University of Texas at San Antonio Student researcher interested in how the delivery of professional development can impact a teacher’s ability to influence students to pursue STEM (and more specifically, CS-related) degrees.Dr. Amanda S. Fernandez, The University of Texas at San Antonio Amanda S. Fernandez an Assistant Professor of Computer Science at the University of Texas at San Antonio.Dr. Timothy Yuen, The University of Texas at San Antonio Timothy T. Yuen is the Associate Dean for Undergraduate Studies in the College of Sciences at the University of Texas at San Antonio. ©American Society for Engineering Education, 2025 Computer Science Professional Development for Middle and
of Engineering, Philadelphia, USA. He received his Ph.D. degree in the G.W. Woodruff School of Mechanical Engineering at Georgia Institute of Technology.Jakia Sultana, University of Texas at El PasoMr. S M Atikur Rahman, University of Texas at El Paso S M Atikur Rahman is a Research Assistant in the Department of Aerospace and Mechanical Engineering (AME) at the University of Texas at El Paso (UTEP). Currently, he is pursuing his PhD degree in Mechanical Engineering at UTEP. He has completed his B.Sc. degree in Industrial and Production Engineering (KUET Bangladesh) and MSc in Industrial Engineering (UTEP USA). Mr. Atikur is working in the field of Simulation (AnyLogic), Deep Learning, and Smart Manufacturing Systems
thinking into curricula to foster creativity, problem-solving skills.Dr. Corey T Schimpf, University at Buffalo, The State University of New York Corey Schimpf is an assistant professor in the Department of Engineering Education at University at Buffalo. He is the Past Division Chair for the Design in Engineering Education Division (DEED) for the American Society of Engineering Education. His research interests include engineering and human-centered design, advancing research methods, and technology innovations to support learning in complex domains. He has a PhD from Purdue University in Engineering Education.Dr. Carolyn S Giroux, Wentworth Institute of Technology Carolyn Giroux is an instructional designer at Wentworth
Director of Aspirations Evaluation at NCWIT for the past 9 years. ©American Society for Engineering Education, 2025TeachEngineering.orgLevel up on pre-collegeengineering educationand outreachTeachEngineering.org is a free digital library of over T H E T E AC H E N G I N E E R I N G C U R R I C U L U M I S :1900 classroom-tested, standards-aligned K-12 AC C E S S I B L E S TA N DA R D S - A L I G N E Dengineering resources created in collaboration with Free hands-on K-12 engineering resources that use low-cost, Most of our
) satisfaction, and (4)impact of the project on teaching and learning.We sent email invitations with a link to the online survey to the 25 faculty that had led one (ormore) TLIF project(s) on July 31, 2024 and the survey was available until August 31, 2024. Thesurvey was conducted anonymously, and we received 18 responses, corresponding to a responserate of 72%. While we have data on the demographic characteristics of faculty that led a TLIFproject (e.g., gender, rank/position, and department) based on the applications, due to theanonymous nature of the survey, we cannot break down the responses in terms of thesecharacteristics.To analyze the data, we use descriptive statistics for responses to the nominal and Likert scaleitems and thematic analysis for
efforts, but a large enough sample size is needed to identify significant trends.Nationwide-scale case study:S&E degrees awarded based on gender, race, and gender + raceThe National Science Foundation report, Diversity and STEM: Women, Minorities, and Personswith Disabilities 2023 [6], is a common source of information on representation in STEM fields.The report analyzes data from the National Center for Science and Engineering Statistics(NCSES). The data tables created for the report are available for download by gender,race/ethnicity, and citizenship status by each of the STEM categories. The STEM categoriesincluded in this data include science and engineering (S&E) and non-S&E fields.The data are very complete, but are provided as
work and do notreflect the views of the NSF.References [1] World Economic Forum, “How to address disinformation,” October 2022. Accessed: 2025-01-13. [2] C. Engledowl and T. Weiland, “Data (Mis)representation and COVID-19: Leveraging Misleading Data Visualizations For Developing Statistical Literacy Across Grades 6–16,” Journal of Statistics and Data Science Education, vol. 29, pp. 160–164, Aug. 2021. Publisher: Taylor & Francis eprint: https://doi.org/10.1080/26939169.2021.1915215. [3] S. Yeom, “Teaching and assessing data literacy for adolescent learners,” in Deep Fakes, Fake News, and Misinformation in Online Teaching and Learning Technologies, pp. 93–123, IGI Global, 2021. [4] K. Janacsek, J. Fiser, and D. Nemeth
change modelShadle, S. E., & and adoption of evidence-basedBullock, D. instructional practices (EBIPs)Shadle, S. E., 2017 To understand faculty perspectives 169 faculty and staff Qualitative Various STEM fields, Dormant’s Chocolate Yes Not specific; focused broadly on facultyMarker, A., & Earl, on drivers and barriers to from 12 departments including biology, Model of Change engagement with evidence-basedB. implementing STEM education at Boise State chemistry, engineering, instructional practices (EBIPs
transfer students at four-year institutions, with the goal of strengthening engineering identity and supporting national STEM advancement. Prior to joining FIU, Daniel served as a STEM Specialist with the Ministry of Education in Dubai. He is also an author and founder committed to advancing inclusive and impactful STEM education.Dr. Bruk T Berhane, Florida International University Dr. Bruk T. Berhane received his bachelorˆa C™s degree in electrical engineering from the University of Maryland in 2003. He then completed a masterˆa C™s degree in engineering management at George Washington University in 2007. In 2016, he earned a PhDr. Jingjing Liu, Florida International University Dr. Jingjing Liu is a Postdoctoral
-situated laboratories in the context of electrochemistry by engaging students inproductive engineering practice.NomenclatureI, Current the battery is cycled at (A)V+, Volume of electrolyte in the posolyte tank (m3)V–, Volume of electrolyte in the negolyte tank (m3)F, Faraday’s constant (96,485 C mol–1)b, column vector containing the constant reaction terms (mol m–3 s–1)K, matrix containing rate constants for species decay and crossover in the system (mol m–3 s–1)𝐶, Column vector containing all bulk concentration (mol m–3)𝐶𝐴∞,+ , Bulk concentration of species A in the positive half-cell (mol m–3) ∞,+𝐶𝐴+ , Bulk concentration of species A+ in the positive half-cell (mol m–3)𝐶𝐵∞,− , Bulk concentration of species B in the positive half-cell
AchievementAbstractThe National Science Foundation (NSF) Scholarships in Science, Technology, Engineering, andMathematics (S-STEM) program supports low-income, high-achieving STEM students throughscholarships and tailored support services. This paper compares the implementation and impactof three different S-STEM projects across three diverse institutions—Rowan University, AlbanyState University, and Tennessee University, highlighting their distinct approaches and outcomesfor diverse student populations.At Rowan University (RU), a public R2 university in the northeastern United States, the 5-yearS-STEM project — Engineering Persistence: Support System for Low-Income Students toCatalyze Diversity and Success — targets undergraduate engineering students
the engineeringeducation context which included SNA. To guide our research toward the study purpose, weprepared the following Research Questions (RQs):RQ1: What is the current breadth of SNA in the engineering education context?RQ2: What areas of SNA in engineering education warrant systematic review(s)?For this research brief, we present key publication, study context, and methodological trends inthe data through an analysis of code frequency. Specifically, we will focus on findings related toRQ1 by identifying the number of records that included each code.MethodologyA scoping review, as presented by Grant and Booth “provides a preliminary assessment of thepotential size and scope of available research literature” [30, p. 95]. We selected
Google Colab. Using claude.ai [18] the response is: Response - Claude 3.5 This Python script: 1 import svgwrite 2 from I P y t h o n . d i s p l a y i m p o r t d i s p l a y , HTML 3 import ipywidgets as widgets 4 from I P y t h o n . d i s p l a y i m p o r t c l e a r o u t p u t 5 c l a s s DFlipFlop : 6 def init ( self ) : 7 s e l f . s t a t e = 0 # Output Q 8 self . prev clock = 0 910 def update ( s e l f , clock , data ) :11 # U p d a t e s t a t e on r i s i n g e d g e o f c l o c k12 i f c l o c k == 1 and s e l f . p r e v c l o c k == 0 :13 s e l f . s t a t e = data14
. IEEE articles of interest Group one: healthcare providers accessing technology [27] [28] [29] [30] [31] [32] [33] [34] at a distance to provide patient care (remote access to technology) Group two: patients accessing healthcare providers at a [35] [36] [37] [38] [39] distance (remote access to personnel) Group three: training healthcare workers to design and [40] [41] use technology Group four: supporting healthcare workers [42] [43] [44]Group one included eight articles, which described improving remote access to technology forpatient care, including: ultrasound for pregnancy [27] and digital pen for documentingpartograph [28], low-power nebulizer [29], diagnosis of urinary tract infection(s) [30] andpreeclampsia [31
intelligence (AI) powered conversational educational agents: The inevitable paradigm shift,” Asian Journal of Distance Education, vol. 18, no. 1, Art. no. 1, Mar. 2023, Accessed: Jan. 15, 2025. [Online]. Available: https://www.asianjde.com/ojs/index.php/AsianJDE/article/view/718[2] B. Khosrawi-Rad et al., “Conversational agents in education–a systematic literature review,” 2022.[3] M. D. Koretsky and A. J. Magana, “Using Technology to Enhance Learning and Engagement in Engineering,” Advances in Engineering Education, 2019, Accessed: Jan. 15, 2025. [Online]. Available: https://eric.ed.gov/?id=EJ1220296[4] S. H. Tanvir and G. J. Kim, “WIP: Generative and Custom Chatbots in Computer Programming Education and their Effectiveness A
= c o m p u t e D e r i v a t i v e ( func , x , h ) 3 % Computes t h e n u m e r i c a l d e r i v a t i v e o f f u n c a t x 4 % u s i n g a c e n t r a l d i f f e r e n c e method . 5 % func : Function handle . 6 % x : P o i n t a t which t o compute t h e d e r i v a t i v e . 7 % h : Step s i z e . 8 d e r i v a t i v e = ( func ( x + h ) − func ( x − h ) ) / (2 * h ) ; 9 end1011 % Example u s a g e :12 f = @( x ) s i n ( x ) ;13 x v a l = p i / 4 ;14 s t e p s i z e = 0 . 0 0 1 ;15 d e r i v v a l = c o m p u t e D e r i v a t i v e ( f , x v a l , s t e p s i z e ) ;16 d i s p ( [ ” D e r i v a t i v e a t x = ” num2str ( x v a l ) ” : ” num2str ( d e r i v v a l ) ] ) ;1718 f 2 = @( t ) t . ˆ 2 ;19 t v a l = 2 ;20
, quantitative analysis for both face validity and contentvalidity evidence can be evaluated using various metrics. Face validity evidence for theinstrument was evaluated using Item Face Validity Index (IFV-I), Universal Agreement ScaleValidity (S-IFV/UA), and Average Scale Face Validity (S-IFV/Ave) [27]. The IFV-I indicatesthe percentage of raters who assign an item with clarity of 3 or 4. The S-IFV/Ave is calculatedby averaging the IFV-I scores across all items on the scale, or alternatively, the mean clarity andcomprehension ratings from all raters. The proportion of clarity is determined by averaging theindividual ratings provided by each rater. The S-IFV/UA refers to the proportion of items on thescale that receive clarity ratings of 3 or 4 from
Development modules are embedded within existing2nd year courses (Basic Analog Electric Circuits, Basic Digital Circuits, and Introduction toElectronics) in hybrid/remote modality for all students to experience. A select group of students(6 in total- 3 from HBCUs/MSIs and 3 from PWI(s)) are chosen for the continuation to a summerinternship with pre- and post- internship mentorship and training. Collaborators RPI and NotreDame have the same structure of participants. Thus, the total numbers are: 6 IEC-HBCUs(Howard, Tuskegee, UMES, North Carolina A&T, Prairie View A&M, and FAMU/FSU), and a © American Society for Engineering Education ASEE 2025total of 12 students with pre
integration of advancedsustainability concepts. Our multi-phase implementation approach, scheduled to commence in Fall2025, is supported by compelling evidence from multiple educational studies. Constantinou et al.'s2022 longitudinal research demonstrated that similar curriculum enhancements increased studenttechnical competency scores by 35% on average across 427 students, while Martinez et al.'s 2023study showed a 42% improvement in building performance assessment capabilities.The curriculum optimization framework incorporates specialized modules on post-pandemicdesign elements, real-time building performance analysis, and hybrid instructional methodologies.Analysis of comparable programs indicates these enhancements can be implemented with
services that we provide to the whole society can't be interrupted. Basically, if your activity is so important, energy production for example, you need to be able to manage the crisis in an overall way." (FG#04- A)Public safety professionals also agreed with the importance of equipping engineering studentswith EDCM skills and knowledge. An assistant chief in a fire department in Texas (S#003)viewed engineers as subject matter experts (SMEs) who can provide crucial information thathelps emergency responders to assess situations and build action plans. In addition, theprofessionals highlighted importance roles of engineers during EDCS, being designers of safeindustrial processes and facilities (S#002) and the first line of defense
every spring semester since.One research-cited reason that collegiate students leave engineering is a lack of engineering-related experiences during the first year of the program. Conventional first-year engineeringcurricula require students to complete multiple gateway courses prior to beginning disciplinarycoursework. These courses oftentimes deal with abstract material with little perceivedengineering context. As a result, students end up believing that all engineering courses will besimilar, and some ultimately leave for other professional arenas where applications can beunderstood much earlier in academic career(s). A key motivating factor in developing ENGR 111was to augment student desire to persist in engineering degree pursuit, by
corresponds to the theoretical side and simulations.Bibliography1. Groover M.P., Fundamentals of Modern Manufacturing Materials, Processes andSystems, 2nd Ed., Wiley, 2004.2. Eltantawie M.A.E., Design, Manufacture and Simulate a Hydraulic Bending Press, Int.J. Mech. Eng. & Rob. Res., Vol. 2, No. 1, January 2013.3. Kumar, M. et al., Design and Fabrication of Pneumatic Sheet Metal Cutting and BendingMachine, International Journal of Engineering Research and Advanced Technology,Special Volume 2, Issue 1, May, 2016.4. Salem, C.B. and Meslameni, W., A Numerical Investigation of the Springback in Air Vbending of Aluminum 1050 A, International Journal of Research in IndustrialEngineering, Vol. 11, No. 2, 119-133, 2022.5. Kalpakjian, S. and Schmid, S.R
: Undergraduate Research Increases Self-Efficacy and Career Ambitions for Underrepresented Students in STEM,” J. Res. Sci. Teach. https://doi.org/10.1002/tea.21341.[3] Watkins-Lewis, K. M., Dillon, H. E., Sliger, R., Becker, B., Cline, E. C., Greengrove, C., James, P. A., Kitali, A., and Scarcella, A., 2023, “Work In Progress: Multiple Mentor Model for Cross-Institutional Collaboration and Undergraduate Research,” American Society for Engineering Education, Baltimore MD.[4] Dillon, H., Cline, E. C., Hadnagy, E., Rodriguez, S. L., Sesko, A. K., Sliger, R. N., and Wilson, N., 2024, “Work in Progress: Transformation Course-Based Undergraduate Research Experience (T-CURE).” [Online]. Available: https://peer.asee.org/work-in
double coded. A Cohen’sKappa value of κ = 0.72 across all three rounds was achieved, indicating strong inter-raterreliability and agreement beyond chance [39].3. ResultsSince this is a research brief, only the results of the Delphi study after round 3 will be presentednext. The full set of results from rounds 1 through 3 will be presented in a forthcoming article.Relevance Ratings. The average relevance ratings (on a 1-5 scale) and standard deviations (s)for the various conceptions of judgment given in Table 1 during the final Delphi round rangedfrom 3.00 (s=1.17) to 4.88 (s=0.33) based on n=17 responses. Decision making (item 7 in Table1) had the highest average relevance of 4.88 and the smallest standard deviation of s=0.33,indicating the
from [9]: µ0 I ˆ B= ϕ (3) 2πswhere s represents the perpendicular distance from the wire, and ϕˆ is the azimuthal basis vector,and I is the current magnitude. When multiple sources (current-carrying wires) are present, theresulting magnetic field is the sum of all fields sourced by each individual wire, according to theprinciple of superposition. Therefore, it is possible to visualize the magnetic field associated witha system containing an arbitrary number of infinite current-carrying wires in a VR environment.The user may interactively manipulate the
prioritize user needs and societal impact.AcknowledgementThis material is based upon work supported by the National Science Foundation under Award No.#2315662. Any opinions, findings, and conclusions or recommendations expressed in this materialare those of the authors and do not necessarily reflect the views of the National Science Foundation.ReferencesBureau of Labor Statistics. (2021). Employment in STEM occupations: U.S. Bureau of Labor Statistics. https://www.bls.gov/emp/tables/stem-employment.htmCasale, C., Thomas, C. A., & Simmons, T. M. (2018). Developing empathetic learners. Journal of Thought, 52(3–4), 3–18.Cook, K. L., & Bush, S. B. (2018). Design thinking in integrated STEAM learning: Surveying the landscape
framework for the BIM feasibility learning metricproposed in this paper.Proposed methodologyThe proposed methodology consists of four basic steps, and it is focused on a learningenvironment: 1. Students need to be familiar with the BEP framework that will be used, including shaping the part of the company (or entire company) that will be carried out in the BEP scheduling. 2. Students must develop the preliminary deliverables for each BEP framework step. 3. BEP scheduling: assigning time and resources (human resources and materials) to develop the S-Curve (accumulated cost -or expenditure over time). 4. Develop the BEP feasibility metric.1st step: BIM and BEP familiarizationThe Project execution Planning framework used in this
questions that relied heavily within the applying, analyzing,and evaluating levels of knowledge from Bloom’s revised taxonomy, building upon the lowerlevels of knowledge like remembering and understanding, but not asking questions that focusedwithin those lower levels. Differences between these collected domain-specific studies are basedheavily on the intentions of the surveys. Turner et al. [31]’s survey is intended for a widerpopulation of US adults and to establish a concept inventory for energy and power grid knowledge.Basic energy knowledge questions are included in Turner et al.’s survey, but a majority of thequestions require higher-level energy knowledge applied specifically to power grid use andinfrastructure. While Prince et al. [32]’s
, consists of five 1-DoF rotational robotic linksplaced one next to the other and mounted on a 60 cm × 12 cm acrylic frame. Each link has aHitech HS-475HB servo motor, an Adafruit BNO055 Inertia Measurement Unit (IMU) sensor,and an STM32 Nucleo-L432KC microcontroller (refer to Figure 2). The Hitech HS-475HB Servomotor is the actuator of the robotic link, with a range of rotation of about 180o . It accepts a PulseCode Modulation (PCM) signal with a minimum of 500 µs and a maximum of 2500 µs of width.The Adafruit BNO055 IMU sensor is an intelligent 9-Axis absolute orientation sensor thatintegrates a triaxial 14-bit accelerometer, a triaxial 16-bit gyroscope with a range of ±2000o /s, atriaxial geomagnetic sensor, and its own 32-bit ARM Cortex M0
history component was therefore created, and launchedat the Japanese university, with Indonesian undergraduates also taking the course as remotelearners. To evaluate the effectiveness of the new interdisciplinary COIL, it was assessedalongside five other existing modules and the results were compared, with the key object ofinvestigation being the effect on participating students’ global competence. In total twoSTEM non-COIL modules, two STEM COIL modules (including the newly created one witha history component), and two history modules (one COIL and one non-COIL) had their pre-and post-program GC scores calculated using the Miville-Guzman Universality DiversityScale – Short Form (MGUDS-S). Results indicated that the two STEM non-COILs and