, refine, and utilize the Engineering MentalHealth Help-seeking Instrument (EMHHI) developed through a NSF Research Initiation inEngineering Formation (RIEF) grant (NSF Award 2024394). The core products of this proposalwill be (a) an improved and refined EMHHI to assess diverse engineering students’ beliefs relatedto help seeking, (b) a standardized protocol for creating institutional help-seeking profiles thatsummarize mental health status and identify help-seeking belief targets for future interventions,and (c) a comprehensive list of key help-seeking beliefs for a diverse array of engineering studentdemographic subgroups. Based on the completion of our first year of this project, this paper willfocus on answering the following research question
received his B. Tech. from Indian Institute of Technology Kharagpur (2010) and his Ph. D. from Rensselaer Polytechnic Institute (2016), both in Mechanical Engineering. He worked as Post-Doctoral Research Associate for 1.5 years and as a Lecturer for 6 months at Rensselaer Polytechnic Institute prior to joining the College of Engineering at West Texas A&M in Fall 2019 as an Assistant Professor of Mechanical Engineering. The famous American scientist Richard Feynman prophesied the huge potential for engineering at small scales (There’s plenty of room at the bottom!). In this spirit, Dr. Pal is interested in the unique nano-mechanical behavior of materials at small scales, and how they can be harnessed to produce
with a range of 1 to 7, signifying a moderate belief in their ability to control effort and attention intheir HyFlex class. The non-significant Pearson correlation (r = 0.019, p = 0.773) indicated that students whoopted for face-to-face or remote participation had a comparable experience in effort regulation. Students, onaverage, scored 4.58 in peer learning, indicating a moderate belief in working and learning with peers in theirHyFlex class. The non-significant Pearson correlation (r = -0.020, p = 0.716) revealed that face-to-face orremote participants had similar experiences in peer learning.Study 8: Krishna, B. (2023). Effect of Modalities on Group Performance in Hyflex Environment (30685608)[Master’s thesis, Purdue University]. ProQuest
://www.suitable.co/products/guided-pathways (accessed 14 January 2024).[2] “Möbius MAA Placement Test Suite by DigitalEd”, Mathematical Association of America,https://maa.org/node/259 (accessed 14 January 2024).[3] J.L.M. Wilkins, B.D. Bowen, and S. B. Mullins, “First mathematics course in college andgraduating in engineering: Dispelling the myth that beginning in higher-level mathematicscourses is always a good thing”, Journal of Engineering Education, Volume 110, Issue 3,https://doi.org/10.1002/jee.20411, 2021.[4] Daniel W. Knight, D.W., L. E. Carlson, and J. F. Sullivan, “Staying in Engineering: Impact ofa Hands-On, Team-Based, First-Year Projects Course on Student Retention”, Proceedings of the2003 American Society for Engineering Education Annual
in productive ways.References[1] b. hooks, Teaching to Transgress: Education as the Practice of Freedom. New York, NY,USA: Taylor & Francis Group, 1994.[2] D. Riley, “Employing liberative pedagogies in engineering education,” Journal of Womenand Minorities in Science and Engineering, vol. 9, pp. 137-258, 2003.[3] Office of Institutional Statistics. “Enrolment Reports | Institutional Analysis | University ofManitoba” umanitoba.ca. https://umanitoba.ca/institutional-analysis/enrolment-reports (accessed:Mar 27, 2024)..[4] A. Quan-Haase, Technology & Society: Social Networks, Power, and Inequality, 3rd ed. DonMills, Canada: Oxford University Press, 2020.[5] B. Arao and K. Clemens, “From safe spaces to brave spaces: A new way to frame
engagement." Interactive Learning Environments 28.4 (2020): 464-481.[13] B. Oakley, R. M. Felder, R. Brent and I. Elhajj, "Turning student groups into effectiveteams", J. Student Center. Learn., vol. 2, pp. 9-34, 2003.[14] Hamnett, McKie, and Morrison. Postgraduate Students' Attitudes towards Group Work:Experiences within a Forensic Chemistry Programme. vol. 19, no. 4, pp. 1240-252, ChemistryEducation Research and Practice 2018.[15] H. J. Hamnett and A. E. McKie, “Developing a procedure for learning and assessing peerreview in a forensic science programme,” Assessment & Evaluation in Higher Education, vol.44, no. 5, pp. 787–798, Dec. 2018, doi: https://doi.org/10.1080/02602938.2018.1536924.[16] R. S. Hansen, “Benefits and Problems With Student
48.4% 17.0% 31.3 PP Limited Incomed 34.2% 20.1% 14.1 PP CO Resident 78.8% 65.3% 13.5 PP Racially Minoritized 40.8% 24.8% 15.9 PPTable 4: Overall SURE Persistence & Demographics with Reference GroupTable 4 Notes:a Data and interpretation for table A and B provided by Nicole Ross of CSU’s Office ofInstitutional Research, Planning, & Effectiveness.b The WSCOE reference group includes all full-time new (summer and fall start)s and transfer(fall starts) undergraduates in entering cohorts FA17-FA22 whose entering
Souza, and D. Schneider, "Digital Nomads during the COVID-19 Pandemic: Evidence from Narratives on Reddit discussions," in 2022 IEEE 25th International Conference on Computer Supported Cooperative Work in Design (CSCWD), 2022: IEEE, pp. 1510-1516.[2] B. Y. Thompson, "The digital nomad lifestyle:(remote) work/leisure balance, privilege, and constructed community," International Journal of the Sociology of Leisure, vol. 2, no. 1, pp. 27-42, 2019.[3] I. Reichenberger, "Digital nomads–a quest for holistic freedom in work and leisure," Annals of Leisure Research, vol. 21, no. 3, pp. 364-380, 2018.[4] T. Anderson, "Towards a theory of online learning," Theory and practice of online learning, vol. 2
commercialization since this isdone in a variety of professional contexts. A 1-credit hour course is one way that these learninggoals could be taught and accomplished.AcknowledgementsThe authors would like to acknowledge Miriam Salah and the Siebel Center for Design (SCD)for the design of the course workbook and the generous support of the Kern Family Foundationas part of SIIP in The Grainger College of Engineering at the University of Illinois Urbana-Champaign and NSF I-Corps Hub-Great Lakes Region, Grant #2048612.References[1] “The Entrepreneurial Mindset,” KEEN - Engineering Unleashed. [Online]. Available at https://engineeringunleashed.com/mindset.[2] Burnett, B., & Evans, D. (2020). Designing Your Work Life: How to Thrive and Change
worker sleep deprivation and its effects on personal safety,” presented at the Procs 26th Annual ARCOM Conference, Leeds, UK: Association of Researchers in Construction Management, 2010, pp. 203–211.[14] S. Sathvik, L. Krishnaraj, and M. Irfan, “Evaluation of sleep quality and duration using wearable sensors in shift laborers of construction industry: A public health perspective,” Front. Public Health, vol. 10, p. 952901, Sep. 2022, doi: 10.3389/fpubh.2022.952901.[15] Y. Kim et al., “Factors associated with poor quality of sleep in construction workers: a secondary data analysis,” IJERPH, vol. 18, no. 5, p. 2279, Feb. 2021, doi: 10.3390/ijerph18052279.[16] S. S. Chandra, K. Loganathan, B. O. Awuzie, and F. Wang, “A
Paper ID #44145Tuition Equity: A Study of the Disparate Impacts of Block TuitionDr. Nicholas A Baine P.E., Grand Valley State University Nicholas Baine, Ph.D., P.E. is an Associate Professor in the School of Engineering. His expertise is in the design of electrical control systems and sensor data fusion techniques. As an instructor, he specializes in first-year engineering course development as well as control system courses. He is actively involved as a member of the board of the North Central Section of ASEE and is a Program Evaluator for ABET.Dr. Karl Brakora, Grand Valley State University Karl Brakora and affiliate
. Zhang, A. Gong, Y. Fan, J. Yan, X. Li, “Nuclear power plants with artificialintelligence in industry 4.0 era: top-level design and current applications – a systemic review.”IEEE Access, vol. 8, pp. 194315-194332, 2020.[2] A. Thakur, D. Sarkar, V. Bharti, and U. Kannan, “Development of in-core fuel managementtool for AHWR using artificial neural networks,” Annals of Nuclear Energy, vol. 150, p.107869,2021.[3] D. Price, M. Radaideh, and B. Kochunas, “Multiobjective optimization of nuclearmicroreactor reactivity control system operation with swarm and evolutionary algorithms.”Nuclear Engineering and Design, vol. 393, p. 111776, 2022.[4] D. Lee, P.H. Seong, and J. Kim, “Autonomous operation algorithm for safety systems ofnuclear power plants by
; Exposition, 2009, p. 14.223. 1- 14.223. 18.[5] S. D. Hart, “Applying the ExCEEd Teaching Model in a Flipped Classroom Environment,” in 2016 ASEE Annual Conference & Exposition, 2016.[6] J. Q. Retherford and J. K. Amoah, “Incorporating ASCE’s ExCEEd Principles in Capstone Project and Other Active Learning Courses,” in Proceedings of the American Society of Engineering Education Southeast Section Conference, 2014.[7] R. W. Welch and C. B. Farnsworth, “Using the ExCEEd Model for Distance Education,” in 2011 ASEE Annual Conference & Exposition, 2011, p. 22.1645. 1-22.1645. 22.
grader toprocess the work and provide feedback. Lengthy feedback times are suboptimal from a learningperspective since the student may miss opportunities to learn from the feedback. Faster feedbackresults in better learning because the feedback has better connection to the work when thememory of the work is fresh.One way to reduce grading time is to employ low-resolution grading, that is, grading methods thatuse low numbers of possible grade levels. Grading on a scale of 100% without fractionalpercentage points has 100 levels. Grading on an A-B-C-D-F scale without pluses and minuses hasfive levels. Miguel and Larson 1 recommend using the lowest number of grading levels that allowsan accurate assessment of student learning, and they state that
://onlinestatbook.com/[11] R. R. Sokal and F. J. Rohlf, Biometry: the principles and practice of statistics in biological research, 3rd ed. New York: W.H. Freeman, 1995.[12] D. Thunnissen, “Uncertainty Classification for the Design and Development of Complex Systems,” 2003.[13] B. M. Ayyub, Ed., Uncertainty modeling and analysis in civil engineering. Boca Raton: CRC Press, 1998.[14] A. A. diSessa, “Toward an Epistemology of Physics,” Cogn. Instr., vol. 10, no. 2–3, pp. 105–225, 1993.[15] A. diSessa, “A History of Conceptual Change Research: Threads and Fault Lines,” in The Cambridge handbook of: The learning sciences, Cambridge University Press, 2006, pp. 265–281.[16] A. J. Magana, “The role of frameworks in engineering education
Paper ID #43119How AI Assisted K-12 Computer Science Education: A Systematic ReviewZifeng Liu, University of Florida Zifeng Liu is a Ph.D. student and research assistant in School of Teaching & Learning, College of Education, University of Florida. Her research interests include educational data mining, artificial intelligence, and computer science education.Rui Guo, University of Florida Dr. Rui Guo is an instructional assistant professor of the Department of Engineering Education in the UF Herbert Wertheim College of Engineering. Her research interests include data science & CS education, Fair Artificial
, and the due dates are allprominently displayed in the module overview.The following details were included in the Module Overview, which was organized using thesame format for every module: A. Unit overview: a brief overview of the subject and the skills that the student will learn. B. Learning Objectives: The module's specific learning objectives. These directly relate to the topic and are more detailed than the learning objectives for the course. C. Pre-class content: tasks students must complete prior to class. This section contains information about how long it should take outside of class and what learning objectives are covered in the content. Figure 3 below provides an example from the Canvas page. listed for
Paper ID #44314A Low-Cost Platform for Teaching Real-Time Digital Signal ProcessingDr. Joseph P. Hoffbeck, University of Portland Joseph P. Hoffbeck is a Professor of Electrical Engineering at the University of Portland in Portland, Oregon. He has a Ph.D. from Purdue University, West Lafayette, Indiana. He previously worked with digital cell phone systems at Lucent Technologies. ©American Society for Engineering Education, 2024 A Low-cost Platform for Teaching Real-time Digital Signal ProcessingAbstractThe STM32F746G-DISCO Discovery kit from
Paper ID #42949Enhancing Teamwork Skills in STEM Education: A Behavioral Theory-BasedApproachTazim Ahmed, The University of Texas at Arlington Tazim Ahmed is currently a PhD student in Industrial Engineering at the University of Texas at Arlington. His research primarily focuses on Human Factors Engineering, Cognitive Engineering, and Engineering Education.Syed Mufid, The University of Texas at Arlington Syed Mufid is currently a Master’s student in Industrial Engineering at the University of Texas at Arlington. His research interests encompass Human Factors, Radio Frequency Identification (RFID) and Supply Chain
everything needed to perform six take-home labs. Students must demonstrate each labto the instructor or the grader. The Digital Operations course is followed by ProgrammableDevices. Students take it in the winter quarter of the second year or in their junior year if they aretransfer students. By this time, students have taken a Python course and therefore haveprogramming experience. The Programmable Devices course meets once a week for a 50-minutelecture followed by a three-hour lab. There are normally eight labs and one final project.Digital Operations Take-Home LabsThe purpose of the take-home labs is a) to help students view digital components as real and tohave them see that they work as presented in class, b) to have students learn about
changes made do not cause problems with ABETaccreditation. The new curriculum needs to satisfy Criterion 5 of the ABET EngineeringAccreditation Commission 2023-2024 Criteria [8]. This criterion states that “the curriculummust include: a) a minimum of 30 semester credit hours (or equivalent) of a combination of college-level mathematics and basic science with experimental experience appropriate to the program. b) a minimum of 45 semester credit hours (or equivalent) of engineering topics appropriate to the program, consisting of engineering and computer sciences and engineering design, and utilizing modern engineering tools. c) a broad education component that complements the
Paper ID #42530Designing and Evaluating Virtual Reality Applications for a Machine DesignCourseDr. Andrea Gregg, Penn State University Dr. Gregg’s career sits at the unique intersection of instructional design, faculty development, educational technology leadership, curriculum planning, and educational research and evaluation. She is an established higher education professional with over twenty years’ experience in online, distance education. As the manager of an instructional design (ID) team responsible for the design, development, and support of nearly 150 courses, she worked with a diverse portfolio including STEM
knowledge: Theorizing practices in households, communities, and classrooms. Routledge. 14. Brown, M., Thompson, J., & Pollock, M. (2017). Ensuring Equity in Problem Based Learning. NAPE. Gap, PA. 15. Luft, J. A. (1999). Rubrics: Design and use in science teacher education. Journal of Science Teacher Education, 10(2), 107-121. 16. Tatto, M. T. (Ed.). (2024). Empowering Teachers for Equitable and Sustainable Education: Action Research, Teacher Agency, and Online Community. Taylor & Francis. 17. Williams, B. (2016). INCREASING ACCESS, EQUITY AND DIVERSITY: NAPE’s Program Improvement Process for Equity. Techniques Magazine by ACTEOnline. https://www.acteonline.org/wp-content/uploads/2018/05/Techniques
such as a tire shop and a catering establishment. The industry consists of rail to the south and a refinery to east. i. Small Residential located sporadically around ii. Commercial nearby iii. Railways and refinery nearby ii. b. Traffic Proximity (daily traffic count/distance to road): i. 210 iii. c. Superfund Proximity (site count/km distance): i. 2.1 iv. d. Hazardous Waste Proximity (facility count/km distance): i. 6.6 v. e. Underground Storage Tanks (count/km2): i. 2.6 vi. f. Wastewater Discharge (toxicity-weighted concentration/m distance: i. 0.011 vii. g. Diesel Particulate Matter* (µg/m3): i. 0.456Discuss the impacts the brownfield has on public health or welfare of the
afterparticipating for 2-3 years might bring more mentors to the program while also giving activementors a brief break from mentoring. Finally, the addition of FEP students to the programmight attract more students to chemical engineering.References[1] J. K. Banerjee, “Mentoring undergraduate students in engineering,” in Proceedings of the2020 ASEE Virtual Annual Conference, June 2020, 10.18260/1-2—34968.[2] K. Elfer, A. M. Rynearson, N. M. Hicks, E. M. Spingola and K. Fair, “Lessons learned:strategies for creating and mentoring diverse graduate student communities,” in Proceedings ofthe 2017 ASEE Annual Conference & Exposition, Columbus, Ohio, June 2017, 10.18260/1-2—28624.[3] S. Zurn-Birkhimer B. and Holloway, (2008, June), “Retention programming For
Paper ID #43318High-Temperature Materials Testing using a Hybrid Rocket TestbedDr. Dustin Scott Birch, Weber State University Dustin Birch is a professor in the Mechanical Engineering department at Weber State University. Dr. Birch earned his PhD in Systems Engineering from Colorado State University. He also earned a BS and MS degree in Mechanical Engineering from the University of Utah. In addition to his academic experience, Dr. Birch has worked for several decades as an engineer and manager for various companies. His experience includes thermal and structural analysis of aerospace propulsion systems, mechanical
that ensure ethical AI use in education.References[1] K. B. Mustapha, E. H. Yap and Y. A. Abakr, "Bard, ChatGPT and 3DGPT: a scientometric analysis of generative AI tools and assessment of implications for mechanical engineering education," Interactive Technology and Smart Education, vol. 1, no. 1, 2024.[2] J. Qadir, "Engineering Education in the Era of ChatGPT: Promise and Pitfalls of Generative AI for Education," in IEEE Global Engineering Education Conference (EDUCON), 2023.[3] J. E. Duah and P. McGivern, "How generative artificial intelligence has blurred notions of authorial identity and academic norms in higher education, necessitating clear university usage policies," IJILT, 2024.[4] T. Jie, J. Hou, Z. Wu, P. Shu, Z. Liu
, vol. 65, no. 4, pp. 544-552, 2022, doi: 10.1109/TE.2022.3147099.[2] A. Godwin and A. Kirn, "Identity-based motivation: Connections between first-year students' engineering role identities and future-time perspectives," Journal of Engineering Education, vol. 109, no. 3, pp. 362-383, 2020, doi: https://doi.org/10.1002/jee.20324.[3] W. J. S. B. E. Hughes, E. Annand, R. Beigel, M. B. Kwapisz, and B. Tallman, "Do I think I’m an engineer? Understanding the impact of engineering identity on retention," presented at the 2019 ASEE Annual Conference & Exposition, Tampa, Florida, June 15, 2019, 2019.[4] M. S. Somia Alfatih, M. S. Leong, and L. M. Hee, "Definition of Engineering Asset
, with input from the other project faculty. Each workshop was team-led by the sociolinguist, anthropologist, and one of the other faculty team members, in rotation.The student participants comprising the first cohort in the program included master’s anddoctoral students from psychology (1), counseling (1), sociology (1), environmental engineering(2), industrial engineering (1), mechanical engineering (1), and sustainable energy engineering(3).TRANSDISCIPLINARY EDUCATION WORKSHOP MODELParticipants in the workshops engaged in (a) two cultural competence workshops, (b) twocommunity engagement workshops, and (c) two qualitative data analysis workshops. Wedescribe the structure and design of key elements in the workshops below. In the tradition
otherwise abstract multiphase fluidprocesses occurring within hydrocarbon reservoirs. Figure 6 shows the top view of the printed3D models with drainage and imbibition processes. In addition, in the same project, students arerequired to estimate several petrophysical properties such as porosity, grain size distribution,fluid saturation, contact angle, and displacement efficiency using open-access image processingsoftware. (a) (b) (c)Fig. 6-3D printed macro-models showing (a) the model is fully saturated with water (blue), (b)the model after drainage with air to achieve the irreducible water saturation, and (c) the modelafter imbibition to achieve the residual gas saturation [8].Undergraduate