. 14th Annual First-Year Engineering Experience (FYEE) Conference: University of Tennessee in Knoxville, Tennessee Jul 30 Workshop: Building Bridges (but not with balsa wood) through Scalable Engineering Design Process LessonsWorkshop PurposeThe purpose of this workshop is to expose STEM and first-year engineering educators to a greater depthand breadth of understanding of the engineering design process (EDP) in order to strengthen their self-efficacy with teaching engineering and ability to motivate student interest in learning engineeringprinciples and to provide educators with lesson plans and supplies to implement these skills immediately.In this workshop, first-year
acohort for structured professional development workshops that are relevant to both early andlate-career students. Workshop topics were selected from student focus groups and representativetopics include time management, LinkedIn, resumes, negotiation, career fairs, interviewing, andalumna panels. Each mentor/mentee pair also meets one-on-one three times a semester forunstructured mentoring. LEAP hosts social events where both current and past LEAP studentsare invited to encourage networking and community building across cohorts. We believe thatmentoring is one approach to cost-effective professional development; therefore, we plan toexpand our program to all first-year students in the Honors Engineering Program.
asproductive study methods [3].Academic coaches provide individualized academic support to students in the College ofEngineering to improve student persistence and degree completion. FEP added academiccoaching to its services in 2018 to better equip engineering students for academic strugglesoutside of learning course content. The academic coaching team started as one coach andcontinually grew; currently, there are two full-time academic coaches that are supported by twopart-time academic coach graduate assistants. The coaches schedule one-on-one meetings withstudents to co-create a success plan that considers life experiences, academic goals, and long-term professional aspirations. The Academic Coaching team also offers in-class presentations,group
coursework at universities around the country, and will understand the benefits ofoffering an e4usa course at their institution. Workshop participants will have time to exploreways to bring an engineering literacy course derived from the e4usa curriculum to their homeinstitution.This workshop is designed for higher education administrators and faculty who offer or plan tobegin offering first-year engineering coursework. High school engineering educators andadministrators may also find this workshop of interest as it relates to developing a network ofinstitutions offering coursework that is closely aligned with the high school e4usa curriculum.Lastly, influencers and changemakers frustrated with the status quo and who desire more diverse,equitable
created to showcase how different engineeringdisciplines are contributing toward resilience, mitigation, and adaptation techniques. The moduleincluded a lecture on the basics of climate change—introducing the concepts of “Anthropocene”,greenhouse gases, and the Keeling curve. Students looked at the proposed plan for achieving netzero emissions described in the book, “Speed & Scale” by John Doerr (2021) and identified theengineering disciplines involved in each of the plan’s objectives [5]. A list of articles featuringnews on climate change-related work from all major disciplines was compiled for the students tohighlight recent real-world applications [6]–[19]. At the end of the module, each student createda concept map [20] to link the fields
adaptation of national models for “gold/red shirt” programsand a first-year research program for mid-tier incoming students, guided by significant featuresof our local context. Here we describe the motivation and structure for this hybrid model first-year plus support program and an informal assessment of our first year.Background and Local ContextSince first learning of Jackie Sullivan's plan to launch a program she called Goldshirt atUniversity of Colorado-Boulder, an engineering education team at OU started trying to figure outhow we could do something similar for our institution [1]. Our local context resulted in acapacity-limited, economic, and political environment that prohibited a similar launch at ourstate institution. The Goldshirt program
pilot study’s insights show where problems seem to lie in the application through theeyes of students. The corrective and prospective mindset works to provide a framework to form asolution. This combination leads to a well-informed and cohesive human factors approach.Current & Planned DesignWebTA is still in development. Both the current and planned parts of the system will beanalyzed. The current design entails a course page and assignment pages with the ability to seeprevious critiques and submit MATLAB code for critiquing. The planned design adds trainingpages to educate students on antipatterns and associated verbiage based on the antipatterns in thecode submission. Figure 1 displays a potential navigation a student may have
success, understanding andplanning for engineering careers, and building community in the incoming engineering cohort.In the activity, students are asked to respond to the prompt ‘To what extent does what you knowat the end of engineering school dictate your future career?’ Students hold up 1-10 fingers torepresent 10-100% influence over their future career and opportunities, but clickers or any otherresponse method could be used to best suit class size or other circumstances. Classes typicallyrespond with average values between 50 and 70%, saying that the majority of future careeroptions and opportunities are dictated by knowledge and skills possessed at the time ofgraduation. The students are then asked ‘What year do you plan to retire?” After
shouldbe noted that the conclusions of this paper are based solely on the researchers’ interactions withChatGPT and analysis of the transcripts generated through these interactions. The transcripts ofall relevant ChatGPT conversations are available at https://go.umd.edu/GPT_FYEE.Results and DiscussionRQ1: In what ways might ChatGPT impact the teaching and assessment of ENES100?When considering the impact of ChatGPT on the teaching and assessment of ENES100, theauthors identified multiple benefits that aid with faculty time-savings. A key benefit to usingChatGPT as an instructor is assistance in lesson-planning. For example, when prompted toidentify a possible hands-on group activity for the first day of the course, ChatGPT’srecommendation was to
together towards a common goal, educators can share ideas, resources and strategies. ○ A team structure collaboration fosters a supportive environment in which educators can learn from each other, provide feedback, and improve teaching practice together. ○ A team structure also enables the exchange of best practices and innovative approaches that lead to better research outcomes. Implementing Team Teaching Methods● Joint planning Facilitate collaborative lesson planning sessions. ○ Distribute planning work by assigning specific tasks to different team members. ○ Learn how to share assessment data, analyze results, and give feedback to students. ○ Discuss strategies for monitoring student learning
choice actions. Choice goals have been defined as “the typeof activity or career one wishes to pursue and performance goals as the level or quality ofperformance one plans to achieve within a given task or domain” [3]. Furthermore, as studentsestablish a set of beliefs about the consequences related to an engineering degree, they begin todevelop goals directed towards these outcomes and formulate a plan to achieve their goals [4].Using the SCCT model as a guiding theoretical framework, this study seeks to understand how aprofessional networking intervention in a first-year Introduction to Engineering course affects astudent’s engineering outcome expectations and their engineering choice goals.MethodologyAs part of a first-year general
. Weeklydeadlines alternate between project checkpoints and reflections to provide individuals and groupstime to understand the feedback received, connect with their team members, discuss with theirpeer mentor, and develop questions and a plan for the next checkpoint.Groups are made up of four to six students. Since MATLAB App involves various components,each group member has ownership of a specific component on the interface with the group goalof making sure they integrate. MATLAB is taught as part of this second semester, first-yearcourses, the program language, and interface are a natural extension of the knowledge they areusing regularly in class. As part of the final reflection, use the Likert scale to rate their learningin various objectives
Paper ID #40604GIFTS: Situational Learning of MATLAB Using Data Collection and Analy-sisModules Based on Upper-Level Engineering Lab ExperimentsProf. Brian Patrick O’Connell, Northeastern University Dr. O’Connell is an associate teaching professor in the First-Year Engineering program at Northeastern University. He studied at the University of Massachusetts at Amherst in 2006 then worked in industry as a Mechanical Engineer working on ruggedized submarine optronic systems. He returned to academia in 2011 at Tufts University planning to work towards more advanced R&D but fell for engineering education and educational
, and veteran barriers. We willbreak audience members up and give them 20 minutes to read, discuss and form an action plan basedon their institutional resources. They will report back an example of how a student facing these barrierswould get support at their institution, imagine if a growing population of engineering first yearsexperienced the barrier and how their institution might respond, and think through whose expertisethey could include within their school to systemically address that barrier. We will provide examples ofhow our team typically triage these case studies to demonstrate the value of our partnership and weeklymeetings.Important Logistical and Financial ConsiderationsOur model has required us to financially invest in people
least one filter that takes more than ten minutes to filter enough water to measure turbidity,which makes it challenging to determine a winner before class ends.In the most recent version of the spy gadget challenge, about 75% of the teams had a workingprototype to share with their classmates. Those who did not achieve their desired functionalitystill had made enough progress that they could convey their intentions. Most of the teamswithout a working prototype either did not arrive to class with a plan or had a plan that wasoverly complex. Students greatly enjoy the interactions in the poster format and leave positivefeedback for their classmates.Even with room for improvement (discussed below), the faculty’s informal observations indicatethat
implementation for a solution they didn’tunderstand. This unsurprisingly lead to a jumble of error-riddled code that was as difficult forgraders to decipher as it was for the authors to describe.Future WorkThe pilot and first revision of this course focused on identifying and assembling a reasonablesequence of content, activities, and assessment. In the next revision we plan to make the links tocomputational thinking more explicit and build more synergy between existing physics conceptsand data analysis through complementary lab activities. We hope this provides a balance that canhelp reduce the tension between need for abstraction and motivation that comes more naturallyfrom concrete application. To assess these changes we plan to administer a survey
Paper ID #40594Sustainability and Life Cycle Assessment in Engineering CurriculumMs. Madeline Fisher, Ohio Northern UniversityMr. Evan Budnik, Ohio Northern University Evan Budnik is a Civil engineering student planning on studying enviromental engineering. He is focous- ing on water recources and water management engineering.Mr. Brady HarmonDr. Lauren H. Logan, Ohio Northern University Lauren H. Logan is an assistant professor of civil and environmental engineering at Ohio Northern Uni- versity. Her research focuses on the interconnection of water and energy, as well as life cycle assessment within engineering education
other students they can work with. One of the authors has experimented withmorning office hours in the library in the past, but they were not significantly better attendedthan normal office hours. One to two students a week visit normal office hours compared to fiveto twenty each session in public office hours. Several students used these times as a study hall,and we were able to help them form study groups. This year, we expanded public office hours totwo afternoons and one evening a week. We spent six hours per week in the library, helpingstudents most of that time. Office hours were well received and helpful; however, it led to somefaculty burnout late in the semester. In the future, we plan to spend less time in public officehours (probably
to the firstphases of entrepreneurship using an elevator pitch competition. Entrepreneurship is the processof finding a need in the market, developing a creative solution or product to fill that need, andmarketing it with the goal of developing a successful business. The entrepreneurship process isdivided into five phases: idea generation, opportunity evaluation, planning, company formationand growth. Entrepreneurship is about recognizing opportunities in the market and acting onthem. It requires to think creatively, to innovate, and to move from an idea into a prototype.The elevator pitch competition was developed within the context of a first-year engineeringseminar. Students were divided into small groups and were tasked at identifying a
redesigned spaces encourage students toengage in hands-on projects and experiential learning. These transformed learning environmentsaim to cultivate a sense of belonging, creativity, and innovation among students, promoting theiroverall engagement and success [1], [2], [4], [5], [13].To ensure the effectiveness of these new initiatives, the College has implemented acomprehensive assessment plan. The National Survey for Student Engagement (NSSE) [9]isadministered each year for engineering students following the launch of the new programs. Thisassessment provides valuable insights into student experiences, perceptions, and outcomes,allowing the College to make data-informed decisions and continuously improve the support andlearning environment
approach in class sessions in differentcourses, including: • Quick Review • Addressing muddiest point(s) • In Class Activities o TPS/conceptual MC o Problem solving o Mini-labs • Leading to the full assignmentWe will finish this section with working time and discussion on the development of a learningactivity for attendees.Part 5: Expectations and Lessons Learned (10 Minutes)In the final part of our workshop, our team will discuss expectations instructors should havewhen starting this process as well as lessons we have learned over several years of transition andsteady implementation of flipped classrooms. These discussions will include: • Time to implement/long term planning for flipped classroom
. Marcia Pool is a Teaching Associate Professor and Director of Undergraduate Programs in the Depart- ment of Bioengineering at the University of Illinois at Urbana-Champaign (UIUC). She has been active in improving undergraduate education including developing laboratories to enhance experimental design skills and mentoring and guiding student teams through the capstone design and a translational course following capstone design. In her Director role, she works closely with the departmental leadership to manage the undergraduate program including: developing course offering plan, chairing the undergrad- uate curriculum committee, reviewing and approving course articulations for study abroad, serving as Chief Advisor
is attributed to the factthat machine learning requires in-depth knowledge of numerous math, statistics, andprogramming concepts [1]. Also, the existing requirements and packed schedules for first yearengineering students leave little room for additional topics [1]. As such, there have been veryfew attempts to introduce first-year engineering students across all majors to ML to date.The University of Maryland’s engineering school started planning a Machine Learning for Allinitiative in 2022, which aims to give every engineering student skills in ML. Theimplementation of ML in Introduction to Engineering Design (ENES100) has been deemed apossible foundation for this initiative. ENES100 is a required course for all first-year
was used or will be used. We then compare counts of each usefulresponse across levels in the hierarchy.Preliminary Results and DiscussionWe coded the exit survey questions according to various aspects of reflection, such asprompts for self-monitoring and self-assessment of learning, along with assessment of coursetopics, identification of future plans for the design project, and occasional questions that wereintended to entertain and engage students.Recent examples of feedback about class activities that enhanced student learning involvedtechnical instruction, design showcases, interactive in-class activities, and time for projectteams to work together during class. Suggestions for improving the course includedadditional background
enjoyed theresearch project, which allows them to explore subjects they were interested in and exposed themto real-world problems, research methodologies, and the latest advancement of the professionalfield. They also experienced the application of the tools learned in class. As a future step, it isessential to develop an assessment plan to evaluate the effectiveness of the research project. Toaddress the challenge that first-year students face in reading technical papers, providingadditional guidance and support is crucial. Here are some suggestions to enhance the guidancefor students: i) Research Questions: Provide students with a set of research questions that helpguide their reading and comprehension of the technical papers, as described in
. Tweeter Circuit #1 Circuit #2 Mono Circuit #4Audio Circuit #3 L+R Mixing Highpass Amplifier CrossoverSource Equaliser Stereo -> Mono Filter Module Unit Mid (3D)Figure 2: Block diagram of the speaker project.Assessment was 22% individual (online prep activities 4%, overall project quiz 6%, and peerassessment 2%) and 78% group (18% = 9 x 2% workshops, 10% project plan, 5% project videopresentation, 35% project final report, and 10
related to student success. There is some evidence to suggest thatthe integration of these skills mutually motivate and support one another while on the other handbringing computational skills into the same course as pre-requisite physics concepts may addmore stress to an already “at-risk” population. We plan to analyze the effects of this conceptualcoupling with student well-being and self-efficacy in a later phase of this study.References[1] J. Butler and M. L. Kern, “The PERMA-Profiler: A brief multidimensional measure of flourishing,”Int. J. Wellbeing, vol. 6, no. 3, pp. 1–48, 2016, doi: 10.5502/ijw.v6i3.526.[2] A. N. Kirn, “The influences of engineering student motivation on short-term tasks and long-termgoals,” 2014.
attend events that have no direct impact on their grade whether they attend or not. We hopethis novel social focus brings additional gain to our students and program, beyond a purelyacademic focus. Figure 1. Mentor Evaluation Graph: Likelihood of mentees to continue with the peer mentor program vs. Anumerical Score (average attendance * number of events planned.) Figure 2. Event Analysis: Average attendance for each event type for all groups and high ranked groups (those with more events and higher attendance than average)References[1] American Society for Engineering Education. (2016). Engineering by the Numbers: ASEERetention and Time-to-Graduation Benchmarks for Undergraduate Engineering Schools,Departments and Programs. Washington, DC
is ongoing. The results will inform future implementationand program communication and seek to understand if the student experience is consistent withthe literature previously mentioned. Additionally, this will serve as the beginning of alongitudinal study to understand student career development over their entire college career. It iscritical to understand the longevity of this structure on a student’s pathway into an engineeringcareer and inform continue intervention of these skills at the first-year level.[1] B. D. Jones, M. C. Paretti, S. F. Hein, and T. W. Knott, “An Analysis of Motivation Constructs with First-Year Engineering Students: Relationships Among Expectancies, Values, Achievement, and Career Plans,” Journal of
inclusive environment, establish goals, plan tasks, and meetobjectives” as a required student outcome supporting the program educational objectives [5].Engineering educators who endeavor to teach inclusive teamwork skills to enable their studentsto work productively and inclusively, however, often discover what organizational theorists havepreviously observed and documented: that teaching people to work productively in diverse teamenvironments is a challenge [1].Historically, many diversity-related educational interventions in Science, Technology,Engineering, and Mathematics (STEM) environments attempt to prepare the marginalized personto cope with the unwelcoming cultures in which they are situated [2]. With NSF support, aresearch team used a