hands-onsemester-long project. The second course takes places in a 15,000 square foot makerspace withroom for students to work in teams of 3-4 on a project that incorporates many engineering skills,one of which is a basic introduction to circuitry.While engineering students are first taught programming in ENGR 110, their first exposure tocircuitry occurs in the second course in the sequence. In ENGR 111, students first learn aboutcircuitry components before constructing very basic circuits with an Arduino. Then, studentslearn about circuitry principles such as Ohm’s Law and build more basic circuits with anemphasis on state measurements.This first exposure to circuitry concepts takes place in the middle of a semester-long project thatstudent
Paper ID #44328Assessing the Effectiveness of Open-ended Engineering Design Projects in aFirst-Year Engineering Programming Course for Improving Students’ Problem-SolvingStylesDr. John Alexander Mendoza-Garcia, University of Florida John Mendoza Garcia serves as an Instructional Associate Professor at the Department of Engineering Education within the Herbert Wertheim College of Engineering at the University of Florida. He received his Ph.D. in Engineering Education at Purdue University, and his Master’s and a Bachelor’s in Systems and Computing Engineering from Universidad de Los Andes, in Colombia, and Universidad Nacional
Paper ID #41541A Custom Generative AI Chatbot as a Course ResourceYutong Ai, University of MichiganMaya Baveja, University of MichiganAkanksha Girdhar, University of MichiganMelina O’Dell, University of MichiganDr. Andrew Deorio, University of Michigan Andrew DeOrio is a teaching faculty and Associate Chair for Undergraduate Affairs at the University of Michigan and a consultant for web projects. His research interests are in engineering education and interdisciplinary computing. His teaching has been recognized with the Provost’s Teaching Innovation Prize, and he has three times been named Professor of the Year by the students
. The mainlearning categories include Think (reading, discussing, listening), Practice (algorithmdevelopment, algorithmic puzzles), Interpret (case studies, analyzing algorithms), Apply (open-ended problems, project-based learning), Evaluate (solution testing, peer evaluation), and Create(presentation, documenting, product development) [2]. For example, well-timed support could beincorporated in a “practice” activity such as algorithm development. Additionally, feedbackcould be applied to an “evaluate” activity such as solution testing. The researchers in [2] suggestmultiple technology-integrated learning activities that could include a number of differentscaffolding techniques within them. Although it is not necessary to apply activities in
Python in the introductory computing course. The course topics and learning goalsfor the course were not changed, and course lectures were only changed to reflect the change inprogramming language.This paper compares student achievement between classes that took the MATLAB-based versionof the course and those who took the Python-based version. Students in the two versions weregiven very similar exams and final project problems so that their achievement of course goalscould be compared.This work is the first phase of a longer-term project intended to assess the digital literacy ofWestern Carolina Engineering graduates. Students’ programming skills will be assessed as theyprogress through the four-year engineering curricula. A particular focus of
multidisciplinary graduate engineering course that bridges the domains of educationand computer science. Leveraging the Communities of Practice framework, we examine how computerscience students integrate new knowledge from education and computer science to engage in aneducational data mining project. In the first course iteration, we investigated the creation of amultidisciplinary community by connecting students from both disciplines through a blend of problem-based learning instruction and traditional lectures. In the second version of the course, we established amultidisciplinary environment by bringing two instructors, one with computer science expertise and theother from education. To investigate the effectiveness of these approaches, we conducted
systems as well as WebAssembly, withsmooth operation even on low-power devices such as single-board computers. Additionally, thetool is designed to continue to grow via community-driven support – the project is open-sourceand hosted on GitHub, open to public contributions, and will grow as community members addsupport for additional hardware platforms. Features and documentation that will allow for furthercommunity engagement are underway, and the long-term goal of the project is to become apopular and useful tool among open-source development environments, especially in aneducational setting.IntroductionModern open-source hardware ecosystems such as Adafruit’s Feather boards [1], Sparkfun’sMicroMod boards [2], and Raspberry Pi’s single-board
indicating an improved learning experience. According to verbal reports,students often struggle with retaining and comprehending lecture content, especially whenreference materials are limited to lecture notes and slides. College students collectively undertook this project to investigate the use of conceptualvideos as supplementary pedagogical tools. They sought to develop materials enhancing coursecomprehension, covering fundamental topics from variable declaration to arrays and functionsthrough a quick topic rundown and detailed programming examples starting from the project'screations. The team embarked on the production of a series of educational videos. Thesedynamic tutorial videos deliver an immersive learning experience that is often
design project. TheInstructional Processor provides the base design, which can be modified to adapt to a new set ofspecifications. Students must modify the appropriate processor components and integrate theminto the data path. The control unit must also be redesigned to accommodate the newinstructions. A sample program is then tested via simulation of the updated VHDL model.The base processor is expanded by adding a serial communication interface, designed using aUART (universal asynchronous receiver transmitter). Next, a programmable timer and interruptsystem are added to the processor architecture. The enhanced FPGA microcontroller is testedusing a design example which gives students an in-depth look at both the internal details andexternal
ensure that students learning can perform effectively in a professionalsetting [5, 6]. Due to this factor, there have been several methods designed to aid in studentlearning especially in engineering education, such as active learning [7–11], project-basedlearning [12, 12–16], inquiry-based learning [17].Active learning has been aware of improvement of students’ affect toward engineering educationin support of meaningful engagement with computer engineering concepts and practices [7].Compeau et al. [8] developed an active learning pedagogy in engineering electromagneticscourse, in which engineering students are actively engaged in learning through specially designedactivities, followed by reflection upon. A teaching plan is elaborated in [9
each lab o Design of lab by instructor/graduate students. ▪ Delivery of lab by graduate students. ▪ Feedback mechanism.• Mechanisms for enforcing cloud computing concepts and services: o Through projects and assignments. o Through targeted upper-level courses. o Through individualized capstone projects.• Resources made available to students: o Internal and external. o Free and for pay.• Cloud+ Certification: o Institutional resources. o Externally funded resources.By presenting our efforts, we hope that other institutions considering expanding their programsof study to include Cloud Computing, Cyber Security, and Cloud+ Certification can benefit fromour experience by
for many platforms [8]. The other compiler is clang,from the LLVM project [9]. Although the clang compiler has a shorter history than GCC, it has areputation for providing compiler output and better diagnostics[10], [11]. In addition, as an entirecompiler infrastructure, there are many tools built with clang as a basis, as we’ll see in section .However, recent versions of both compilers have mostly caught up with each other, either optionworks well.To install these compilers, MacOS and Linux users can use a package manager (such as Homebrewor apt/dnf) to easily install either of the two compilers.Under Windows, which is used by the many students as their personal computer, this picture is morecomplicated. One path students can use is to use
that is engaging, interactive, and fun. This approachwas also compared with a research-centric group project that delved into establishing secure meth-ods for cyber-physical systems. The study indicates that a majority of students (77.4%) viewed theCapture the Flag Scavenger Hunt as a highly valuable learning experience.1 IntroductionStudying computer security is crucial in today’s interconnected digital landscape to safeguard sen-sitive information, preserve privacy, and ensure the reliable functioning of computer systems 1 . Anundergraduate (UG) course in computer security typically includes topics such as network security,operating system security, cryptography, software security 2 . Cryptography, a fundamental pillar
transfer in a range of learning environments. ©American Society for Engineering Education, 2024 WIP: Exploring How an Unofficial Discord Server Supports Undergraduate Learning in Computer ScienceAbstract WIP: Discord, a social platform originally targeted for the videogame community, isbecoming more and more popular as a tool for group projects, class discussions, and communityfor computer science (CS) students. At our university, a group of undergraduate CS studentsstarted a public, unofficial CS departmental server in 2017 where students can join and talk toothers in their classes under a thin veil of anonymity. Through the years, this Discord server hasgrown, it now houses 2,353
) tools come online, technical writing instruction is poised tocreate new applied projects, teaching students to use ML constructively, objectively evaluate MLoutput, and refine final products faster. STEM researchers are already publishing their use ofChat GPT-adjacent language tools in high impact scientific outlets like Nature. Engineeringstudents need exposure and to develop competency in using these tools. ML can supporttechnical writing by proofreading content; suggesting novel syntactic structures; producingusable content faster; and upskilling writers in the process. This paper presents the use of fourML tools, applied in service to a series of technical writing and communication projectsappropriate for sophomore-junior level students
development expert, along withinstructions about what makes LOs well-constructed in terms of three main parts: Behaviour (theobservable action of the student), Conditions (in what context the student will perform theaction), and Degree (how well the behavior must be performed). Moreover, the prompt containsexamples of what conceptual LOs (which they define as Remembering and Understanding inBloom's Taxonomy) and project LOs (based on the remaining levels of Bloom's taxonomy) are togive the model a basis for what output to produce. The authors include the criteria that need to besatisfied for LOs to be effective; readers are strongly encouraged to borrow the checklist fromKennedy [37] to expand on their list. Lastly, they list what the user input
conciseinterface; 3) extensive functionalities, including code compilation, project organization, andsupport for multiple languages; 4) mainstream adoption among professional software engineers,bridging the gap between classes and future careers.We have identified Microsoft Visual Studio Code (VS Code) as the preferred option. Byintegrating VS Code with a selection of extensions, it becomes an IDE that incorporates all fouraforementioned features. Additionally, VS Code has been widely adopted in many advancedcourses in our department, including operating systems, compiler constructions, computernetworks, and others. However, it has not received significant attention to CS1 courses.Furthermore, based on our study of 20 computer science departments, none of
Paper ID #41661Board 43: AP-CS, ChatGPT and Me: a High School Student PerspectiveDr. Zoe Wood, California Polytechnic State University, San Luis Obispo Whether it is creating computer graphics models of underwater shipwrecks or using art and creativity to help students learn computational thinking, Professor Zoe Wood’s projects unite visual arts, mathematics and computer science.Miguel Manoah Refugio Greenberg ©American Society for Engineering Education, 2024 AP-CS, ChatGPT and Me: a high school student perspectiveAbstractWith the creation of openAI’s ChatGPT system, a problem has arisen in
Paper ID #42183WIP: AI-based Sentiment Analysis and Grader EnhancementsMr. Bobby F Hodgkinson, University of Colorado Boulder Bobby Hodgkinson is an Associate Teaching Professor in the Smead Aerospace Engineering Sciences Department (AES) and co-manages the educational electronics and instrumentation shop. He assists students and researchers in the department for sensor and data acquisition needs as well as manages several lab courses and experiments. He is a member of the Professional Advisory Board for the senior capstone projects course. Prior to joining Smead Aerospace department in 2012, he was the lab manager at
engineering education was handed out to a sample of civil engineering and technology students from various classes. The survey included questions about their knowledge, frequency, benefits, challenges, and suggestions for future use of AI tools in engineering education. The questionnaires were distributed to 107 junior and senior students in seven civil engineering courses during the fall semester of 2023. Half of the courses took the survey online, via Canvas Course, and the other half as a handout. The questionnaire was anonymous and was distributed to various civil engineering courses, such as Construction Management Materials, Transportation Operations, Planning and Scheduling, and Project Information Modeling. In addition, the students who took
Computer Science from University of Maryland, College Park in 1986. He is currently Professor of Computer Science at Virginia Tech, where he has been since 1987. He directs the AlgoViz and OpenDSA projects, whose goals resp ©American Society for Engineering Education, 2024 WIP: Exploring Office Hour Interactions in a Data Structures and Algorithms CourseAbstractLarge universities often have introductory computing courses with hundreds of students, dozensof TAs, and multiple TAs on duty at the same time. We investigate what occurs during office hourinteractions between students and TAs, focusing on a large intermediate data structures coursewith major programming assignments
JavaScript.Dr. Hamid S Timorabadi P.Eng., University of Toronto Hamid Timorabadi received his B.Sc, M.A.Sc, and Ph.D. degrees in Electrical Engineering from the University of Toronto. He has worked as a project, design, and test engineer as well as a consultant to industry. His research interests include the applicati ©American Society for Engineering Education, 2024 WIP: Immersive Learning: Maximizing Computer Networks Education Based on 3D Interactive AnimationsAbstractThe potential of 3D animation models can enhance the learning process, making it morevivid and clear by capturing students' attentions. As concepts related to computer networksare often abstract and intricate, educators commonly
Paper ID #43103 Arthur Hoskey is a Professor of Computer Systems at Farmingdale State College in New York. He received his Ph.D. in Computer Science from the City University of New York Graduate Center and received his B.A. in Psychology from the State University of New York at Purchase. Dr. Hoskey worked as a software engineer prior to starting his academic career. Dr. Hoskey’s primary line of research has been around innovative pedagogical methods. One line of research was a collaboration with faculty from multiple State University of New York colleges on a project to explore and develop a semi-standardized and accessible introduction to computer science course (SUNY IITG funded research), focused on teaching
simulation, such as the representation ofcontinuous signals and discrete (digital) signals using the sampling theorem. This project makesuse of the state-of-the-art design principles and techniques to create a user interface and virtualenvironment that are user friendly, efficient, and effective for learning. Integration of existingthird-party software libraries is another crucial component in the rapid development of virtuallabs. This project successfully integrated SPICE, a popular circuit simulator, as the backend ofthe virtual lab, greatly expediting the overall development. This paper will discuss the techniquesfor integration of third-party software to achieve interoperability between different software.While our current development focuses on
Consortium. He is a Senior Member of the IEEE.Dr. Bruce R Maxim, University of Michigan, Dearborn Bruce R. Maxim has worked as a software engineer, project manager, professor, author, and consultant for more than forty years. His research interests include software engineering, human computer interaction, game design, virtual reality, AIXiaohong Yuan, North Carolina A&T State University Dr. Yuan is a professor in the Department of Computer Science at NCA&T. Her research interests include AI and machine learning, anomaly detection, software security, cyber identity, and cyber security education. Her research has been funded by the National Security Agency, the National Centers of Academic Excellence in
professions. Estell is Professor of Computer Engineering and Computer Science at Ohio Northern University, where he currently teaches first-year programming and user interface design courses, and serves on the college’s Capstone Design Committee. Much of his research involves design education pedagogy, including formative assessment of client-student interactions, modeling sources of engineering design constraints, and applying the entrepreneurial mindset to first-year programming projects through student engagement in educational software development. Estell earned his BS in Computer Science and Engineering degree from The University of Toledo and both his MS and PhD degrees in computer science from the University of
Paper ID #41872Board 47: A Mentor-Mentee Matching Algorithm to Automate Process ofFinding an Ideal Mentor for StudentsMs. Sweni ShahDr. Hamid S Timorabadi P.Eng., University of Toronto Hamid Timorabadi received his B.Sc, M.A.Sc, and Ph.D. degrees in Electrical Engineering from the University of Toronto. He has worked as a project, design, and test engineer as well as a consultant to industry. His research interests include the applicatiSanjana DasadiaSamreen Khatib SyedDoaa Muhammad, University of Toronto ©American Society for Engineering Education, 2024 Work In Progress: MentorMate: A Platform to
considered the next stepforward to providing personalized, inclusive and accurate responses that address each student’squestions in an engaging and efficient manner. This information could pertain to course materialsand helping as a course tutor [5] or providing insight on university-specific knowledge, rangingfrom administrative procedures and scholarship opportunities to faculty research areas and campuslife insights.Institutional Support and Other NeedsThis project was initiated by the Department Head of Computer Science & Engineering, who wasworking with faculty in his home department and in the School of Chemical Engineering. TheirPredictive Analytics and Technology Integration Laboratory (PATENT) aims to accelerateadvances in several
has mentored dozens of graduate and undergraduate students in research and K-12 outreach activities and is the Director of the Excellence in Computing and Information Technology Education (ExCITE) program. She is a fellow of the Center for the Advancement of STEM Leadership Program (CASL) and the Opportunities for Under-Represented Scholars (OURS) post-graduate institutional leadership certificate program and an alumna of the Frontiers of Engineering Education program (FOEE) of the National Academy of Engineering. She has been serving on the Project Kaleidoscope (PKAL) Capital Area Regional Network steering committee since 2016.Rui Kang Rui Kang is Professor of Secondary Education (6-12) of Georgia College &
, Nigeria and the University of Cape Town, South Africa. Currently, His research focus is in the field of Computing and Engineering Education where he is involved with investigating team-based computational projects using qualitative, quantitative, and artificial intelligence-based tools. He is also involved with developing and redesigning a Team-Based transdisciplinary graduate course under the Purdue University EMBRIO Innovation Hub Grant project, where He has contributed by applying computational fluid dynamics methods in the development of partial differential equation (PDE) models to implement cell cytokinesis. His ongoing PhD research broadly investigates teamwork interactions and interdisciplinary learning in