Paper ID #37212Integration of VHDL Simulations and Written Reflections to ImproveStudent Understanding of Sequential Logic CircuitsBen Arie Tanay, Purdue Engineering EducationDr. Renee M. Clark, University of Pittsburgh Renee Clark serves as the Director of Assessment for the Swanson School of Engineering at the University of Pittsburgh. She received her PhD from the Department of Industrial Engineering, where she also completed her post-doctoral studies. Her research has primarily focused on the application of data analysis techniques to engineering education research studies as well as industrial accidents. She has over 20
Paper ID #38062Changes to a Circuits Lab Sequence to Encourage Reflection andIntegration of Experiences Across Related Courses to Explore NewSolution Spaces to an Engineering ProblemDr. Chandrasekhar Radhakrishnan, University of Illinois, Urbana-ChampaignDr. Christopher D. Schmitz, University of Illinois at Urbana - Champaign Christopher D. Schmitz received his Ph.D. in Electrical and Computer Engineering from the University of Illinois in 2002.Dr. Rebecca Marie Reck, University of Illinois Urbana-Champaign Rebecca M. Reck is a Teaching Associate Professor of Bioengineering at the University of Illinois Urbana- Champaign. Her
Paper ID #43465Board #440: Effect of Reflection Exercises on Preparation for Exams: A CaseStudy in an ECE Machine Learning ClassDr. Ahmed Dallal, University of Pittsburgh Dr. Dallal is an associate professor at the department of electrical and computer engineering, Unversity of Pittsburgh. Dr. Dallal’s primary focus is on education development and innovation. His research interests include biomedical signal processing, biomedical image analysis, and computer vision, as well as machine learning, networked control systems, and human-machine learning. ©American Society for Engineering Education, 2024
undergraduate students over the years. Next, we will introduce and discuss the twoclasses (Freshman Engineering and Electromagnetism) where we deployed the method. We willalso highlight the students’ work and introduce their journeys by sharing their reflections andsome examples of their activities and challenges. The main question that we are trying to ask andfind evidence for is, "Can we re-engineer mistakes and use them as an important part of thelearning, changing, and adapting to the process, examinations, and growth of the students?” Wefound that providing low-stakes learning opportunities is impactful in encouraging collaborationsamong the students and allowing them to openly engage in their own identity, discuss, examinetheir knowledge and not
response to these trends, more engineering courses are being designed to incorporate moreinnovative, creative problem-solving skills2,3,4,5. Some examples include field trips or minicompetitions as a creative model to encourage creativity6. In addition, problem-based learningand critical thinking skills in the context of real-world problems have been integrated intoengineering education to facilitate students’ divergent thinking during the idea generation phase7.Among them, the most common instructional approach in engineering education is open-endeddesign projects, where the target product is not defined in order to allow creative opportunities3,5.One argument in favor of open-ended design projects is that students reflect on their owncreative
for teaching highly technical concepts. ©American Society for Engineering Education, 2023 Considerations for Software-defined Radio Use within a Project-based Learning SubjectAbstractIn this paper we reflect on the use of software-defined radio (SDR) within a project-basedlearning (PBL) subject at the master’s level that incorporates a semester-long wirelesscommunication design project. PBL as a pedagogy is an important tool for addressing disparitiesexisting between the capabilities with which engineering students graduate and those demandedby employers. Ideally, it enables ‘dual impact’ activities in which both technical and professionalskills can be developed concurrently
facets of knowledge inlearning activities. Additionally, Krathwohl's revision of Bloom's Taxonomy [14] emphasizes theevolution of the framework, underlining the significance of metacognitive knowledge. This newlyintroduced category reflects advancements in cognitive psychology, stressing the importance ofstudents' awareness of their own cognitive processes—an aspect crucial for effective learning.Building on Bloom's Taxonomy, which originated in 1956 [16], the end goal has always been tocontribute to the development of students’ learning facilitated through a taxonomy of educationalobjectives and in this case, specific to engineering education. The taxonomy not only classifieseducational goals but also provides precision in discussing curricular
, we developed the Plug -n- Play approach, a flexiblepedagogical approach which ensures instructors have a fixed core structure, flexibility inleveraging their own teaching style, and a mechanism for constant reflection which allows foradaptations to the course structure over time. The PNP approach focuses course design around thestudent experience, while acknowledging and supporting individual teaching styles and teachingmethods.To assess PNP, a classroom observation protocol was developed to evaluate student engagement,as well as examination of sixteen sections worth of grades and student evaluations. The resultsshow that students are highly engaged with the course material, peers in the class, and theinstructors. Finally, the PNP approach
Intrinsic Motivation items of the questionnaire were codedon a Likert-scale from “Strongly agree” to “Strongly disagree”. The Learning Styles Inven-tory questionnaire included 44 items that were binary in nature, students picked the bestfit from two presented options, e.g. “I understand something better after I a) try it out orb) think it through”. Each of these 44 items belonged to one of 4 learning styles categories:Activist/Reflective, Sensing/Intuitive, Visual/Verbal, or Sequential/Global. Students wouldthus get a score between 0 and 11 for each category - for example, the 11 items that cor-responded to the Activist/Reflective spectrum were added with a score of 1 if the responsecorresponded to Activist and a score of 0 if the response
much betterDoes your system display a low pass response or a high pass response? How do you know?Students displayed errors in identification and terminology that are anticipated for any laboratoryexperiment on frequency response. In their written reflections, some students correctlyqualitatively described a highpass response, but incorrectly classified it as a lowpass response.Students in both the speaker completed first and resistor completed first groups bothemphasized the behavior of the speaker when justifying whether their circuit was high or lowpass. One student in the resistor completed first group reversed their judgment of the filternature after doing the speaker version of the experiment. After completing the resistor-onlyportion of
analysisof the autoethnographic account of the first blind student to complete the introductory ECEcourse at our institution, Stanford University. This work also expands the role of the blindstudent to become a co-researcher, actively guiding the direction of this work while receivingmentorship from research team members on qualitative research methods.In this work, we begin with the analysis of seven reflection journal entries written by the blindstudent and relevant discussion session notes recorded by the lead researcher. These data weregenerated and collected via the autoethnography method and analyzed by applying the CAREmethodology, using a grounded theory approach, during which we completed open and focusedcoding. We then identify
1. Alsodiscussed is the pedagogical background required for designing realistic engineering problems.Finally, an example project for sophomore-level electrical and computer engineers is explained indetail, with the author’s own experiences in assigning this project explored. The project is anopen-ended problem with multiple solution options. Students have scaffold-ed experiences withinthe course to guide them towards several possible techniques. Students follow a fullproblem-solving structure through defining their problem, exploring options, planning a method,implementing said method, and then reflecting upon the success of their design.IntroductionThe first of the seven ABET outcomes is stated as “an ability to identify, formulate, and
you understand those concepts very well you won’t have to waste more time relearning it.” “Review your Physics II before you start the class.” “Do well in University Physics 2” Needs for Visualization “Bringing more visualization would be helpful.” “I would have preferred more visual aids, specifically animations of the fields.”Conditions and Constraints in Class EnvironmentThe class environment plays a pivotal role in fostering effective learning and holds significantimportance in shaping the educational experience for students. It is useful to clarify the classenvironment for both universities along with the constraints so that it reflects better howvisualization tools and trials work. Both institutions adopt typical university classes and
necessitate covering aspects from adiverse range of topics, including fundamentals of digital design, computer architecture, parallelprogramming, and systems thinking. Although such concepts naturally intersect within thediscipline of computer engineering, structural considerations within our master’s programs anddisparate prior knowledge within our cohort entail students inherently experience the subject asinterdisciplinary in nature. This presents numerous challenges in subject design but offers anopportunity for developing interdisciplinary competencies and an appreciation for otherdisciplinary ways of thinking. Based on instructor observations while teaching, we reflect on thesuccesses and shortcomings in the subject’s design that impact
different passives, sensors, andperipherals to the MKR Motor Carrier, including resistors, potentiometers, FSRs, motors, servos,encoders, accelerometers, Hall-effect sensors, ultrasonic sensors, infrared reflectance sensors,and photoresistors.Software DesignThe Arduino MKR was programmed to establish a wireless access point and await commandsover UDP from an external device (e.g., a student running MATLAB on a laptop or classroomdesktop). The MKR remains waiting, responding to commands as they are received.When a command is received to read from a peripheral device or a GPIO pin, for example, theArduino responds with the value. Several data streams have been established to facilitate datatransfer when several different data values are needed, which
provide leadership, create a collaborative and inclusive environment,establish goals, plan tasks, and meet objectives." Therefore, engineering schools must preparestudents with teamwork skills and incorporate teamwork as a significant part of their engineeringcurricula (ABET, 2021).Team participation is typically evaluated through peer evaluations or through instructorobservation of individual team members. Several tools have been developed to assess individualperformance, such as the Team Effectiveness Questionnaire (TEQ) or the ComprehensiveAssessment of Team Member Effectiveness (CATME). These assessment tools are based onself-reflections or peer evaluations. However, the efficacy of these tools has been questioned.At the University of
interviewed. The feedback from the students and reflections from the faculty wouldprovide guidance about the integration of the undergraduate research experiences into the coursesto broaden the impacts of undergraduate research on learning and teaching. In the future, at leastanother two cohorts of students. especially from underrepresented groups, will be recruited. Wewill have a longitudinal study to explore the impacts of undergraduate research experiences onlearning and teaching using a mixed qualitative and quantitative method.KeywordsResearch Experience for Undergraduate, Drone Swarms, Artificial Intelligence. 1. Introduction Studies showed that interdisciplinary undergraduate research activity efficiently improvesstudents’ learning and
-resources for Fall2021 and in-person classes with e-resources for Winter 2022, in Figure 7, indicates a slightdifference in performance in the midgrade. The weighted average scores for Fall 2021 andWinter 2022 are 3.03 and 2.93. Up to Winter 2022, the in-person class with hybrid resources had, to some extent, normaldistribution whereas the class fully online had non-normal distribution; but the mean value didnot deviate significantly. The learning outcomes for both in person and online does not havesignificant difference as reported in [6-8]. The weighted average scores reflect the reportedresults. The difference in the trend in the figures can, therefore, be attributed to the backgroundof the students.Assessment 1 and Final grades for Winter 2022
. According to the NationalResearch Council [3] and Savey [4], inquiry-based learning (IBL) is a pedagogical approach inwhich students begin with a question followed by investigating the solutions, reflecting, andcommunicating findings, and creating new knowledge based on the collected evidence. IBL hasbeen widely adopted in science education because of its great potential to facilitate more positivestudent attitudes and a deeper understanding of scientific concepts [5], [6]. Additionally, accordingto Specht et al [7], inquiry-based learning has been increasingly suggested as an efficient approachfor fostering students’ curiosity and motivation by linking science teaching in schools withinformal learning and phenomena in everyday life. To ensure the
university setting. The success of an advanced digital design course deliveredusing a remote Field Programmable Gate Arrays (FPGA) lab inspired the creation of anintroductory digital logic curriculum for 2-year community college and high school students. TheBEADLE curriculum is designed to prepare students for a junior-level course in computerengineering at a 4-year university, where digital logic is typically taken during the first twoyears. To evaluate the curriculum, we offered it to a sophomore class on digital logic design at a4-year public university and collected pre- and post-assignment surveys to gauge understandingof the material. Reflection pieces were also used to evaluate the students' approach and level ofcomprehension. In this paper
thecourse. The survey also allowed students to expand on any challenges they were still facing atthe end of the course. This final survey allowed us to explore in depth the students’ interests,prior exposure to ECE, course expectations, learning experiences, and takeaways, in addition toany remaining challenges and final reflections. We provide a brief class profile in Table 2,generated from the final survey data. It is important to highlight the different making andelectronics experiences that students had been exposed to prior to taking E40M, in addition to thedifferent academic major interests of the enrolled students. This diversity helped us collect amore representative body of data pertaining to the overall student population’s
further evaluate the impact of quizzes on grades, we compare grades based on solelyindividual efforts such as exams and quizzes, while excluding homework and laboratoryassignments from the calculations. By the authors’ observations, homework assignments may notalways provide an accurate reflection of a student’s knowledge or performance, as students oftenseek assistance from others or even may copy answers from peers or online sources. Althoughlabs are relatively more representative of a student’s individual effort, students still receivesignificant help with them.For this comparison, we calculate the grade with quizzes by re-scaling both quizzes and exams, sothat the total adds up to 100%. We consider eleven quizzes contributing 20%, three
designed toencourage students to consolidate their knowledge and foster a deeper understanding of thecourse material by visualizing and summarizing the relationships between key topics. This typeof active learning also empowers students to take ownership of their learning by creating andrevising their concept maps.A fundamental aspect of our course improvement work involved gathering feedback fromstudents regarding their perceptions of the effectiveness of concept mapping in these courses. Ineach course, a survey was administered at the end of the semester to gauge students’ experiences,opinions, and reflections. Our findings from the surveys indicate that concept mapping isperceived positively by a significant proportion of the students
therepresentation of female students (28.3%) when compared to Electrical Engineering(14.4%) [14]. Further, in our experience, extra-curricular opportunities to engage with HEprojects, for example through student clubs, are often rooted in the civil and mechanicalengineering disciplines. For example, many Engineers without Borders student chapter projectsfocus on water access and building construction. While electrical engineering students mayparticipate in these experiences, not seeing their discipline reflected in the projects may limit theappeal. In short, there is at least the perception that electrical engineering students do not engagewith HE themes as often in their coursework or in extra-curricular ways as their peers in otherengineering disciplines
. By analyzingqualitative data from weekly blog post reflections and student interviews, this work aims to unpackthe complex ways global competencies are cultivated among undergraduate and graduateengineering students with varying degrees of prior research experience. The findings of thisresearch are expected to inform future engineering education practices, providing valuable insightsfor educators, policymakers, and institutions aiming to enhance the global competencies of theirstudents through international research collaborations.IntroductionGlobal competence has increasingly become a key differentiator in engineering, significantlyinfluencing an engineer’s employability and career progression [1], [2], [3], [4]. However, workingwith
, examinations, and attendance (for asynchronous/flippedmodalities only) are also given in Table 1 for each iteration. Average final grades range from79.33% to 86.47% which reflects that overall the groups are demonstrating good to very goodmastery of the course material. The average final examination grade, which is the finalindividual assessment of course material, ranges from 67.63% to 79.91% over this same perioddemonstrating satisfactory (with some weaknesses) to satisfactory performance.To determine if there were differences in student course performance between iterations from2018 to 2023 a one-way ANOVA was conducted using the average course grades in Table 1.This analysis reported that the final course grade between semesters was not
on their form as there is a large pool of random examquestions for each topic (around 30 versions of each question). Exam Reflection Form Topic: What steps I took to solve the problem: What I misunderstood and what I should have done: Notes: Figure 5: Exam reflection tool used by students when going over incorrect exam questions.As an example, Figure 6 shows a fill-in-the-blank question on non-strict parameter passing; passby need.In order to prevent unnecessary re-attempts to achieve a perfect score on questions where thestudent has already achieved a score of 90% or higher, all such scores are converted to 100%credit. The difference between a 90% score and 100% typically comes down to typos rather thana lack of understanding. This
emphasis on the electrical aspectsand the power electronics associated with such technologies. This course does not addresspower system-level topics such as grid integration and economics of renewable energy sources.The course instruction is enhanced by Simulink model simulations to provide students with agraphical environment for simulating and analyzing renewable energy systems. This course canserve as guide to other instructors interested in initiating a course in renewable energy.In this paper the contents and teaching methods of a course in renewable energy technologies arepresented. Example Simulink assignments are described. Reflections on the student experienceare presented and lessons learned are highlighted.Course ContentTable 1 outlines
regulators, and data conversion circuits.Students obtained more accurate results, matching calculations, and simulations compared tousing breadboards. In addition, students gained time spent on additional testing and analysis.Students completed assignments using both the customized PCBAs and conventionalbreadboards. Quantitative and qualitative surveys have been conducted to assess the impact ofPCBAs on students' learning experience, technical effectiveness, and educational impact. Studentfeedback on using PCBAs compared to traditional breadboarding has been analyzed and sharedin this paper. The use of custom PCBAs addresses known breadboarding impediments, includingloose connections, noise, probing challenges, and cluttered layouts. They reflect
and reflectively. In essence, formative assessment is fundamentally concerned withnurturing students' learning and development [9], rendering it a vital component in the fusion ofassessment and teaching [3], [10].Brown [11] describes the formative assessment as the evaluation of learners in the process of"forming" their skills and competencies, facilitating their continuous growth. It encompasses allactivities conducted by instructors and learners alike, supplying information that can beharnessed as feedback to refine ongoing learning and teaching practices [12]. Importantly, thisdefinition underscores the active involvement of both students and teachers, making formativeassessment an integral component for enhancing students