acrossundergraduate engineering, and to create a shared definition of EML for OSU ’s College of Engineering.3.2 Need for instructional EM trainingWhile we believed our curriculum changes were strong and had research supporting their efficacy [15], we realizedthat we needed a better way to onboard members of our teaching team to this new approach of engineeringinstruction. Given that KEEN provides many training opportunities for faculty, instructors were able to engage inprofessional development through the network. However, our undergraduate teaching assistants (UTAs) and graduateteaching associates (GTAs), who are crucial to our teaching teams, did not have access to the same external resources.Furthermore, engagement with faculty development through the
options for curriculum design in first-year programs.Background and ObjectivesIn the mid-2000’s, a call went out to integrate the teaching of science, technology, engineering,and mathematics into what we now collectively refer to as STEM [1]. Since that time, additionalinitiatives have suggested that it might be even more beneficial to integrate the arts into STEMlearning, creating STEAM. Some even argue that it should be pushed even further, addingadditional study of the societal implications of STEAM research and work, further lengtheningthe acronym to STEAMS [2]. For this paper, the focus will remain on STEAM and itsimplications for the first-year engineering curriculum.Students’ experiences in their first-year engineering (FYE) classes are
any comments – only the information of the instruments – the operator activatesthe independent variable and collects the information of the dependent variable(s). in the spirit tomake the process INTERACTIVE, the video is, in reality, a Video Quiz. The Video Quizincludes questions during the implementation of the experiment to ensure students' knowledgeand understanding of what they are doing.Given that the implementation of the experiment is remote, all the questions are multiple-choicequestions. Any time a question is presented, the video stops, and the students need to answer. Ifthe answer provided is the correct answer, the video continues. If the answer is wrong, thestudents need to rewind the video, observe the phenomenon again, and
findings to the user. The user has theability to input a variety of parameters including farm acreage, crop selection, investment capital,and solar panel type. Through calculations using these inputs and the various data sets, the user ispresented with an “outputs” page, which includes a solar array installation cost estimate, as wellas an AgPV revenue proforma based on market rates and compares it to traditional farming. Themodel provides an opportunity cost measure which is the loss of potential gains when one optionis chosen over another option. For the AgPV model, the projected revenue is compared to theincome from the S&P500’s inflation-adjusted yearly average return of 8.5% [22]. The AgPVdecision model allows a user to take advantage of
students to perform statistical analysisand data visualization and to use EXCEL spreadsheets for data representation and calculations.While Module 2 does not cover errors in measured data, the other two modules do address thistopic. In the next stage of the module development process, we plan to compare how each course-specific module covered topics such as errors in measured data.Table 6. Example Teaching Modules Module Module 1 (Monitoring Module 2 (Engineering Module 3 (Engineering Tool Topic and Analysis of the Hydrology) Hydrology) Environment) Module Errors in measured Visualization and Errors in measured data, Topic(s) data, Statistical
qualitative data using various coding methods. Two research team members readthe reflections and compared results. One researcher read reflections sequentially by student bycategory and identified salient patterns across participants. For example, Reflection 1 fromStudent 1 in the top 10% increase category was read first, followed by Student 1’s Reflections 2and 3. Then, Reflection 1 from Student 2 in the top 10% increase category was read, and so on.A second researcher read each reflection to determine similarities and differences incharacteristics and analyze patterns across reflections. This research team member readreflections as they were written chronologically within each category. All Reflection 1 samplesin the 10% increase category were read
hasdecided to conduct all 2021-2022 reviews virtually and it expects to review over 1080 programsacross all four commissions during the accreditation cycle. Over 730 of these programs will beevaluated by EAC.The objectives of this study were to: • gather input on best practices and opportunities for improvement in all elements of the virtual review, including pre-visit preparation, virtual “on-site” operations, team dynamics, communication and training, and • provide recommendations for future virtual reviewsResults of surveys, author(s)’ observations, and recommendations to improve future reviews -whether in-person or virtual - are presented in this paper. Lessons learned address suggestionsfor improvement for future virtual reviews
under Grant No.1743666. We thank Stephanie Jarek for assistance compiling the information sources.ReferencesAustin, A. E. (2002). Preparing the next generation of faculty: Graduate school as socialization to the academic career. The Journal of Higher Education, 73(1), 94-122.Beqiri, M. S., Chase, N. M., & Bishka, A. (2009). Online course delivery: An empirical investigation of factors affecting student satisfaction. Journal of Education for Business, 85(2), 95-100.Borrego, M., & Henderson, C. (2014). Increasing the use of evidence‐based teaching in STEM higher education: A comparison of eight change strategies. Journal of Engineering Education, 103(2), 220-252. https://doi.org/10.1002/jee.20040Cannon
patterns in Activity 7 Activity #8: Failure Case Study Presentations Usual format: In teams of three, the students investigate a failure case study prior to classand the activity is used for group presentations of their findings. Given a series of library andweb-based resources, student teams select a building failure case study and create a four-minutePowerPoint presentation which answers the questions: Which building system type failed?Which key components of the system were involved and how did they fail? Who suffered fromthis event? Which profession(s) was involved with the cause? What could have been donedifferently to have prevented the situation? Each student in the team has to participate in thepresentation. The student teams
of Engineering, Educating Engineers: Preparing 21st Century Leadersin the Context of New Modes of Learning. Washington, D.C.: National Academy Press, 2013.[9] Harrisberger, L., & others. Experiential Learning in Engineering Education. AmericanSociety for Engineering Education, 1976.[10] Fisher, D. R., Bag, A., & Sarma, S. Developing Professional Skills in UndergraduateEngineering Students through Co Curricular Involvement. Journal of Student Affairs Researchand Practice, 54, 3, pp. 286–302, 2017. https://doi.org/10.1080/19496591.2017.1289097[11] Simmons, D. R., Creamer, E. G., & Yu, R. Involvement in Out of Class Activities: A MixedResearch Synthesis Comparing Outcomes of Engineering to Non- engineering UndergraduateStudents
/indicator_reg.asp (accessed Mar. 07, 2021).[8] C. Riegle-Crumb, B. King, and Y. Irizarry, “Does STEM Stand Out? Examining Racial/Ethnic Gaps in Persistence Across Postsecondary Fields,” Educational Researcher, vol. 48, no. 3, pp. 133–144, Apr. 2019, doi: 10.3102/0013189X19831006.[9] J. Rothwell, “The Hidden STEM Economy,” Brookings, Jun. 10, 2013. https://www.brookings.edu/research/the-hidden-stem-economy/ (accessed Mar. 07, 2021).[10] S. M. Pennell, “Queer cultural capital: implications for education,” Race Ethnicity and Education, vol. 19, no. 2, pp. 324–338, Mar. 2016, doi: 10.1080/13613324.2015.1013462.[11] R. Straubhaar, “Student Use of Aspirational and Linguistic Social Capital in an Urban Immigrant-Centered English Immersion
impact your ethical knowledge, reasoning, or behavior?” Alumni rated sixengineering related activities, three non-engineering related, and could add other(s). Theresponse options provided were: did not participate, involved but no impact (0), small impact (1),moderate impact (2), large impact (3). Near the end of the survey, individuals were askedwhether they might be willing to participate in an interview about how their ethics instruction asa student impacted them after graduation. The survey concluded with demographic questions:year they had taken the targeted course, year they had earned their Bachelor’s degree, open-ended line to fill in the major of their Bachelor’s degree, whether or not they had earned graduatedegrees, types of
, January 24, 2018. [Online]. Available: https://www.insidehighered.com/digital- learning/article/2018/01/24/blendflex-lets-students-toggle-between-online-or-face-face. [Accessed April 15, 2021].[9] R. Zaurin, S. D. Tirtha, N. Eluru, “A Comparison between Mixed-Mode and Face-to-Face Instructional Delivery Approaches for Engineering Analysis: Statics,” in 127th American Society for Engineering Education (ASEE) Annual Conference & Exposition, Virtual, June 22-26, 2020.[10] Learning Assistant Alliance Resources: Generalized Program Elements, online: https://sites.google.com/view/laa-resources/generalized-program-elements. Accessed February 28, 2021.[11] R Core Team. (2020). R: A language and
, students are required to complete pre- and post-assignments toprepare them for the module and reflect on their learning, respectively.The course culminates with students writing a Personal Action Plan. This plan incorporates areflection on the choices students made as they created their pathways through the course, apersonal engineering statement focusing on the personal qualities that they seek to exhibit as anengineer, a personal vision (one-year or five-year), and the proposed initial step(s) they plan totake in fulfilling that vision.Analysis: How does choice support exploration and self-understanding?This course structure is designed to support the course learning goals. In the subsequent analysis,we investigate the extent to which providing
Distinguished Teaching Award.” https://marinebiology.uw.edu/news-stories/2019/04/24/jose-m-guzman-receives-uw- distinguished-teaching-award/ (accessed Apr. 30, 2020).[11] A. J. Franco Mariscal, J. M. Oliva Martínez, and S. Bernal Márquez, “An educational card game for learning families of chemical elements,” Journal of Chemical Education, vol. 89, no. 8, pp. 1044–1046, 2012.[12] J. C. Roberts, C. Headleand, and P. D. Ritsos, “Sketching designs using the five design- sheet methodology,” IEEE transactions on visualization and computer graphics, vol. 22, no. 1, pp. 419–428, 2015.[13] D. Roam, The back of the napkin: Solving problems and selling ideas with pictures. Portfolio, 2013.[14] M. Scaife and Y. Rogers, “External cognition: how
students from the Fall 2016 andSpring 2017 semesters and correlated with the Week 8 cumulative score. RESULTSResults from the Cinematic Meditation Exercise We computed the mean Week 8 cumulative score for the following categories of students:(a) those who submitted the essay for the cinematic meditation assignment, denoted by S andSUMMER 2020 VOLUME 8 ISSUE 2 13 ADVANCES IN ENGINEERING EDUCATION Interventions for Promoting Student Engagement and Predicting Performance in an Introductory Engineering Class Figure 7
ensure qualityCommittee Size: Depending on the program, the committee consists of anywherefrom 6 students to 20 students. These numbers do not include additional volunteersthat may be recruited closer to the actual event.Recruitment/Membership: For BEST of CWIT and Cyber 101 Program, thecommittees are led by a staff member, as well as the Student Lead(s) for thatparticular program. Student Lead(s) apply for their positions each spring for thefollowing academic year. Bits & Bytes is led by a staff member. Recruitment for theplanning committees is done through email to current scholars and affiliates, andstudents apply by completing a Google Form. Student Lead(s) and staff select theplanning committees. The students on the planning committees
reference to thedefinition of bits in timer 2’s control register which is provided in the microcontroller’s datasheet.Cognitive load theory predicts that when these elements are spatially or temporally separated,such as refer- ring to a textbook, a datasheet, and traditional source code, additional extraneousload is imposed to successfully integrate these elements. Because LP encourages including allthese elements as a part of the document, as shown in Figure 2(b), we hypothesize that the use ofliterate programs will reduce extraneous load, thereby improving students’ ability to master theseconcepts, which will lead to higher test scores.We investigated the impact of LP in a digital system design course because modern hardwaredescription languages
bymanipulating weights within the penalty function in lieu of applying constraints on responses.To illustrate operation of the solution algorithm, we present a hypothetical class of 17 students thatwill be assigned to three project teams, one of which will be closed shown in Figure 2: A B C D E F G H J K L M N P Q R S Gender Male Male Male Male Male Female Female Male Male Male Male Male Male Female Male Female Male Ethnicity Hispanic Hispanic Black White White White White White White Asian White White White Asian White