powerful tool in curriculum design and studentengagement in the lab experiments. We aim to provide a resource for other instructors who areinterested in participatory design of courses, providing participatory design experiences forstudents in a lab course, or implementing a novel course in synthetic biology. In the future, wewill collect data on student experiences to identify the aspects of participatory design thatstudents find most helpful.Appendix A. Example Lab ScheduleWeek In your lab session: Pre-lab Due and Quiz1 Welcome and Introduction, Lab Safety No pre-lab due2 Lab 1: Making Media and Pouring Plates3 Lab 2: Isolation of plasmids pOSIP-KL-mcherry and pE-FLP4 Lab 3: DH5-alpha Chemicompetent cell
freshman seminar: a citation analysis study. Reference Services Review 32(3): 284-292.16. Subramanyam, Krishna. 1981. Scientific and Technical Information Resources. New York: Marcel Dekker, Inc.17. Auger, C.P. 1998. Information Sources in Grey Literature. London: Bowker Saur.18. MacLeod, Roderick A. and Jim Corlett. 2005. Information Sources in Engineering. Munchen: KG Saur. Page 15.278.17
the classroom. The current solution to tackle these challengeswas implementing a professional identity assessment [3], as well as utilizing the reflectionsto better understand their experiences and what needs arose from the program. IntroductionThe at-home remote patient monitoring sector of healthcare is a growing industry. Thishealthcare market is valued at $24 billion and is projected to reach $166 Billion by 2030 [1],[4]. This industry provides individuals with disabilities or chronic medical conditions withnew levels of independence by allowing them to remain at home. These companiesleverage technology and personally crafted care plans that address the needs of theirclients. The technologies
their peers internationally, especially for science and math scores where they were not in top-ten nations [2]. Although there has been significant effort in the last decade to address the issue onnumerous fronts, such as the growth of STEM-focused schools, the level of impacts of theinterventions due to multiple reasons, such as limited literature on STEM-school outcomes, studentselection criteria, and others continue to limit the effectiveness of the efforts [3]. Further, theeducational disruptions due to the COVID-19 pandemic have also contributed to a decline insecondary student performance and learning, with average mathematics scores in 2022 lower thanthe previous years [4]. Furthermore, the Program for International Student Assessment
://www.wenger-trayner.com/introduction-to-communities-of-practice, 2015.[14] P. D. Sherer, T. P. Shea, and E. Kristensen, "Online communities of practice: A catalyst for faculty development," Innovative Higher Education, vol. 27, no. 3, pp. 183-194, 2003.[15] F. van As, "Communities of practice as a tool for continuing professional development of technology teachers’ professional knowledge," International Journal of Technology and Design Education, vol. 28, no. 2, pp. 417-430, 2018.[16] S. Ma, G. L. Herman, M. West, J. Tomkin, and J. Mestre, "Studying STEM faculty communities of practice through social network analysis," The Journal of Higher Education, vol. 90, no. 5, pp. 773-799, 2019
Education, vol. 107, pp. 140–163, Jan. 2018. [3] “Education: U.S. Civil Engineering Schools | Engineering News-Record.” [4] D. D. Truax, “Civil engineers: Declining numbers and increasing need,” Sept. 2022. [5] R. Krishnamoorthy, “Many colleges plan to close down civil engineering dept. in Tiruchi region,” The Hindu, Apr. 2021. [6] A. R. Raman, “30 colleges to close civil engineering courses,” The Times of India, Apr. 2021. [7] S. Urolagin, I. Upadhyaya, and A. A. Thakur, “Data Visualization and Analysis of Engineering Educational Statistics,” International Journal of Advances in Applied Sciences, vol. 7, p. 309, Dec. 2018. [8] R. B. Corotis and R. H. Scanlan, “Future of Civil Engineering Profession and Role of Education,” Journal of
dissemination can be simplified as a list that we useto check our work in all that we develop. 1. Develop motivation to practice better communication by connecting this science communication work to student, faculty, and institutional success. 2. Have a simple set of tools that everyone has training in and is committed to use both in their communication and in their feedback to others about how that communication has worked. 3. Plan for continuous engagement with repeated touch points that start with a mix of mandatory sessions and opt-in opportunities and build toward a common acceptance of the value of this work. 4. Reinforce a
students with technical proficiency in ML, especially with a rise in AI/ML-focusedsenior design projects over the past few years. During our pilot offering of the BME ML coursein Spring 2024, we designed and taught a one-week module about diversity, equity, andinclusion (DEI) problems in ML with the following learning objectives (LOs): 1. Assessing whether a question solved by ML exacerbates existing society bias. 2. Understanding “distribution shift” from training data to real-life usage, which is the source of bias in ML systems. 3. Designing equitable ML systems with considerations of the “right” problem and dataset.MethodsOur one-week module consists of one lecture (80 minutes) and one hands-on lab (approximately90 minutes
50-min lectures had to be freed. In the past, three reviewsessions were done before the midterms, and two project description sessions were needed forthe smaller assigned projects. The review sessions were moved to out-of-class Q&A sessions,with the opportunity to watch previously recorded review sessions asynchronously. The projectdescription lectures were not needed anymore. The final (6th) lab session was used to test thetruss and was added to the class time by moving the third midterm to the final exam slot afterclasses ended. Figure 3: Student welding components of their prototype. Figure 4: Student welding the prototype truss connections behind a protective screen. Figure
Midterm Exam Week 9 Spring Break – No Class – Project Assigned Week 10 Lab 1 – Field Operations with a Theodolite Measurement of Horizontal Distances Week 11 Lab 2 – Leveling Week 12 Lab 3 – Traverse Survey Week 13 Lab 4 – Topographic Survey Week 14 Project Week 15 Project Week 16 Finals Week – Project PresentationsOverall, the course curriculum is currently structured as follows: 1. Learning Stage Division: The curriculum divides the learning process into two main stages. In the first half of the semester, students acquire knowledge about surveying principles, and in the second half of the semester, students transition to applying this knowledge in practical settings, including laboratory
AC 2012-4437: AUTOMATED PROBLEM AND SOLUTION GENERATIONSOFTWARE FOR COMPUTER-AIDED INSTRUCTION IN ELEMENTARYLINEAR CIRCUIT ANALYSISMr. Charles David Whitlatch, Arizona State UniversityMr. Qiao Wang, Arizona State UniversityDr. Brian J. Skromme, Arizona State University Brian Skromme obtained a B.S. degree in electrical engineering with high honors from the University of Wisconsin, Madison and M.S. and Ph.D. degrees in electrical engineering from the University of Illinois, Urbana-Champaign. He was a member of technical staff at Bellcore from 1985-1989 when he joined Ari- zona State University. He is currently professor in the School of Electrical, Computer, and Energy Engi- neering and Assistant Dean in Academic and
added design considerations to a finalJamboard for each of the stakeholders that could address some of the potential harms and benefits.Results The instructors worked through this activity step-by-step, explaining the relevantdefinitions and giving the students time to think to themselves and with their group before addingtheir ideas to the Jamboard. One full class session, approximately one hour, was devoted to thisactivity and surrounding discussions. After a Jamboard was populated, the class discussed theresponses and then moved on to the next step. Figure 1 shows the general flow of the Jamboards.Figure 1: Outline of Jamboard flow. Note: Stakeholder 1 is used as an example, but the processwas completed for stakeholders 1, 2, 3, and 4
for the course design. Building new context-richcourses can be a challenge that is often underestimated and undervalued [3-5]. Ultimately, wedesigned the course to prepare students for their senior engineering design experience through alocally informed engineering design project based on interviews with sustainability andeducation stakeholders. Through this work, we developed three objectives of the course: (1) helpstudents bridge their theoretical knowledge of energy with their understanding of the localenergy infrastructure, (2) give students the opportunity to apply sustainability concepts withinthe chemical engineering framework, and (3) analyze the economic, social, and technical impactsof engineering decision-making.IntroductionAs many
experience in structural design, analysis, and construction processes. He also served in several construction legal litigations as an expert witness. Dr. Maleki’s current research agenda is the application of new technologies to improve the undergraduate construction education. Dr. Maleki has published several technical and scientific papers in peer-reviewed journals and international conferences. He is a member of multiple scientific societies and serves as a peer reviewer for several journals. ©American Society for Engineering Education, 2024 Application of LiDAR Technology in Construction Education - Case study: Estimating CourseAbstractThis study explored the use of LiDAR
already addressed via the ABET evaluation process? • RQ3. What are the best measurements to evaluate the mentor experience and student- employment outcomes for which there are comparatively fewer precedents?To identify published research precedents for the RQs, a truncated systematic literature review(e.g., truncated PRISMA [3]) was carried out. The phrase “civil engineering capstone” wassearched for within the ASEE PEER [4] database in the fields of title, conference session name,document content, tagged topics, and tagged divisions, resulting in 135 relevant records. Notethat “environmental engineering” was deliberately not included in the search phrase given thecomparatively rarer nature of environmental engineering being in
climaterather than promoting equity and justice through the practice of engineering (e.g., [2], [3]).These efforts are important and necessary, but they are insufficient – they do not equip faculty toaddress issues such as systemic racism and identity-based exclusion in the academic content ofinfrastructure-focused courses.Communities of practice (CoPs) are both a learning theory and a theory of change. Wehypothesize that a national faculty CoP can effect change in this context – transforminginfrastructure education from a focus on decontextualized technical content to a social-technicalendeavor. Approximately 10 years ago, an effort to create a model course for undergraduateinfrastructure education evolved into a national Community of Practice focused
improved we were able to collect pre-requisite course grades for students that took thecourse at the UA and at PCC (or another transfer institution).The first course, ECE 320 (Circuit Theory) had 230 students over 3 semesters and its requiredprerequisite course is ECE 220 (Basic Circuits). When a student took ECE 220 multiple times tosatisfy the ECE 320 pre-requisite, we only counted the final try. Originally new UA freshmanrepresent 126 of these students and and 51 were 2 year school transfers when they first came tothe UA (the rest are international, or 4-year transfers or some other registration category). Thesecond course, CE 333 (Structural Engineering) had 92 students and its required prerequisitecourse is CE 215 (Mechanics of Solids). Sixty
- mean-for-civil-engineers.[4] Y. Walter, "Embracing the future of Artificial Intelligence in the classroom: the relevance of AI literacy, prompt engineering, and critical thinking in modern education," International Journal of Educational Technology in Higher Education, vol. 21, no. 1, 2024, doi: 10.1186/s41239-024-00448-3.[5] "Artificial Intelligence Tools: Advancing meaningful learning in the age of AI." Oregon State University. Accessed" Dec. 28, 2024. [Online.] Available: https://ecampus.oregonstate.edu/faculty/artificial-intelligence-tools/blooms-taxonomy- revisited/[6] Y. Song, et al., "A framework for inclusive AI learning design for diverse learners
modelsand iterated the process to create a functional unit. Such a system can be further modified toenable various configurations of heat exchanger internals that were unavailable in the physicallab. By enabling students to create, combine, and repeatedly use these modular systems, thisexperiential learning enables deeper engagement and personalized learning.IntroductionOne of the hallmark characteristics of chemical engineers are their ability to design, analyze, andoperate unit operations [1], [2]. Their ability to do so usually starts during their undergraduateeducation, where they take a Unit Operations Laboratory (Unit Ops Lab) course. Traditional UnitOps Labs face several challenges with both accessibility and cost, making them only
, specifically in Process Control [3], but the implementation of labexperiences in process control courses have been largely constrained in many higher-educationinstitutions by several factors like lack of equipment and technical support [4]. Several initiativeshave been reported to compensate for this deficiency including classroom lab kits [3], remotelabs [4], [5], [6], virtual lab simulators [6], [7], [8], [9], and the use of data from unit operationexperimental modules [10] among others.Our chemical engineering curriculum includes a capstone senior course on Process Control, 5credit units, with a companion laboratory course (1 credit hour). The lab includes six fullyautomated experimental setups, three for liquid level control and three for
EDUCATION Rafael S. Gutierrez, Sergio Flores, Fernando Tovia, Olga Valerio, Mariano Olmos. ”Simulation Based Modeling of Warehousing Operations in Engi- neering Education Based on an Axiomatic Design.” MAS 2011: The 10th International Conference on Modeling and Applied Simulation, September 12-15, 2011. Rome, Italy. (Collaborators representing the University of Texas at El Paso; Universidad Autonoma de Cd. Juarez; Philadelphia University; El Paso Community College) RECENT COLLABORATORS Professor Rafael Gutierrez, UTEP; Professor Sergio Flores, UTEP; Ar- turo Bronson, UTEP; and Peter Golding, UTEP.Ms. Tonie Badillo, El Paso Community College Ms. Tonie Badillo is a Division Dean at the Valle Verde campus of El Paso
engineering, including determinacy in students’ statics class,normal stress in their subsequent mechanics of materials class, and the method of virtual work intheir structural analysis class. Repeatedly investigating the same structure, in varying contextsand across the curriculum, increases the relevance of the underlying theories, as well as reducesstudent’s “cognitive load” associated with learning a new concept while internally relating theanalytical model to an actual structure. A key feature of this project is that the anchored learningmethodology can be implemented within an already crowded engineering program of study withminimal change to the curriculum, learning outcomes, and learning objectives. This aspect isessential for the anchored
survey and sponsorship of the IRB protocol at GT. Page 26.236.10 References[1] "Student chapters", ASEE Student Division: A blog for the students in the American Society for Engineering Education: ASEE Student Division.[2] Carberry, A., "Engineering education communities and societies": engineeringeducationlist, 2011.[3] Berger, E. J., Diefes, H. A., Hamaker, K. H., Jones, J. D., McComb, S. A., Mulkay, E. L., and Oakes, W. C., "Asee student chapters: Perspectives on and preparation for higher education", Journal of Engineering Education Vol. 87, No. 3, 1998, pp. 231-234
and the Main Library have beendesignated to house the mathematics collection. The Main Library houses the Main Stacks,which stores over 5 million items. Nearly 10,000 linear feet of the print Math Library collectionwill be temporarily housed in the Main Stacks during the 3-4 years of the Altgeld Hallrestoration project.The Math Library is a unit within the Physical Sciences and Engineering Division (PSED) of theUniversity Library System and therefore maintains a close working relationship with PSEDdivision hub, the Grainger Engineering Library Information Center (GELIC). GELIC, like theother libraries, employs Pre-Professional Library and Information Science (LIS) GraduateAssistants (GAs). The GA position allows these future librarians to
which further enhances tech-proficiency. To reiterate,not every simulation is posted as a clicker and some are utilized for instructional purposes only.There are a few non-PhET sims that are used in class due to lack of sim availability for all thetopics.Class Environment:The flipped classroom model emphasizes active engagement and participation. Lecture time isstructured to involve problem-solving and interactive questioning, which complements theintegration of tools like clickers and simulations to enhance understanding of complexengineering concepts.Clicker Question Formats:There found to be an optimal 3-clicker limit per 50-minute lecture sessions based on studentfeedback from spring 2022 semester. Therefore springs 23 and 24 semesters
Paper ID #49310BOARD # 31: Work in Progress: Supporting Student Learning with Notetakingin Lectures Based on Visual CommunicationDianne Grayce Hendricks, University of California, Santa Cruz Dr. Dianne Hendricks is an Associate Teaching Professor in the Biomolecular Engineering Department at the University of California at Santa Cruz. She teaches molecular biology labs, biotechnology, universal design, and technical communication courses. Prior to UC Santa Cruz, Dianne was an Associate Teaching Professor in the Department of Human Centered Design and Engineering (HCDE), the Director of the Engineering Communication Program, and
visual study tools ratherthan traditional reading-writing methods.It is important to consider that through the application of different teaching methods theknowledge can be further approached. In architecture, it is necessary to make relationsbetween theoretical aspects and concepts with much more practical and technicalapplications. Thus, the requirement of having a broad comprehension of topics and therelations between them is fundamental. Through mind maps, graphic relations can be madebetween the several topics covered on a course. Visual tools can help “clarify the relationshipbetween material objects and concepts to understand” [3]. The critical challenges faced byan ArPM (Architect Project Manager) are ‘poor planning,’ ‘unfamiliar
visualizations. 2. To focus students on thinking critically about what statistical parameters indicate in a particular problem. 3. To facilitate students’ ability to read and respond precisely to an engineering-related problem. To develop our approach and content, we drew from literature across multiple fields, including information and data literacy pedagogy, technical writing in engineering, argumentation, and data visualization. The resulting data literacy module comprises assignments paired with applied engineering problems derived from the existing scientific literature and real-world datasets.We deployed the new assignments in Fall 2024. While we have confidence in the revised module, werecognize that some elements of the assignments
, May 2015, doi: 10.15390/EB.2015.4167.[24] F. Tang, “Content Analysis Approach: A Review on the Extent of Science and Engineering Curriculum Meet Competency Requirements for Testing, Inspection and Certification Industry,” in 2018 IEEE International Conference on Industrial Engineering and Engineering Management (IEEM), Dec. 2018, pp. 1356–1360. doi: 10.1109/IEEM.2018.8607398.[25] Rong Tang and Watinee Sae-Lim, “Data science programs in U.S. higher education: An exploratory content analysis of program description, curriculum structure, and course focus,” Educ. Inf., vol. 32, no. 3, pp. 269–290, Jul. 2016, doi: 10.3233/EFI-160977.[26] J. W. Creswell, Educational Research: Planning, Conducting, and Evaluating
of simulation assignments.References[1] F. Stern et al., "Integration of simulation technology into undergraduate engineering courses and laboratories," International Journal of Learning Technology, vol. 2, no. 1, pp. 28-48, 2006.[2] K. A. Shollenberger, "Computational fluid dynamics (CFD) within undergraduate programs," in ASME 2007 International Mechanical Engineering Congress and Exposition, 2007, pp. 361-366: American Society of Mechanical Engineers Digital Collection.[3] K. Volkov, "Thermofluids Virtual Learning Environment for Inquiry-Based Engineering Education," WSEAS Transactions on Advances in Engineering Education, no. 3, pp. 94-107, 2011.[4] S. Noor and A. Rahman, "Recent advances in the use of