient strategies to study networks that meet the existing gaps,recognizing the increased
to those who are seeingthe content for the first time, and (2) is there a way to create a “simple” version of this game,targeted at younger audiences (approximately ages 5-10).To answer Question 1 and help educators implement this game, regardless of backgroundknowledge, we introduced a Facilitator’s Guide. This document covers all information needed byan instructor – from game equipment needs to detailed instructions to alternative tips forimplementation. We plan on improving this guide as more user feedback is received.To answer Question 2, we introduced two versions of the game: Simple and Advanced. TheAdvanced version is the same as explained above for this study, where students estimate materialproperties via measurements made using
acquisition system: Arduino Mega at $23, Taiss rotary encoder at $18 each, DCmotor for $15, and jumper wires for $3.Planned implementation. The proposed equipment can be utilized in mechanical vibrations,machine dynamics courses, and vibrations and control theory laboratories. As a low-costsolution, multiple setups can be assembled to conduct experiments for both free and forcedvibration analyses. These can be integrated into laboratory activities so teams of students can Figure 4. The top row displays the CAD models of the device from front, isometric, and left views, while the bottom row shows the physical prototype: (1-4) feature the front view with dual pendulum rods and encoders, both free and coupled together by a compliant spring; (5,6
howthese strategies impact success. In this study, the term “best practices” refers to guidelinesthat have been established for optimizing AI interactions during problem-solving tasks, forexample in (Open AI, 2024; Google, 2024).An IRB-approved plan guided data collection from the competition, where teams of threeundergraduate students were encouraged to use generative AI to solve programmingproblems. Over 100 students participated. After the competition, students voluntarilysubmitted transcripts documenting their interactions with AI tools. These transcripts wereexamined using a directed content analysis (Hsieh and Shannon 2005) to assess how wellstudents followed prompt engineering best practices.The study findings reveal significant variability
), and enhance safety compliance and decision-making capabilities through realistic workscenarios. In addition, an adaptive difficulty mechanism is introduced in the PPE InspectionTraining scenario. Finite automaton improves training efficiency and stability and optimizes theoverall user experience.In future work, will focus on optimizing LLM’s response and developing more diverse teachingmodules as templates to adapt to educational needs flexibly. Also, future studies plan to collectadditional data on user experience and educational research to allow for better statistical analysisby considering more participants and real-world application scenarios and consideringphysiological, socioeconomic, cultural, and other variables. Future work will
Engineering at Morgan State University, where he also serves as a Research Assistant. He holds a bachelor’s degree in Civil Engineering from the Federal University of Technology, Akure (FUTA). His current research focuses on the sustainability and resilience of transportation infrastructure in the face of sea level rise, with a particular emphasis on coastal vulnerability and adaptive planning for future climate scenarios. Tolulope is passionate about engineering education and research, with a strong appreciation for field experiences that bridge theory and practical application.Mr. Pelumi Olaitan Abiodun, Morgan State University Pelumi Abiodun is a current doctoral student and research assistant at the department of Civil
economics of higher education,” J Econ Persp, vol. 13, no. 1, pp. 13–36, Feb. 1999, doi: 10.1257/jep.13.1.13.[31] B.C. Harvey, “Teetering on the demographic cliff, part 1: Prepare now for the challenging times ahead,” Planning for Higher Ed, vol. 49, no. 4, pp. 1–12, 2021.[32] R.J. Ely and D.A. Thomas, “Cultural diversity at work: The effects of diversity perspectives on work group processes and outcomes,” Admin Sci Quart, vol. 46, no. 2, pp. 229–273, Jun. 2001, doi: 10.2307/2667087.[33] J.B. Main, M.M. Camacho, C. Mobley, C.E. Brawner, S.M. Lord, and H. Kesim, “Technically and tactically proficient: How military leadership training and experiences are enacted in engineering education,” Int J Engr Ed, vol. 35, no. 2, pp. 446
can and should be collected. Additionally, our research team plans toconduct analyses on multiple axes of our data. The ones we find most interesting are institutiontype (i.e., in community colleges where everyone is a TFF, institutional constraints are differentthan at R1 institutions where TFF are a small subset), and the immigration status of TFF (theexperiences of international PhD students were significantly different from domestic students).Future papers from our research team cover the topics of culturally relevant mentorship, facultyfit, and the climate of engineering departments for Latine/Hispanic TFF.Limitations We hope to increase servingness for individual students, who as a group of students, areof course not monolithic
practiceimpacts student practices and perceptions, so confirmatory studies of these factors must accountfor the clustering of students based on their instructors. In future work, we plan to usehierarchical linear modeling to account for the nested structures of this data.ConclusionThis study used EFA to analyze 448 survey responses completed by students in statics andmechanics undergraduate courses at twelve diverse institutions to understand their perceptions ofusing the CW in their classes. We found two factors associated with students’ practices and fourfactors that detail student perceptions around their experiences using the tool. While correlationsbetween practice and perception were found for positive learning experiences, the factorrepresenting
information was highlighted in observations that AI eliminates”scrounging on Google to find a good explanation for a question...you get a direct response to yourniche question.” Beyond student applications, participants recognized potential faculty benefits,noting that AI can assist in developing ”assignment description[s] or...lesson plan[s]” and ”helpteachers generate homework and streamline the process of grading,” allowing educators to ”spendmore of their time focused on the students.”3.1.5 Creative SupportAI’s utility as an ideation tool and starting point generator was identified in 42 responses (10.50%total). Participants valued how AI chatbots help students ”get an idea as to how to start a certainproblem...when they have no idea
plan to test the two classifier models on various types of student learningdata, for example, the live student engagement and performance data obtained from a learningmanagement system, as it would assist course instructors to better assess student academic needs.Using our own data instead of an online dataset might also help address severe class imbalanceissues. Additionally, it may be worthwhile to build hybrid models that combine RFC’s featureselection with MOC’s multi-output prediction, as it would allow for more precise predictions anda deeper understanding of how different aspects of student engagement and performance areinterrelated. Furthermore, it may be worthwhile to incorporate some qualitative data, such asteacher assessments
knowledge and skills in fields related to the National Aeronautics and SpaceAdministration’s (NASA’s) mission and the needs of the future workforce.To participate, students must first contact the faculty coordinator at their home institution, whoplays a crucial role in identifying and matching students with appropriate projects. Faculty mentorsfrom participating member institutions submit proposals for projects aligned with NASA’s goalsand relevant STEM disciplines. These proposals include key project components, such as learningoutcomes, timelines, mentoring plans, and expected deliverables. The program places a strongemphasis on inclusivity, actively recruiting women and members of underrepresented minorities,thereby ensuring a diverse pool of
,contributions from individual instructors can continue to be carried out by future instructors withthe coordinator’s help. The coordinator is the bridge between courses and between semesters.Students and new instructors have greatly benefited from standard course policies and consistentexpectations.Reform Project 2: Integration of computational tools in collaboration with computer science andmath prerequisite coursesThe project aimed to modernize essential undergraduate service courses by incorporatingmeaningful computational tools and exercises. While the focus was initially on Statics, the facultyparticipating in this project is the core of a broader Python Working Group initiative, with plans toimplement similar changes in other courses over time
: Tech Presentation 1 and 2 Prototyping, Soldering, Electronics Prototyping, testing plan, build, test. Tech 2 Testing Presentation 3 and 4 Testing, During flex time: power tools, Iterate, Test, Final Refinements. Website and Refining, advanced 3D printing, laser video production. Practice presentation and 3 Presenting cutting, CNC Router, final presentation. programming, solderingThis curriculum closely parallels the Seven Key Characteristics of Integrated STEM proposed byRoehrig, et al [14] which are: 1) focus on real-world problems - using the UN SustainableDevelopment goals as a
identifytrends and the need for additional support for students in each category. Plans for improvedstudent engagement as a result of this study are presented.The Student PopulationIntroduction to Chemical Engineering (Intro) is offered as the first course in ChemicalEngineering at the U of A and covers topics such as chemical engineering as a profession, jobopportunities, ethics, communication skills, unit conversions, limiting reactant calculations andmaterial balances for reacting and non-reacting systems. Prior to 2013, the course was part of atwo-course freshman-level sequence that also included Introduction to Chemical Engineering II(Intro II), which emphasized ideal and real gases, steam table use, humidification and energybalances for reacting
future iterations of this course. The memo-based assessments and studentpresentations provided valuable opportunities for students to begin to communicate likeengineers. However, we need to explicitly discuss how each guiding question relates to a broaderdefinition of sustainability earlier in the course. We plan to do so at the introduction of eachmodule in future iterations. We will also integrate the areas of the EOP framework that were notintegrated into this iteration, Social Responsibility and Environmental Literacy. EnvironmentalLiteracy will be integrated with Environmental Impact, as understanding one can help a studentunderstand the other. While some students independently identified the importance of SocialResponsibility, we will
3. understand relationships between sociocultural influences and engineering education 3. Other & practice 4. Teaching Virginia Tech 4. translate education research to practice 5. Research 5. communicate the implications of engineering education research to various 6. Teaching stakeholders 7. Teaching 6. design and critique assessment plans for engineering-related courses and programs 7. apply pedagogical
Dr. Corey Woodcockfor assisting with the 3D printing process and William Marshall and Alex Guo for preparing theinitial maze generation scripts in MATLAB.References[1] P. Wang, P. Wu, J. Wang, H.L. Chi, and X. Wang, "A critical review of the use of virtualreality in construction engineering education and training," International Journal ofEnvironmental Research and Public Health, vol. 15, no. 6, pp. 1204, 2018.[2] M.E. Portman, A. Natapov, and D. Fisher-Gewirtzman, "To go where no man has gonebefore: virtual reality in architecture, landscape architecture and environmental planning,"Computers, Environment and Urban Systems, vol. 54, pp. 376-384, 2015.[3] D. Kamińska, T. Sapiński, N. Aitken, A.D. Rocca, M. Barańska, and R. Wietsma
perceived assets were mentioned by participants in their essays (seeTable 2). The frequency at which the identified subthemes were mentioned varied between 31%to 4% of the students, with the four most common assets being identified by more than 20% ofthe participants. In the following, identified sub themes will be discussed in detail from mostcommon to least common.Commitment. The most common asset expressed by a third of the students in their essays wastheir willingness to commit and persist despite potential obstacles. As one student stated: Beingdedicated to achieving these goals requires discipline, perseverance, and hard work. It isimportant for people to have a clear understanding of what they want to achieve and to developa plan for how to
in STEM classrooms and its impact onundergraduate and graduate students. Students believe that the Universal Design for Learningprinciples benefit their learning. However, only a few faculty members implement theseprinciples. Most of the articles highlighted how students preferred Multiple Means ofRepresentation. The other two principles were barely explored. Researchers should examine howstudents feel about Multiple Means of Action and Expression and Multiple Means ofEngagement. Autumn Cuellar plans to explore all three principles in her dissertation by 5interviewing disabled engineering students, using this WIP paper as background
encounter issues in additional notes or during the lab. the lab activity. the lab. context. I justify my I document my I observe my lab experimental setup thought process while I take notes on key partner interactingchoices to my partner designing and observations during with the simulationwhen planning the lab conducting the the experiment for
. Thisincluded the time spent preparing interactive activities. Although these quizzes could be reused infuture semesters, it still requires instructors to continuously update the quizzes to ensure that thequizzes align with each lecture.Another concern is that extra time is needed to implement gamified activities during classes.Gamification activities require pausing for quizzes and reviewing answers. In addition, managingstudent participation and ensuring smooth transitions between activities can add more time. Thiscould reduce the time available for other instructional activities. If the course has tight schedules,this challenge can require adjustments in lesson planning to accommodate gamifiedelements.Despite these challenges, all instructors who
Paper ID #46269WIP: Identifying the Pre-college Engineering Experiences of our First-YearEngineering StudentsBrian Patrick O’Connell, Northeastern University Dr. O’Connell is an associate teaching professor in the First-Year Engineering program at Northeastern University. He studied at the University of Massachusetts at Amherst in 2006 then worked in industry as a Mechanical Engineer working on ruggedized submarine optronic systems. He returned to academia in 2011 at Tufts University planning to work towards more advanced R&D but fell for engineering education and educational technologies. His research now focuses on
Paper ID #47770WIP: Examining the Experiences of Neurodivergent Learners in STEM Fieldsin Their Transition to and Engagement with Online LearningMr. Alec Jon Bauer, Clemson University I am currently a senior at Clemson University, majoring in Biology and pursuing a pre-medical track with plans to apply to medical school. I have personally experienced the challenges associated with transitioning to online learning. This research is particularly meaningful to me, as I understand the significant impact such transitions can have on neurodivergent learners. However, I am committed to leading this study objectively, ensuring
effective problem-solving. This highlights the importance of design education in helpingstudents refine their planning and problem-solving skills. By incorporating mind mappinginto architectural education, students can improve their ability to recognize key elements ofa problem, generate solutions, and communicate their ideas more effectively. The process ofvisualizing solutions through mind maps not only supports cognitive development but alsoenhances the overall design process. Mind maps are a valuable tool in architecture education,enhancing learning by helping students organize complex ideas, link theory to practice, andintegrate creative and technical skills. They bridge the gap between studio and lecture-basedcourses, promoting a more