, most students were aerospaceengineering majors. Ninety-two percent of the participants were male and ninety seven percentwere 21 years old or younger.3.3 Data CollectionThree data collection mediums were used in this study:[A] Course records were graded and compiled by the instructor on each student’s usage of theweb log interface in Blackboard. Key information gathered were organized as the quality of Page 25.620.5post, determined by a 4-point scale (i.e. 2 points for thoroughness, 1 point for relevance and 1point for peer comment(s)) and student participation which is the number of posts submitted perstudent minus any “mis-posts” or duplicates
multiple semesters or years and allowsprojects to address complex and compelling needs.EPICS teams, or course sections, consist of 8-24 students and are student led with a faculty orindustry mentor (called an advisor), and a graduate teaching assistant (TA). Each team comprisesmultiple sub-teams, each one of which supports a single design project. The project timelines arecompletely decoupled from the semester schedule allowing projects to span multiple semestersor even years allowing projects of significant scope to be developed. Once a project is delivered,a new project is then identified by students under the guidance of their faculty mentor(s) andcommunity partner(s).Student assessment data indicates that students who are involved in EPICS
and practitioners. In order to improve its globalcompetitiveness, the United States must grow its science, technology, engineering andmathematics (STEM) workforce. Although the engineering sector has grown in past years, in2012, engineers comprised only 1.2% of the U. S. workforce.18 The U. S. Department of Laborforecasts growth in workforce needs among all of the major engineering disciplines (chemical,civil, electrical, industrial and mechanical); however, the projected demand for civil engineers isfar greater compared to the other disciplines (Table 1). 19 This is largely due to the need for civilengineers to address issues related to the country’s aging infrastructure and to the design anddevelopment of new infrastructure needed to
opportunity to integrate evidence-based education practices into the lab portion of the coursethat aimed to aid in students’ learning of technical writing practices. Table 1 compares Autumn2019’s lab schedule and associated technical writing post-lab assignments with Autumn 2020’slab schedule and associated technical writing post-lab assignments.Table 1: Autumn 2019’s lab & assignment schedule compared to Autumn 2020. Post-labs with technical writingfocus that are part of the complete quantitative analysis for this paper are denoted with blue text. Post-lab Full LabReports used for comparisons through t-tests are denoted with red **. Week Autumn 2019 Autumn 2020 Lab
measurement of engineering identity was accomplished using an adapted version of Godwinet al.’s (2016) measure of identity. Godwin et al. concludes that an engineering student’sengineering identity is a function of four attitudes relating to interest, performance, recognitionand agency. Interest is the student’s innate attraction to the subject material surroundingengineering, such as math, science and physics. Performance is an academic self-efficacyconstruct measuring how much a student believes in their ability to positively perform inacademically in engineering coursework. Recognition is how a student believes they arerecognized as an engineer, particularly by meaningful others such as parents or professors.Finally, agency or as Godwin et al
statistically significant decrease.The engineering profession largely requires students to be multifaceted so communication ofhow project skills translate might provide an opportunity for course improvement. These twoquestions have some of the highest variances, suggesting there may have been a subset ofstudents with very solidified career plans. Question 6 and 8’s averages are above a 4, suggestingstudents had high expectations for the course to impact the community and help them becomemore aware of the needs of the community. However, by the end of the course, a statisticallysignificant decrease is observed. One aspect of the service-learning experience that might besacrificed in the approach detailed in this article is potential to build strong
such as theones that are increasingly being used in entry-level freshman classes lead professors and teachingassistants to engage with them. This is something students appreciate, especially freshmen whoare often not especially engaged with their engineering departments 10. In Reisslen et al.’s 8survey of freshman students who had taken a hands-on laboratory sequence, many of the onlysurvey questions that showed significant differences were ones relating to their interactions withthe professor and teaching assistant. Students rated their opportunities to interact with bothprofessor and teaching assistants higher after having taken the class than before.Relevance of Mathematics. Perhaps the only negative consequence of teaching a
StudentsIntroductionThe College of Engineering at Rowan University, a four-year, mid-sized, suburban, publicuniversity in the North East, is in the fourth year of a six year NSF S-STEM grant (Scholarshipsfor Science, Technology, Engineering and Math). In addition to providing two cohorts ofstudents with four year $3,000 dollar annual scholarships, students are provided targetedmentoring, participate in an Engineering Learning Community (ELC) in the first year, and areprovided with tutoring-on-demand for core engineering courses throughout the four-year degreeprogram.Only students with financial need were accepted into the S-STEM scholarship program and ELC.Students from under-represented groups in Engineering were aggressively recruited, i.e., women,African
professional connectedness.24 The increased sense of professionalconnectedness associated with engaging in service is characterized through the five stages(exploration, clarification, realization, activation and internalization) of Delve et al.’s ServiceLearning model.32 Based on this framework, multiple iterations of a preliminary student survey,and student interviews, evidence of validity and reliability were established. Thus, theEngineering Professional Responsibility Assessment (EPRA) is an appropriate tool for assessingthe development of social responsibility in engineering students.24Previous results using EPRA found that female engineering students had more positive SRattitudes than male engineering students.24 It was also found that students
learning modes used to overcome thelearning-style mismatch include active learning, collaborative and cooperative learning, and Page 12.560.3problem- or project-based learning7,1.Table 1. Dimensions of Learning Styles6 (Felder & Brent, 2004) Dimension Types of Learners within each Dimension Perception Sensing/Sensors Intuitive/Intuitors Input Modality Visual(s) Verbal(s) Processing Active(s) Reflective(s) Understanding Sequential(s
computer programming students: a middle eastern and American comparison. IEEE Transactions on Education, 2006. 49(4): p. 443-50.15. Felder, R.M., Learning and teaching styles in foreign and second language education. Foreign Language Annals, 1995. 28(1): p. 21-31.16. Ma, L., et al., Investigating the viability of mental models held by novice programmers. ACM SIGCSE Bulletin, 2007. 39(1): p. 499-503.17. Bonar, J. and E. Soloway. Uncovering principles of novice programming. in Proceedings of the 10th ACM SIGACT-SIGPLAN symposium on Principles of programming languages. 1983. Austin, Texas: ACM.18. Brown, H. D., & Gonzo, S. T. Readings on second language acquisition. Englewood Cliffs, NJ: Prentice Hall
. Stylus Publishing, LLC., 2017.[7] W. C. Newstetter, “Of Green Monkeys and Failed Affordances: A Case Study of a Mechanical Engineering Design Course,” Res. Eng. Des., vol. 10, no. 2, pp. 118–128, 1998.[8] D. Armel and S. A. Shrock, “The Effects of Required and Optional Computer-Based Note Taking on Achievement and Instructional Completion Time,” J. Educ. Comput. Res., 1996.[9] S. A. Lei, “Revisiting Extra Credit Assignments Perspectives of College Instructors,” J. Instr. Psychol., 2010.[10] T. Park, C. S. Woods, S. Hu, T. B. Jones, and D. Tandberg, “What Happens to Underprepared First-Time-in-College Students When Developmental Education is Optional? The Case of Developmental Math and Intermediate
LLC is only for first-year students, the factors and skillsets participants learn stay with them their remaining time atFAMU.References[1] K., Inkelas, J.E. Jessup-Anger, M. Benjamin, and M.R. Wawrzynski, (2018) Living LearningCommunities that work: A research-based model for design, delivery, and assessment. StylusPublishing, LLC.[2] K. Inkelas, Z. E., K. E., Daver, Vogt, and J., Leonard, (2007). Living–Learning Programsand First-Generation College Students’ Academic and Social Transition to College. Research inHigher Education, 48(4), 403-434. doi: 10.1007/s11162-006-9031-6[3] K. Inkelas, M. Soldner, S. Longerbeam, and J. Leonard (2008). Differences in StudentOutcomes by Types of Living–Learning Programs: The Development of an Empirical
ƉƌĞƐĞŶƚ ƚĞĐŚŶŝĐĂů ŝŶĨŽƌŵĂƚŝŽŶ ŝŶ ƚĂďůĞƐ ĂŶĚ ŐƌĂƉŚƐtƌŝƚĞ ƌĞƉŽƌƚƐ ĂŶĚ ŐŝǀĞ ŽƌĂů ƉƌĞƐĞŶƚĂƚŝŽŶƐZK E/E' d/s/d/^ ƐƐĞƐƐ ŝŵƉĂĐƚƐ ŽĨ ƐĞůĞĐƚĞĚ ŐůŽďĂů Θ ƐŽĐŝĞƚĂů ŝƐƐƵĞƐ ƚƚĞŶĚ ƉƌŽĨĞƐƐŝŽŶĂů ƐŽĐŝĞƚLJ ŵĞĞƚŝŶŐƐ ĂŶĚ ŽƚŚĞƌ ƐƚƵĚĞŶƚ ĨƵŶĐƚŝŽŶƐ ƉƉůLJ ĐƌĞĂƚŝǀĞ ƉƌŽďůĞŵ ƐŽůǀŝŶŐ ƚĞĐŚŶŝƋƵĞƐDĂŶĂŐĞ ƚŝŵĞ ĂŶĚ ƌĞƐŽƵƌĐĞƐ ĚƵƌŝŶŐ ƉƌŽũĞĐƚƐ Page 13.855.15 Figure 10. Linkages between the freshman curriculum and the engineering disciplinesAssessmentDuring the 2006-07 academic year, the Living with the Lab curriculum was tested in pilotsections of honors students one last time before being fully implemented throughout the Collegeof
supported coursewith an A or a B and is recommended for the position by their instructor. Many of these coursesare freshman-level mathematics and chemistry courses, as well as some sophomore-levelengineering courses. PAL leaders attend class for the section(s) they support so they are aware ofthe current material being discussed. This also allows them to build rapport with the instructor aswell as the students enrolled in the section(s) they support. Leaders then hold two 80 minutesessions each week. During sessions, leaders facilitate collaborative activities and studentdiscussions related to course topics as well as provide a safe place to ask questions and makemistakes along the way. We intentionally hire undergraduate students, rather than
, June), Advising Engineering Students to the BestProgram: Perspective, Approaches, and Tools Paper presented at 2012 ASEE AnnualConference & Exposition, San Antonio, Texas. https://peer.asee.org/20898[8] Bonwell, C.C., and J. A. Eison, “Active Learning: Creating Eccitement in theClassroom,” ASHEERIC Higher Education Report No.1, George Washington University,Washington, DC , 1991.[9] Freeman, S., Eddy, S. L., McDonough, M., Smith, M. K., Okoroafor, N., Jordt, H., &Wenderoth, M. P. (2014). Active learning increases student performance in science, engineering,and mathematics. Proceedings of the National Academy of Sciences, 111(23), 8410-8415.[10] Johnson, D., R., Johnson, and K. Smith, Active Learning: Cooperation in the CollegeClassroom
predefined projects, with the knowledge they had coming into the course and with theadditional resources.Qualitative responsesTable 4-6 lists some representative responses from the students open-ended statements.Table 4: Project Preference Qualitative Statements Given the three available options (RAD, AGP, and Pre-defined Projects), describe which project(s) you would prefer and why. 1. I prefer something where there are a set of rules and principles that I would follow. I do not feel confident in creating anything because of my current lack of technical knowledge. 2. AGP [prompt-based OEP] because there is structure but also it is open ended. 3. RAD [free-choice OEP] because it gives the best relevant experience to creating, designing
Society for Engineering Education Annual Conference & Exposition.Edington, S., Holmes Jr., A. L., & Reinke, P. (2015). A tale of two common reads: Models for developing a successful common reading program for first-year engineering students. In American Society for Engineering Education.Godwin, A., Potvin, G., Hazari, Z., & Lock, R. (2016). Identity, critical agency and engineering: An affective model for predicting engineering as a career choice. Journal of Engineering Education, 105(2), 312–340.Good, C., Rattan, A., & Dweck, C. S. (2012). Why do women opt out? Sense of belonging and women’s representation in mathematics. Journal of Personality and Social Psychology, 102(4), 700–717.Jordan, K. L
, Cohort 2 has almost twice the number of students. This is one set ofdata points that suggest the approaches utilized in STRIDE are not only effective, but may evenbe improving in their execution. It should be noted that there could also be various reasons forthese changes, and continuous improvement and revisiting of new data is recommended. A boostin overall average of Cohort 2 over Cohort 1 could have been as a result of a stronger incomingfirst year class. It could have also been due to the recent implementation of university-wide firstyear advising. In the year that Cohort 1 was in their first year, the university did not have its newFirst Year advising model. In Cohort 2’s first year, the university did have it. Hence, this couldhave also
of 1998. Itis administered by the National Science Foundation’s Division of Undergraduate Education(DUE). The program was modified in 2004 and is now known as the Scholarships in Science,Technology, Engineering, and Mathematics (S-STEM) Program. The CSEMS Program supportsacademically talented students, financially needy students for study in the “targeted disciplines”of computer science, engineering, and mathematics; the S-STEM program will additionallysupport study in other natural sciences. Although metrics of financial need are established by thefederal government, participating institutions interpret thresholds for academic merit andfinancial need based on local circumstances. In addition to supporting students with financialneed, the
disaster. In defense of their entity, the students createdan opening statement for the defense, called up to three defense witnesses/experts and composeda defense closing summary statement. In addition to defense, students were allowed to cross-examine witnesses called by other defendants and prepared questions in advance. The aim of thecross-examination was for the students to identify and clarify weaknesses in the arguments andpositions presented by other entities and to make sure information given was complete andaccurate.The overall purpose of this mock hearing was to engage the students in critical thinking andanalysis in a fun and relevant manner. The first objective was to identify what technical error(s)occurred and then dig deeper and try
which are the most effective or have the greatest return on effortinvested. Other variables of interest are the students’ prior team experience in K-12, the students’team experience in their other first year classes, and the effects of the DBT learning curve ingoing from the first cycle to the second cycle.References1. Knight, D. W., Carlson, L. E., & Sullivan, J. F. (2007). Improving engineering student retention through hands-on,team based, first-year design projects. 31st International Conference on Research in Engineering Education,Honolulu, HI, June 22-24, 2007.2. Mena, I. B., Zappe, S. E., & Litzinger, T. A. (2013). Examining the experiences and perceptions of first-yearengineering students. ASEE Annual Conference and Exposition
QuestionsMidterm Section 13 Section 18 OverallEngineering Design Process (15) 82% 89% 85%The Role of Failure in Engineering (25) 92% 91% 91%Solution Development and Selection (10) 88% 90% 89%Nature of the Design Process (10) 93% 89% 91%FinalImportant Process Steps (30) 94% 97% 95%Table 5. Summary of Errors and Omissions in Student Vignette Analyses (Midterm) Didn't mention problem identification and 15 research at all Student stated that s/he needed more 14
number of students will indicate they want less of a particular project type as those whoindicate they want more.Another trend in the data was that if a student knew what engineering major s/he wanted cominginto the program, there was typically one project that helped cement that choice, often related tothat major, and possibly another project that helped them determine what they did not want to do.Minor Design projects, which are design-and-build are mentioned, along with weekly homeworkprograms. These are both listed in many categories. The responses show that certain projects areperceived as connected to particular engineering majors, and participating in those clearly helpedstudents make decisions on those majors. In the comments, the
significant differences in perceivedabilities at either the course outset or end of the course across the control and experimentalsections. In experimental sections, the majority of team tasks were broken down and assigned,whereas in the control sections this was left up to the team. It is possible that students in controlsections were more aware of each other’s work because task assignments required ongoingnegotiation throughout the quarter. Alternatively, control teams who divided tasks throughout thequarter according to teammates’ perceived strengths may have felt able to assess teammates’contributions by referencing the perceived quality of the deliverable(s) for which each teammatewas primarily responsible.To gain additional insight, we isolated
. Nora Honken, University of Cincinnati Nora is an Assistant Professor in the Engineering Education Department at The University of Cincin- nati. She holds a PhD in Educational Leadership and Organizational Development for the University of Louisville, a MS in Industrial Engineering from Arizona State University and a BS in Industrial Engineer- ing from Virginia Tech. She also has extensive industrial experience.Dr. Patricia A Ralston, University of Louisville Dr. Patricia A. S. Ralston is Professor and Chair of the Department of Engineering Fundamentals at the University of Louisville. She received her B.S., MEng, and PhD degrees in chemical engineering from the University of Louisville. Dr. Ralston teaches
one student smaller.Next, gruepr runs its genetic optimization algorithm, displaying its progress to the instructor. Allof the instructor’s chosen teaming options are used in the algorithm’s fitness function. After theoptimization algorithm operates for some time, the set of teams with the quantitatively highestscore is shown to the instructor. The instructor can choose to keep these teams, make minortweaks by swapping one or more pairs of students between teams, or get rid of the teams andrestart the optimization scheme from the beginning. If the instructor chooses to restart theoptimization, they may also choose to adjust the teaming options and/or team size(s) at that time.Since genetic algorithms are, in general, not guaranteed to find
Paper ID #11112High School Homework Habits and Success in First year EngineeringDr. Nora Honken, University of Cincinnati Nora is an Assistant Professor in the Engineering Education Department at The University of Cincin- nati. She holds a PhD in Educational Leadership and Organizational Development for the University of Louisville, a MS in Industrial Engineering from Arizona State University and a BS in Industrial Engineer- ing from Virginia Tech. She also has extensive industrial experience.Dr. Patricia A Ralston, University of Louisville Dr. Patricia A. S. Ralston is Professor and Chair of the Department of