EducationRepository (PEER) database was carried out to find papers closely related to the current studywhich can provide guidance for this research. One benefit of using this database is that the PEERpapers are most convenient to download from a single site. Six key papers were identified andthoroughly reviewed to provide a foundation for the study. The following paragraphs summarizethe findings of this sample of the literature.Estrada and Atwood [6] explained that the factors leading to the most frustration among studentstaking laboratory-based courses are difficulties with equipment and troubleshooting, difficultieswith concepts from the theory, and confusing lab documents. Woods [7] listed several key skillsfor troubleshooting problems: knowledge about a
”The gate reviews improved several aspects of the course. The industry experts withunderstanding of instructional design were able to contribute significantly to make the courseaddress contemporary issues relevant to the course. Their contributions during the earlystages of the course development and during gate reviews resulted in improvements in coursematerial, delivery methods and level of assessments. Improvements were observed in overallstudent performance. The following sections indicate some of the improvements experienced.5.1. Quality improvements in course materialThe course material was systematically developed with multiple gate reviews as discussed inthe previous sections. Workbook and laboratory worksheets were introduced for the
before leaving the classroom. The second group participatedin this course also in person and after the face-to-face lecture they were assigned to complete thesame worksheets online and submit them electronically in the Canvas Learning ManagementSystem. The only changed factor between the two groups was the worksheet formats. Thecomparison between the two groups is based on the average grades in learning objectivesthrough assessment measures such as exams and laboratory experiments which was kept similarfor the two groups. The assessment measures and tools are explained in detail in the next section.2. Methodology and approachIn this section we have provided information about the Digital/Microprocessor Basics(EET2141) course and introduced
homework,” Southern Economic Journal, vol. 78, no. 4, pp. 1333–1345, April 2012.[6] J. A. Holdener and B. D. Jones, “Calculus homework: A storied approach,” PRIMUS, vol. 29, no. 1, pp. 21–42, May 2019.[7] L. Pogačnik and B. Cigić, "How To Motivate Students To Study before They Enter the Lab," Journal of Chemical Education, vol. 83, no. 7, pp. 1094–1098, July 2006.[8] M. Rollnick, S. Zwane, M. Staskun, S. Lotz and G. Green, “Improving pre-laboratory preparation of first year university chemistry students,” International Journal of Science Education, vol. 23, no.10, pp. 1053-1071, Oct. 2001.[9] G. O’Brien and M. Cameron. "Prelaboratory activities to enhance the laboratory learning experience," in Proceedings of The Australian
was introduced already in the 1990s, and adecade later a vivid discussion continued regarding the role and added value of designexperiments, design research, and design-based research for educational research [6], [7], [8],[9].Both in the management science and learning sciences, the need for design science is justifiedwith bridging of practice to theory, thereby advancing practices alongside theories. Inlearning sciences, the design experiments are seen as a means of studying learningphenomena in the real world instead of the laboratory, thus arriving at better understanding ofthe contextual aspects or learning and enabling the establishment of better learningconditions. Like educational research in other disciplines, also engineering
options of online teaching methods1,2,3 prior to making thetransformation of the on-campus course to the on-demand course. Our on-demand approach boresome resemblance to the online modality. The following steps were taken in such transformation.Revision of the course learning outcomesIn the transition from the on-campus, in-person course in fall 2019 to the online, on-demandcourse in summer 2020, the course learning outcomes for the in-person course were reviewed. Inthe review, we found that most of the outcomes could be transitioned to the on-demand coursewithout modifications. For outcomes involving in-person, in-laboratory experiments, they werenot feasible in that summer term due to campus closure. They were replaced by computer-aidedcontrol
company and as founding Director of the Center for Integrating Research & Learning (CIRL) at the National High Magnetic Field Laboratory, Florida State University. Under Dr. Spiegel’s leadership, the CIRL matured into a thriving Center recognized as one of the leading National Science Foundation Laboratories for activities to promote science, mathematics, and technology (STEM) education. While at Florida State University, Dr. Spiegel also directed an award winning teacher enhancement program for middle grades science teachers, entitled Science For Early Adolescence Teachers (Science FEAT). His extensive background in science education includes experiences as both a middle school and high school science teacher
(interactions, delivery), in class(interactions, delivery), assessment, laboratory support, and educational technology. Theseresults are summarized in Table 8 for faculty support and in Table 10 for TA support. Somestudents did not have any additional suggestions to provide for faculty or TAs to support theirlearning. These responses were coded as "None." Some responses were off topic in that neitherfaculty or TAs had control over what was being requested. These responses were coded as "OffTopic." Finally, some responses were descriptive and not specific enough to place into anyprimary category of course planning and delivery. These responses were coded as "Intangible."In order to understand whether student expectations shifted from traditional to
technology(ABET), the different engineering program outcomes include applying knowledge of mathematics,science and engineering, designing and conduct experiments, designing a system, components tomeet realistic needs, functioning in a multidisciplinary team, formulating and solving engineeringproblems, communicating effectively, etc. [3]. Various researchers have made attempts toincorporate these requirements in their courses independently. For example, various researchstudies exist on related topics such as problem solving [4-8], course or laboratory projects [9-13],technology in classroom [14-17], teamwork [18-21], experiential learning [22-25], design skills[26-28], etc.BackgroundPublished literature in the past [1-4] presents details about
throughout the entiresemester. These groups were arranged such that neither gender was placed in a minority. Afterthe completion of the semester-long data collection, researchers selected consented groups basedon complete attendance, meaning that no group member was absent from a week of datacollection. Participant demographics, such as age, race, and engineering major, were notcontrolled in this study. Groups were spread across four registered sections, each taught by threeteaching assistants. In this paper, we analyze data from two weeks of 50-minute discussionsessions held in a laboratory classroom.Data AnalysisGroups’ video and audio data were collected as they solved each task. This study analyzes datafrom 22 total video recordings, one from
Engineering, Mathematics, and Physics.Undergraduate students from each major assisted faculty in the development of the VR lessons.One undergraduate research assistant from each of the five STEM areas assisted the faculty indeveloping and testing the lessons. The research assistants gained experience in the lessondevelopment process starting from establishing learning objectives, and then storyboarding andprototyping.The implementation of these lessons was in the following courses 1) Introduction to AerospaceEngineering, 2) Aerodynamics-I, 3) Molecular Cell and Genetic Biology, 4) Molecular Cell andGenetic Biology Laboratory, 5) Signals and Systems, 6) Microprocessors, 7) Pre-Calculus andAlgebra, 8) Calculus 1, 9) Differential Equation, 10) Physics I
“collective intelligence” of a groupsolving simulated laboratory tasks is determined by the type of interactions they have. Thesefindings suggest that effective team dynamics within a learning group improve performance.Other studies link these positive interactions to friendship. Myers found that self-selected groups,which favor group selection among friend groups, reported higher relational satisfaction andlearning during group tasks [21]. Theobald reported that having a friend in a group activity in aSTEM class was predictive of group comfort levels [22].3 MethodsThis study used qualitative methods: narrative analysis was applied to transcripts ofsemi-structured interviews. Interviewers asked second and third year engineering majors at aprivate
Paper ID #32840”I Wish I Would Have Known. . . ”: Characterizing Engineering Students’Reflections on Their Graduate ExperiencesMr. Kanembe Shanachilubwa, Pennsylvania State University I am a second-year doctoral candidate at Pennsylvania State University in the mechanical engineering department. Member of the Engineering Cognitive Research Laboratory (ECRL). Current research topics include graduate school attrition and student well-being.Miss Megan ElleryGabriella M. Sallai, Pennsylvania State University Gaby Sallai is currently a graduate student in the mechanical engineering department at Penn State. She is working under
. For this week, twocompletely different topics were being studied: electrochemistry in particular batteries and areview electrolysis as well as coordination compounds and complex ion solubility. Two differenttopics were being studied in one week based on the calendar and trying to incorporate the conceptof coordination compounds before they were covered in the laboratory class.Examples of student responses in week 12 reflect the conceptual confusion on the coordinationcompounds. Student 1 stated “What remains unclear to me is how to name complex ions, ligands,and determining which are cis-trans.” Student 2 noted: “Identifying the coordination number(number of attached ligands), oxidation states of metals in the coordination compounds
University of Louisiana at Lafayette. His research interests are in Hydrology, Water Resources, Rainfall Remote Sensing, Water Management, Coastal Hydrology, and Advances in Hydrology Education ResearchProf. David Tarboton, Utah State University David Tarboton is a professor of Civil and Environmental Engineering, Utah Water Research Laboratory, Utah State University. He received his Sc.D. and M.S. in Civil Engineering (Water Resources and Hy- drology) from the Massachusetts Institute of Technology and his B.Sc Eng in Civil Engineering from the University of Natal in South Africa. His research and teaching are in the area of surface water hydrol- ogy. His research focuses on advancing the capability for hydrologic
(NSF) grants CCF-0939370, and OAC-2005632, by the Foundation for Food andAgriculture Research (FFAR) grant 534662, by the National Institute of Food and Agriculture(NIFA) grants 2019-67032-29077 and 2020- 70003-32299, by the Society of Actuaries grant19111857, by Cummins Inc. grant 20067847, by Sandia National Laboratories grant 2207382, andby Gro Master. Any opinions, findings, and conclusions, or recommendations expressed in thismaterial are those of the authors and do not necessarily reflect the views of the funding agencies.References[1] S. Hurtado, R. M. Gonyea, P. A. Graham, and K. Fosnacht, “The relationship between residential learning communities and student engagement,” 2019.[2] C. Ujj, “Impact of Living-Learning Communities on
you weld too fast on cast iron it will crack because of that. Getting that application is really useful, solidifies the information you learn and contextualizes it.Connecting theoretical concepts with application: for Liam it is through YouTube, for theauthors on this manuscript, it was through choreographed laboratory experiences. We ask, does itmatter which channel is employed? What seems clear is that contextualized learning, suchwatching a YouTube video, facilitates both individual and collaborative processes of learningand knowledge building [26]. This promotes a rich, deeper understanding for students, and webelieve that these online channels should be integrated and celebrated as critical component ofone’s development into
. Analyze simple Internal Combustion Engine performance 8. Perform Free and Forced Convection, Conduction, and Radiation experiments 9. Communicate experimental results in a written engineering format that fulfills WE requirementsME-3335 Course Objectives:Through hands-on laboratory exercises and computational simulations, students will have theopportunity to master the engineering skills necessary to achieve the learning outcome. Specificcourse objectives are as follows: 1. Utilize physical equipment and instrumentation to acquire data from a variety of simple thermal fluids systems, 2. Pose scientific questions and follow the corresponding procedures in an experiment designed to answer those questions, 3
Paper ID #34305Test Anxiety and Its Impact on Diverse Undergraduate EngineeringStudents During Remote LearningDr. David A. Copp, University of California, Irvine David A. Copp received the B.S. degree in mechanical engineering from the University of Arizona and the M.S. and Ph.D. degrees in mechanical engineering from the University of California, Santa Barbara. He is currently an Assistant Professor of Teaching at the University of California, Irvine in the Department of Mechanical and Aerospace Engineering. Prior to joining UCI, he was a Senior Member of the Technical Staff at Sandia National Laboratories and an
documents that successful course completion is lower in online courses than intraditional face-to-face courses [21]. Both course completion rates and withdrawals are worse inSTEM courses [22], particularly in lower level STEM courses [23]. A lack of engagement andlower successful completion rates have been shown in online physics courses [24] as reported byMurphy and Stewart. Murphy and Stewart used eight years of data with 3,032 students tocompare face-to-face lecture courses with three semesters of a hybrid course with online lecturesand face-to-face laboratories. They found that there was a 11% lower successful completion rate(A/B/C) for students in the hybrid course compared to the solely face-to-face course. Thesefindings in STEM courses are
) Learning Laboratory, a design-oriented facility that engages students in team-based, socially relevant projects. While at Texas A&M University Imbrie co-led the design of a 525,000 square foot state-of-the-art engineering education focused facility; the largest educational building in the state. His expertise in educational pedagogy, student learning, and teaching has impacted thousands of students at the universities for which he has been associated. Imbrie is nationally recognized for his work in ac- tive/collaborative learning pedagogies, teaming and student success modeling. His engineering education leadership has produced fundamental changes in the way students are educated around the world. Imbrie has been a
. 2017.[3] S. Jaikaran-Doe, A. Henderson, E. Franklin, and P. Doe, Strategies for promoting cultural diversity within student laboratory groups in an engineering degree course at an Australian uni ersit , Australasian Association for Engineering Education Annual Conference 2018, Hamilton, New Zealand.[4] M. V. Jamieson and J. M. Sha , Appl ing Metacogniti e Strategies to Teaching Engineering Innovation, Design, and Leadership, Proceedings of the Canadian Engineering Education Association, 2017.[5] S. Beecham, T. Clear, J. Barr, M. Daniels, M. Oudshoorn, and J. Noll, Preparing Tomorro s Soft are Engineers for Work in a Global En ironment, IEEE Software, vol. 34, no. 1, pp. 9 12, Jan. 2017.[6
. 2019, Accessed: Mar. 07, 2021. [Online]. Available: https://peer.asee.org/using-natural- language-processing-tools-on-individual-stories-from-first-year-students-to-summarize-emotions-sentiments- and-concerns-of-transition-from-high-school-to-college.[25] M. Szoke, A. Borgoltz, M. S. Kuester, N. Intaratep, W. J. Devenport, and A. Katz, “The Development of Remote Laboratory Sessions at the Stability Wind Tunnel of Virginia Tech During the Coronavirus Pandemic,” in AIAA Scitech 2021 Forum, American Institute of Aeronautics and Astronautics.[26] J. Devlin, M.-W. Chang, K. Lee, and K. Toutanova, “BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding,” Oct. 2018, Accessed: Nov. 05, 2020. [Online
laboratories community through Twitter connections," Twitter for research handbook, 2015, [Online]. Available: http://www.academia.edu/download/41349806/Massimo.Menichinelli_MakerLaboratoriesCommunit y_on_Twitter_PREPRINT_HIRES.pdf.[15] V. Wilczynski, "A Classification System for Higher Education Makerspaces," 2017.[16] M. B. Jensen, C. C. S. Semb, S. Vindal, and M. Steinert, "State of the Art of Makerspaces - Success Criteria When Designing Makerspaces for Norwegian Industrial Companies," Procedia CIRP, vol. 54, pp. 65–70, Jan. 2016.[17] E. Mañas Pont, "Analysis and comparison of representative locations in the general makerspace panorama," Universitat Politècnica de Catalunya, 2014.[18] Craig Forest, Ms. Helena Hashemi
). Thesemulti-citers, as we call them above, indicate that a cluster of scholars, a program in the field, orseveral laboratories are committed to the work of reading, understanding and citing Blackwomen as the founders of intersectionality. This uptake allows us to resist the tendency toexplain away critical or purposeful reading practices: “Oh, I was never asked to read this ingraduate school!” Or, “Yeah, we don’t really read ‘that stuff’ in engineering.”These trends represent some pain points that the field might do well to reflect and act on. Evenwithin the field’s efforts to address equity and inclusion, Black women’s knowledge appears tobe delegitimized or erased. For Jones and Dotson, the choice to omit or carefully integrate Blackwomen into our
features is shown in Table 2. We first categorized the jobpostings based on the types of institutions. Postdoc appointments under universities were assignedto “academia.” Other appointments at national laboratories, industry research centers, or corpora-tions were categorized as “non-academia.” To further extract the structure from the text data, theKSAs and domain discipline dictionaries were applied to analyze the job posting data. The wordfrequencies were calculated based on the two dictionaries. Two lists of identified KSAs and main Table 1: KSAs Features Dictionary KSAs Features Examples of KSAs Features - Grants/awards adjudication - Mock
demonstrated that studentschoose different learning pathways (infrequent vs. frequent vs. no searching) which providesempirical support for a UDL approach to course content design and delivery.LimitationsThe results presented in this study include event data from COVID-19 affected semesters andnon-COVID19 semesters prior to 2020. The data are from authentic learning environments ofengineering courses under non-laboratory controlled conditions. Our current analysis is limitedto event logs of higher education students in a subset of undergraduate engineering courses atone university in the U.S. using a single web tool
Paper ID #34949Identifying Signature Pedagogies in a Multidisciplinary EngineeringProgramDr. Kimia Moozeh, University of Toronto Kimia Moozeh has a PhD in Engineering Education from University of Toronto. She received her Hon. B.Sc. in 2013, and her Master’s degree in Chemistry in 2014. Her dissertation explored improving the learning outcomes of undergraduate engineering laboratories by bridging the learning from a larger context to the underlying fundamentals, using digital learning objects.Lisa Romkey, University of Toronto Lisa Romkey serves as Associate Professor, Teaching Stream and Associate Chair, Curriculum