University of Texas, Rio Grande Valley Liyu Zhang is an Associate Professor in the Department of Computer Science Department of Computer Science at the University of Texas Rio Grande Valley. He received his Ph. D. in Computer Science from the State University of New York at Buffalo in SeptembDr. Hansheng Lei ©American Society for Engineering Education, 2023Early Integrating of Industry Certification Objectives into Modern Cyber Security Degree CurriculumAbstractWe have recently created a new bachelor’s degree in cyber security (B.Sc. CS) [1] to address thenational and pressing needs for cybersecurity specialists, cyber-crime analysts, incident andintrusions analysts, IT
Paper ID #39170Surveying the Importance of Integrating Technical Interviews intoComputer Science Curriculums and Increasing Awareness in the AcademyMs. Rachel Field, Morgan State University Ms. Field is currently working on her Master’s in Advanced Computing at Morgan State where she received her Bachelor’s in Computer Science. She has interned at the REU MagLab as a software engineer during her undergraduate studies at Morgan State. Currently she is working under Dr. Edward Dillon as a graduate research assistant to educate and increase awareness of the interview process, specifically for computer science
College of Engineering and Computer Science at the University of Texas Rio Grande Valley (UTRGVLaura SaenzDr. Liyu Zhang, The University of Texas, Rio Grande Valley Liyu Zhang is an Associate Professor in the Department of Computer Science Department of Computer Science at the University of Texas Rio Grande Valley. He received his Ph. D. in Computer Science from the State University of New York at Buffalo in Septemb ©American Society for Engineering Education, 2023 A Bridged Cyber Security Curriculum with Embedded Stackable CredentialsAbstract— Supported by a federal grant, The University of Texas Rio Grande Valley (UTRGV)streamlined the Bachelor of Science
Paper ID #36789Effect of Automated Instantaneous Feedback, Unlimited SubmissionAttempts, and Optional Exercises on Student Engagement, Performance, andAcademic Integrity in an Introductory Computer Programming Course forEngineersMarko V. Lubarda, University of California, San Diego Marko V. Lubarda is an Assistant Teaching Professor in the Department of Mechanical and Aerospace Engineering at the University of California, San Diego. He teaches mechanics, materials science, design, computational analysis, and engineering mathematics courses, and has co-authored the undergraduate textbook Intermediate Solid Mechanics (Cambridge
course available in some high schoolsbut many schools lacked teachers with the experience necessary to teach the class, and the situation waseven more dire at the middle school level. For example, there was no common CS curriculum. There hadalso been a lack of administrative support for having teachers attend CS PD. In addition, counselors hadnot encouraged students entering high schools offering the CS course to take it. To meet CS goals in the state, an RPP approach was implemented. RPPs are collaborative, long-term partnerships whose goal is to improve persistent problems of practice in education in a local context.In the RPP model, research is incorporated into decision-making processes, and the problems addressed aremeaningful to
website can serve as a simplemethod to facilitate an accessible and inclusive learning environment for students.KeywordsTeaching/Learning Strategies, Accessibility, Inclusivity, Distributed Learning Environments,Online learning, Course design1. Introduction1.1 BackgroundThe use of Virtual Learning Environments (VLEs) have enabled us to organize learningresources and disseminate information to students with positive impacts in their motivation tolearn [1], [2]. Importantly, analytics from VLEs such as clickstream data can be used topredict at-risk students [3], [4] as well as academic performance of students [5], [6]. VLEsare primarily used as a repository for teaching materials but recently, integration withapplications such as Turnitin, VLEs
Paper ID #38033RVfpga: Computer Architecture Course and MOOC Using a RISC-V SoCTargeted to an FPGA and SimulationDr. Sarah L. Harris, University of Nevada, Las Vegas Dr. Harris is a Professor at the University of Nevada, Las Vegas (UNLV) in the Electrical & Computer Engineering Department. She earned her M.S. and Ph.D. at Stanford University and has worked at Hewlett Packard, Nvidia, and the Technical University of Darmstadt. Before joining the UNLV faculty in 2014, she was a faculty member at Harvey Mudd College for ten years. Her research interests include embedded systems, biomedical engineering, and robotics, and she
robotics10 and human robot teaming11. Due to their distributed, wireless nature,swarms have also been used as an internet of things testbed12. Several low-cost ground roboticsswarms have also been proposed, which allow for scalable testing13-14. Of these platforms,several examples, such as the Pheeno, Spiderino, and Pi-swarm, have been used in educationalcontexts to teach swarm robotics, often in a K-12 context15-18.However, education tools and programs around AI and Swarm AI do not generally have astandard curriculum, as many different traditional fields are needed to come together to learnabout and develop AI at the level of professional practitioners. In Swarm AI in particular, aspectsof robotics, engineering, and computer science are often seen
Paper ID #37043Combining Game-Based and Inquiry-Oriented Learning for Teaching LinearAlgebraDr. Ashish Amresh, Arizona State University Ashish Amresh is an Assistant Professor in the College of Technology and Innovation and is leading the Computer Gaming curriculum initiatives at Arizona State University, where he founded the Computer Gaming Certificate and the Camp Game summer program. IDr. Vipin Verma, Arizona State UniversityMichelle Zandieh, Arizona State University ©American Society for Engineering Education, 2023 Combining Game-Based and Inquiry-Oriented Learning for
online course format. The relationships between course grades, KarmaCollab app engagement, student self-reported sentiment via an end-of-quarter survey, and teaching staff interviews are presented to showcase interesting remote learning insights. At the start of 2020, university students, staff, and faculty faced the unforeseen challenge of transitioning to a fully online curriculum due to the COVID-19 shelter in place order. Although fully online course formats are nothing new, university courses are traditionally built around an in- person experience. One area that thrives from an in-person format is STEM laboratory courses. From chemical mixtures in a controlled lab
Paper ID #38704Latinx Culture, Music, and Computer Science Remix in a Summer CampExperience: Results from a Pilot StudyMs. Jayma Koval, Georgia Institute of Technology Jayma Koval is a Research Associate at Georgia Tech’s Center for Education Integrating Science, Mathe- matics and Computing (CEISMC). At CEISMC, she focuses on educational research in the K-12 setting, curriculum development and teacher learning and professional development. She is currently a Doctoral student in Educational Policy Studies at Georgia State University, focusing on Research, Measurement and Statistics.Diley Hernandez, Georgia Institute of
. focus on the incorporation of CT into K–12 education. The authors reviewvarious pedagogical approaches for teaching CT, including coding activities, game design, androbotics. They argued that CT should be integrated into the existing curriculum rather thantaught as a standalone subject and provided examples of how this can be done across multiplesubject areas [21]. Also, Rehmat et al. focused on exploring effective instructional strategies forteaching young learners CT. The authors highlighted the importance of developing CT skills inearly education and provided an overview of key CT concepts and skills. It was suggested touse questioning and modeling techniques to aid students in understanding the robot’smovements and associated CT
reliance on cloud computing and big data will continuously increase, andnew data-centric technologies and engineering approaches will be developed. Due to this rapidlydeveloping field, there is a need to track these trends and incorporate the corresponding developments intoour current science and engineering curriculum. Besides data science skills already taught in traditionalengineering curricula, such as mathematical, computational, and statistical foundations, the NationalAcademies guide discusses that key concepts in developing data acumen include domain-specificconsiderations and ethical problem-solving. This work-in-progress (WIP) paper will highlight the foundation of a comprehensive study toexplore data science education in two
taught in thissequence is basic programming.The programming instruction presented in ENGR 111 is an extension of the programming skillslearned in ENGR 110. However, ENGR 110 teaches programming basics in Python, whereas theENGR 111 instruction utilizes Arduino microcontrollers for its programming curriculum. Theprogramming instruction in ENGR 111 also forgoes standalone programming assignments forscaffolded modules that prepare students for an end-of-semester Cornerstone Project.Accordingly, students gain exposure to varying programming languages, and a wide introductionto software design concepts that help prepare them for the remainder of their academic andprofessional careers.In this paper, two semesters of ENGR 111 with two different
Northeastern University to focus on teaching and developing curriculum in the First Year Engineering program. ©American Society for Engineering Education, 2023 What to Teach First, Hardware or Software? Improving Success in Introductory Programming CoursesAbstractThis complete evidence-based practice paper presents an analysis and lessons learned inintroductory engineering courses with content that includes problem-solving, algorithmic thinking,the use of microcontrollers, and C++ at a medium-sized private urban university. These coursesspecifically incorporate the integration of hands-on, project-based design projects with computerprogramming. The goal of the project work is to provide an
Intelligence (AI) applications have become an integral part of our lives, from socialapplications on smartphones to crewless vehicles. However, as they remain in the domain of“computer magic,” these new advancements of knowledge processing and reasoning using AI toolswill not be of a great benefit to humanity, unless a complementary education environment isprovided to help students and communities become involved in this scientific revolution early,ethically, and systematically. Introducing and exploring AI concepts and basics earlier in thestudents’ learning journey will help address the future AI job market needs as well as AI ethicsissues and will open the door for new innovative AI applications in all segments of life. The long-term goal of this
NASA University Leadership Initiative (ULI) Project “Safe AviationAutonomy with Learning-enabled Components in the Loop: from Formal Assurances to TrustedRecovery Methods” and NSF Excellent in Research (EIR) project “Integrated Sensor-RobotNetworks for Real-time Environmental Monitoring and Marine Ecosystem Restoration in theHampton River”, the authors have successfully developed a research-based course on machinelearning and robotics for undergraduate engineering students at Hampton University. This paperpresents the goals, challenges, design process, engaging strategies, assessment /outcomes, andlessons learned for the new course. Besides, this paper also presents the integration of IBM AIcourse and NVIDIA machine learning modules, along
contexts, the effects of the policy change may not transfer to othercontexts.7 Conclusion and Future WorkWe examine two different policies, a time-restricted policy and a point-restricted policy, to seewhich policy aligned more with the goal of students only submitting well-tested, quality codesubmissions. Under the point-restricted policy, we experienced a modest increase in correct firstsubmissions. For future work, we shift our focus to tackle the testing aspect of submitting onlyquality code. Integrating more explicit testing components to labs will answer the question ofhow well students are testing these submissions, which is an important component to ensure Time-Restricted vs. Point-Restricted
due to the growth oftechnologies, fast connections, and the widespread use of mobile devices. As a result,cybersecurity education is in dire need of an innovative curriculum and teaching approaches.Game-based learning is one of the emergent and quickly evolving types of computer-basedlearning. Creating cloud services and ready-to-use cybersecurity training courses, with a focus onteaching and training cybersecurity algorithms is essential [3]. Providing a virtual lab offers apractical learning environment is a crucial step, to enable thousands of students to access onlinecybersecurity education [4]. A visual lab provides students with a simulated environment wherethey can gain hands-on experience with cybersecurity tools and techniques
interestedin developing a workstation that integrated as many of the necessary equipment in anelectricity/electronics laboratory as possible and that was economically viable, even forinstitutions with limited resources. To achieve this, the UTESA-OPEX consortium embarked onthe development of several technologies and resources that enabled the functioning of all theinvolved parts in a unified way as an educational ecosystem. Therefore, at the end of the projectdevelopment time, the research team had managed to develop a workstation, a practice board, anLMS platform with educational content, and an application for the interface with the workstation.Workstation:The workstation is the hardware that has been developed to incorporate the electronic boards
Paper ID #37309The ”besTech” Technology Practice Framework for Early Childhood Educa-tionDr. Safia Malallah, Kansas State University Safia Malallah is a postdoc in the computer science department at Kansas State University working with Vision and Data science projects. She has ten years of experience as a computer analyst and graphic de- signer. Besides, she’s passionate about developing curriculums for teaching coding, data science, AI, and engineering to young children by modeling playground environments. She tries to expand her experience by facilitating and volunteering for many STEM workshopsJoshua Levi Weese, Kansas
InitiativesInitiatives to address technical interview preparation for CS majors are expanding. Companiesand organizations alike are making resources available for students to prepare for technicalinterviews [1, 13, 26, 32]. In academic settings, institutions have also begun to expand theirresources and/or adjust their CS curriculums in an effort to foster student exposure to thetechnical interview process [8, 12, 35]. Moreover, academic scholars are now conducting casestudies and related interventions to tackle potential challenges that are associated with thetechnical interview process [7, 20, 23, 25].2.3.1. Persistent Finding – Performance AnxietyWhen observing prior efforts that highlight student performance during mock technicalinterviews, anxiety has been
, 2023 Creating and implementing a custom chatbot in engineering education Shameel Abdullah, Yasser-Al Hamidi, and Marwan Khraisheh Mechanical Engineering Program, Texas A and M University at QatarAbstractThis paper investigates the development and use of a chatbot in an engineering curriculum. Thechatbot helps students find course materials, answer general inquiries, schedule meetings withprofessors and teaching assistants, and much more. Students require assistance during their timeat university. College life is stressful, and tasks such as keeping track of deadlines, schedulingmeetings, and finding resources become daunting as the semester progresses. The constant emailexchanges about general course
robot useful,while the AR robot scored highly in the interest portion of the MUSIC model.This study highlights the potential of AR and VR technology to motivate students in the field of robotics. Theimplementation studied was an effective proof of concept, and future iterations will include a fully immersiveprogramming interface within a virtual environment to allow collaboration over shared tasks and resources, evenwhen geographically separated. Future iterations will also incorporate accessibility and inclusivity to a greater degreeby leveraging Universal Design for Learning (UDL) principles to integrate the tool effectively into the curriculum of anundergraduate engineering course.Keywords: Virtual Reality, robotics, Engineering Education
students agreed or stronglyagreed that the system enabled them to identify areas for improvement in their interviewpreparation. The results from this work could be valuable for educators and administratorslooking to enhance their curriculum and integrate new technologies to improve the careertrajectory of students. We also hope to raise awareness of the effectiveness of using virtual realityas a career training approach to help students combat anxiety and gain practice usinglow-pressure interactive scenarios.1 IntroductionAs of March 2023, roughly 5.8 million individuals were seeking employment in the United States[1]. Although the hiring process can be intimidating for all applicants, it can be especiallydaunting for those new to the job market
improving the classroom experience for both students and instructors. ©American Society for Engineering Education, 2023How much deadline flexibility on formative assessments should we be giving to our students?AbstractRecent studies have proposed new ways of providing learning experiences and measuringstudents’ achievement of learning goals, grounded on the principles of growth mindset, masterylearning, and specifications grading. In one initiative called “A’s for All (as time and interestallow)”, students are given the support to achieve the proficiency they want (not necessarily an A)as long as they are willing to put in the time and effort, thus providing students more control
Paper ID #39344Identifying Collaborative Problem-Solving Behaviors Using SequentialPattern MiningYiqiu Zhou, University of Illinois, Urbana-ChampaignQianhui Liu, University of Illinois, Urbana-Champaign Qianhui (Sophie) Liu is a PhD student in the Department of Curriculum & Instruction, College of Edu- cation at UIUC. Her research interests are learning analytics, educational data mining, computer science education, and explainable AI.Sophia Yang, University of Illinois, Urbana-Champaign Sophia Yang is a second-year Ph.D. candidate with research work focused in the areas of Computing Education, Database Systems
equity, inclusion, andoverall representation in these areas need to be addressed more. In recent years, there has been arise of college-to-company pipeline initiatives with the purpose of increasing thedisproportionately under-representation of black women in tech. However, there has only been aslight increase in the representation of black women in tech from these initiatives, which stillindicate an insufficient level of their representation in tech.The objective of this research is to examine critical factors that impact the representation ofblack women in CS. To look at such factors directly, this article discusses a case-study consistingof a series of focus groups conducted on 24 black women, who were either current CS majors orrecent
Paper ID #40242Data Science (Dataying) for Early ChildhoodDr. Safia A. Malallah, Kansas State University Safia Malallah is a postdoc in the computer science department at Kansas State University working with Vision and Data science projects. She has ten years of experience as a computer analyst and graphic de- signer. Besides, she’s passionate about developing curriculums for teaching coding, data science, AI, and engineering to young children by modeling playground environments. She tries to expand her experience by facilitating and volunteering for many STEM workshops.Lior Shamir, Kansas State University Associate