conference presentations. In her PhD research, she is exploring the integration of generative artificial intelligence (GenAI) into K-12 STEM education.Marina Milner-Bolotin, University of British Columbia, Vancouver Prof. Milner-Bolotin is a STEM (originally physics and mathematics) educator who studies how modern educational technology can be used to enhance K-12 and post-secondary STEM learning and STEM teacher education. She has published extensively in field. She is also a co-author of an introductory physics textbook and a collection of mathematics problems for gifted and curious students. She is also actively involved in STEM outreach and studies its impact on the students and their parents
incorrectpractices, which can have negative effects [6]. However, a complete ban on technology use isnot a viable option, given the growing dependency on technology in everyday life [7, 8].Therefore, technology should be intentionally and appropriately utilized to improvechildren’s CT skills, while being mindful of its potential negative aspects. Current technologyresources also must be improved, and increased collaboration between technologists andeducators is essential to assemble safe and effective technology practices. To help educators use technology intentionally and ensure children develop essentialtechnology literacy in a healthy environment, this paper presents a new besTech frameworkthat was developed from best practices for technology
Paper ID #41833Survey of Tools and Settings for Introductory C ProgrammingSunjae Park, Wentworth Institute of Technology Sunjae Park is an assistant professor in the School of Computing and Data Science at Wentworth Institute of Technology, an engineering-focused institution in Boston. He received his undergraduate degree in Electrical Engineering from Seoul National University, and received a masters degree and PhD from Georgia Institute of Technology. His research interests are in program analysis and computer science education. ©American Society for Engineering Education, 2024 Survey
Paper ID #39791Enabling Remote Student Learning of IoT TechnologiesDr. Lifford McLauchlan, Texas A&M University, Kingsville Dr. Lifford McLauchlan is an Associate Professor and Interim Chair in the Electrical Engineering and Computer Science Department at Texas A&M University - Kingsville, and has also worked for Raytheon, Microvision, AT&T Bell Labs, and as an ONR Distinguished Summer Faculty at SPAWAR San Diego, CA. He has over 55 publications covering areas such as adaptive and intelligent controls, robotics, an ocean wave energy converter, green technology, education, wireless sensor networks and image
Science from Portland State University. Dr. Alawini has worked in various roles in the tech industry, including as a database administrator, lead software developer, and IT Manager. He conducts research on data management systems and computing education. Dr. Alawini is passionate about building data-driven, AI-based systems for improving teaching and learning. ©American Society for Engineering Education, 2023 Identifying Collaborative Problem-Solving Behaviors Using Sequential Pattern MiningAbstractWith the increasing adoption of collaborative learning approaches, instructors must understandstudents’ problem-solving approaches during collaborative activities to better
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
). Evidence of scholarship as demonstrated by national and/or inter- national publications, and experience with ABET and SACS assessment. ©American Society for Engineering Education, 2023 Using VR (Virtual Reality) Technology to Teach Fall Safety Topics to Students: Simulation Outcomes and Student LearningsAbstract VR (Virtual Reality) which is a new technology, has been used to simulate training that is tooexpensive and time-consuming to practice in real life. This study aims to find students’ learningimprovement on Fall related safety by using low-cost VR technology. This will also helppracticing how to survive Fall hazard techniques. In the current study, a well-known VRsoftware was used to
grading." Teaching of Psychology 40.3 (2013): 233-237.3. Satyanarayana, Ashwin, Reneta Lansiquot, and Christine Rosalia. "Using Prescriptive Data Analytics to Reduce Grading Bias and Foster Student Success." 2019 IEEE Frontiers in Education Conference (FIE). IEEE, 2019.4. Kobayashi, Michiko. "Does anonymity matter? Examining quality of online peer assessment and students’ attitudes." Australasian Journal of Educational Technology 36.1 (2020): 98-110.5. Panadero, Ernesto, and Maryam Alqassab. "An empirical review of anonymity effects in peer assessment, peer feedback, peer review, peer evaluation and peer grading." Assessment & Evaluation in Higher Education (2019).6. Dorsey, J. Kevin, and Jerry A. Colliver. "Effect of anonymous
has co-authored three popular textbooks, most recently Digital Design and Computer Architecture: RISC-V Edition in 2021.Daniel Chaver Martinez, University Complutense of Madrid, Spain ˜Luis PinuelOlof KindgrenRobert C.W. Owen ©American Society for Engineering Education, 2023RVfpga: Computer Architecture Course and MOOC using a RISC-V SoC Targeted to an FPGA and Simulation Sarah L. Harris1, Daniel Chaver2, Luis Piñuel2, Olof Kindgren3, Robert Owen4 1 University of Nevada, Las Vegas, University Complutense of Madrid, 3Qamcom Research & 2 Technology, 4Imagination
Paper ID #43665(Board 49/Work in Progress): Using Generative AI for Reducing FacultyWorkload in Online Engineering CoursesMr. Gerry A Pedraza, Texas A&M University Gerry is the Assistant Director of Learning Design at the Engineering Studio for Advanced Instruction and Learning at Texas A&M University. He is a proactive innovator dedicated to enhancing faculty workflows in collaboration with instructional designers. His primary goal is to streamline faculty transition to online teaching, fostering seamless interactions between educators and instructional staff. Gerry’s work is instrumental in saving valuable time
research that hasinvestigated how these technologies can be effectively designed to suit intended objectives.As large investments continue to be made in educational technologies for engineeringclassrooms, it becomes imperative to investigate factors contributing to their successfulintegration for learning. This need has led to recent research focused on understanding thebehavioral intention of students to use technology for their intended purpose, stemming fromthe idea that the success of any innovation lies in its end users' (learners) disposition [3].Several models and theories have thus been adopted, modified, and validated to assessinfluencing factors for students' acceptance behavior in technology-enhanced learningenvironments [4].Although
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
effects of collective MMORPG (Massively Multiplayer Online Role- Playing Games) play on gamers’ online and offline social capital," Computers in human behavior, vol. 27, no. 6, pp. 2352-2363, 2011.[13] M. H. Hopson, R. L. Simms, and G. A. Knezek, "Using a technology-enriched environment to improve higher-order thinking skills," Journal of Research on Technology in education, vol. 34, no. 2, pp. 109-119, 2001.[14] S. Bas and G. Tegan. "What Is a Conceptual Framework? | Tips & Examples." https://www.scribbr.com/methodology/conceptual-framework/ (accessed.[15] C. Carroll, M. Patterson, S. Wood, A. Booth, J. Rick, and S. Balain, "A conceptual framework for implementation fidelity," Implementation science
of Computer Assisted Learning, vol. 28, no. 6, pp. 557–573, Feb.2012, doi: https://doi.org/10.1111/j.1365-2729.2011.00476.x.[4] A. Hellas, T. Vikberg, M. Luukkainen, and M. Pärtel, Scaffolding students’ learning usingtest my code. New York, NY: Association for Computing Machinery, 2013, pp. 117–122. doi:https://doi.org/10.1145/2462476.2462501.[5] C.-Y. Chou and N.-B. Zou, “An analysis of internal and external feedback in self-regulatedlearning activities mediated by self-regulated learning tools and open learner models,”International Journal of Educational Technology in Higher Education, vol. 17, no. 1, Dec. 2020,doi: https://doi.org/10.1186/s41239-020-00233-y.[6] N. Dabbagh and A. Kitsantas, “Using Web-based Pedagogical Tools as Scaffolds
Stephanie Wortel-London. Equity in the who, how and what of computer science education: K12 school district conceptualizations of equity in ‘cs for all’initiatives. In 2019 research on equity and sustained participation in engineering, computing, and technology (RESPECT), pages 1–8. IEEE, 2019.[20] June Ahn and B Quarles. Technology and education in the united states: Policy, infrastructure, and sociomaterial practice. In Convergence: US Education Policy Fifty Years After the ESEA and the HEA of 1965. Harvard Education Press, 2016.[21] Anthony S Bryk, Louis M Gomez, Alicia Grunow, and Paul G LeMahieu. Learning to improve: How America’s schools can get better at getting better. Harvard Education Press, 2015.[22] CSTA &
the needsof the user. Additionally, including comprehensive tutorials, guides, and instructional resourcesempowers educators, researchers, and enthusiasts to build, program, and use the robot in the mostappropriate way for their needs. Since the entire project follows the principles of open-sourcehardware, it fosters collaboration and knowledge sharing, thereby enabling a global community oflearners and innovators. Finally, there will be a discussion on how open-source robotics, combined with modularityand accessible educational materials, revolutionizes robotics education by providing acustomizable, hands-on learning experience to serve as a valuable resource for diversecommunities, fostering a passion for technology, and
context of online learning and engagement, educational technologies, curriculum design which includes innovative and equitable pedagogical approaches, and support programs that boost the academic success of different groups of students. She teaches in active learning environments and strives to bring EE and CER into practice. ©American Society for Engineering Education, 2024 Equitable Computing Education Abstract The field of computing continues to struggle to increase participation that better reflects the domestic composition of the US society at large. Society could benefit from diversifying its workforce as
research has identified the challenges thatchatbots can potentially solve. These include providing mentoring for students and leveraging theadaptation capabilities of chatbots [2]. Currently, prototypes of chatbots have been tested on smallscales in the education sector where various chatbot programming platforms such as GoogleDialogFlow, and Amazon’s Alex Skills were utilized [3]. However, the frequency of use of suchchatbots has not been conclusively linked to improvement in student learning due to the lack ofcomprehensive question-answer databases [4]. 1ChatGPT is another recent advancement that looks promising. However, in terms of learning andteaching, the content it generates is not curated for
Engineering and Mechanics and the Learning Sciences and Technologies at Virginia Tech. He holds degrees in Engineering Mechanics ( ©American Society for Engineering Education, 2023 Work In Progress: Using Natural Language Processing to Facilitate Scoring of Scenario-Based AssessmentsIntroductionEvaluating socio-technical skills is a complicated and difficult task in engineering education.Scenario-based assessments have been proposed as a format providing more targeted feedbackand reliable measures of student performance than existing self-report scales. Unfortunately,while these scenario-based assessments may offer more reliable measures of students’socio-technical skills, the process of
TechnologyTom McKlinMr. Douglas Edwards, Georgia Institute of Technology Douglas Edwards is a K-12 Science Technology Engineering Mathematics (STEM) educational researcher with the Georgia Institute of Technology. His educational experience in the Atlanta area for the past twenty years includes high school mathematics teachiRafael A. Arce-NazarioJoseph Carroll-MirandaIsaris Rebeca Quinones Perez, University of Puerto Rico, Rio PiedrasLilliana Marrero-SolisJason Freeman, Georgia Institute of Technology Jason Freeman is an Associate Professor of Music at Georgia Tech. His artistic practice and scholarly research focus on using technology to engage diverse audiences in collaborative, experimental, and ac- cessible musical
Paper ID #41930Improving Efficiency and Consistency of Student Learning Assessments: ANew Framework Using LaTeXDr. Ira Harkness, University of Florida Ira Harkness is an Instructional Assistant Professor in the Department of Materials Science and Engineering. He has two decades experience in higher education, including directing information technology and facilities efforts at UF, and working with non-profits and community organizations to address K-12 education. His expertise is in computational nuclear engineering and nuclear engineering education.Prof. Justin Watson ©American Society for
administration in cancer chemotherapy. Dr. Farahani’s research interests are in dynamical systems, optimization and Algorithm design.Dr. Esmaeil Atashpaz-GargariDr. Lu Zhang, National University Dr. Lu Zhang is an Associate Professor at National University in the School of Engineering and Com- puting at 3678 Aero Court, San Diego, CA, 92123, USA. His main research interests include science and engineering education, database technologies, data sci ©American Society for Engineering Education, 2023 Optimal Faculty Staffing using Depth First SearchAbstract Scheduling at academic departments is a challenging issue as it involves assigning courses tofaculty based on their availability and
involve a hands on experience that let students see, smell, and feel the things that they are learning about. ©American Society for Engineering Education, 2023Development of a Hardware Educational Tool for Teaching ComputationalThinking with Scratch®.Abstract. In “The Future of Jobs Report 2020”, the world economic forum (WEF) built a list often skills that will be most required in jobs by 2025, one of them being “technology design andprogramming”. In response to the above, in recent years, many projects have been launched toincrease programming knowledge for different audiences and in different parts of the world. Oneof these projects was developed through a collaboration between a university in Colombia and
aspossible.Academic advising is a crucial part of a student’s education, and technology is starting toenhance its effectiveness. Advising apps are gaining popularity in higher education institutionsbecause they help to streamline the process and improve efficiency and accuracy. Feghali et al.[5] conducted a study that highlights the use of advising apps and expert systems as a means tocomplement traditional advising, which primarily depends on one-on-one human interactionbetween students and their advisors. These programs and apps can help faculty advisors tominimize the effort and mental load it takes to find the best courses for each student to take,freeing up more time for them to build connections with their students during advisingappointments
did not watch the videos on time. Thus, while accountability quizzes and shorter videoscan motivate some students, stronger incentives are required to encourage the majority of studentsto complete pre-class videos.Based on the results of the last two questions, while only small percentages of students opposevideo-based learning, the author believes that more motivation and careful design of instructionalvideos would help address these concerns with the growing use of flipped instructions inengineering programs.4. ConclusionsIn the age of digital media, video content has become an increasingly popular way for students tolearn and engage with educational material. This popularity helped the spread of flipped pedagogyin academic setups. Flipped
diagnostics. ©American Society for Engineering Education, 2024 Immersive Virtual Labs for Enhancing In-Person and Online EducationAbstractLabs play a critical role in science and engineering education, offering practical insights andhands-on experience to students that cannot be achieved through theoretical learning alone. Withthe continuous advancement in technology, education is being reshaped and many universitiesare now offering online programs. This shift in educational paradigm offers students access to awider range of academic resources, without being limited by geographical boundaries, timeconstraints, among others. However, the rise of online education also brings unique challenges,such as lack of face-to-face
a moment-by-moment learningcurve [38], a plot of the changes to student model variables in each BKT model on the verticalaxis over the count of performances considered on the horizontal axis. This analysis not onlyprovides us with a simple slope calculation to show performance trends over time, butindications of exactly when during the educational experience the player demonstrated evidenceof learning.Capturing, Processing and Reporting Analysis from ThermoVRWhile a full description of a data telemetry system are well outside the scope of this paper, thehigh-level infrastructure and approaches are easily described. For this work we adopt and extendthe Open Game Data research infrastructure [39] which provides opensource technologies
Conference on Innovation and Technology in Computer Science Education V. 1., 2021, pp. 415-421.[17] Massachusetts Institute of Technology. “Crush Your Coding Interview.” https://capd.mit.edu/resources/crush-your-coding-interview/. (2022, January 18). Retrieved February 4, 2023.[18] Northeastern University. “Interview type: Technical.” Employer Engagement and Career Design. https://careers.northeastern.edu/article/interview-type-technical/. Retrieved February 5, 2023.[19] Rensselaer Polytechnic Institute. “Interviewing.” https://ccpd.rpi.edu/students/job- search/interviewing Retrieved February 1, 2023.[20] Stanford University. “CS 9: Problem-solving for the CS technical interview.” https://web.stanford.edu/class/cs9
, Z. Bright, Q. Kimble-Brown, C. Rogers, M. Lewis, J. Esema, B. Clinkscale, and K.L. Williams. “Exposing Early CS Majors to Coding Interview Practices: An HBCU Case Study.” 2021 Conference on Research in Equitable and Sustained Participation in Engineering, Computing, and Technology (RESPECT), IEEE, 2021, pp. 1-4.[17] E. Dillon, and K. L. Williams. "Course content as a tool of inclusivity for Black/African- American women in computing." Journal of Computing Sciences in Colleges, 36(3), 2020. pp. 151-160.[18] Z. Dodds, C. Alvarado, G. Kuenning, and R. Libeskind-Hadas. “Breadth-first CS 1 for scientists.” ACM SIGCSE Bulletin., 39, 3, 2007, pp. 23–27.[19] EEOC.gov. “US Equal Employment Opportunity Commission. Diversity in
. Hayne, “Design of an Instructional Processor,” Supplement to: C. Roth and L. John, Digital Systems Design Using VHDL, Third Edition, Boston, MA: Cengage Learning, 2018. [Online]. Available: http://academic.cengage.com/resource_uploads/downloads/1305635140_559956.pdf.[3] RISC-V International. [Online]. Available: https://riscv.org/.[4] S. Harris, D. Chaver, L. Pinuel, O. Kindgren, and R. Owen, “RVfpga: Computer Architecture Course and MOOC using a RISC-V SoC Targeted to an FPGA and Simulation,” Proceedings ASEE Annual Conference and Exposition, Baltimore, MD, June 2023.[5] Grenoble Institute of Technology, “LeaRnV: RISC-V based SoC Platform for Research Development and Education.” 2020. [Online]. Available: https