Conference Session

Computers in Education Division (COED) Poster Session

Collection

2023 ASEE Annual Conference & Exposition

Authors

Matthew Norris, Virginia Tech; Hamidreza Taimoory, Virginia Polytechnic Institute and State University; Andrew Katz, Virginia Polytechnic Institute and State University; Jacob R Grohs, Virginia Polytechnic Institute and State University

Tagged Divisions

Computers in Education Division (COED)

students inthe college of engineering and college of arts and sciences. Student responses to open-endedquestions were scored manually by two trained raters in accordance with Grohs et al.’s publishedscoring guide [15]. Scores for each response were assigned and rationales recorded. An initialsample of 20% of the responses were scored individually by each rater. These scores were thencompared across raters to develop a consensus for interpreting student-generated text [16] andscoring guidelines normalized across raters. The remaining 80% of responses were split evenlybetween the two raters. This process required 50 human hours of work.Facilitated ScoringUsing the RStudio and the R Shiny package we import a spreadsheet of the raw text

Conference Session

Computers in Education Division (COED) Poster Session (Track 1.A)

Collection

2025 ASEE Annual Conference & Exposition

Authors

Joel Nirupam Raj; Ashwath Muppa, Thomas Jefferson High School for Science and Technology; Rhea Nirmal; Teo W. Kamath; Achyut Dipukumar; Aarush Laddha; Mihai Boicu, George Mason University

Tagged Topics

Diversity

Tagged Divisions

Computers in Education Division (COED)

] Mok, R.; Campanelli, M.; Datta, A.; Gupta, A.; Hickman, R.; Osthus, F.; Zwart, P. Using AILarge Language Models for Grading in Education: A Hands-On Test for Physics. arXiv preprintarXiv:2411.13685, 2024[4] J. Raj, A. Muppa; A. Dipukumar; R. Nirmal; A. Laddha; T. Kamath, S. Hong, M. Potla and M.Boicu. "Quantitative Analysis of Rubric-based Feedback Received From Claude 3.5 Sonnet onMathematical Programming Problems," 2024 IEEE MIT Undergraduate Research TechnologyConference (URTC), Cambridge, MA, USA, 2024, pp. 1-5,doi: 10.1109/URTC65039.2024.10937532.[5] H. McNichols, J. Lee, S. Fancsali, S. Ritter, and A. Lan, “Can Large Language ModelsReplicate ITS Feedback on Open-Ended Math Questions?,” 2024, arXiv: 2405.06414[6] K. M. Collins et al

Conference Session

Computers in Education Division (COED) Track 6.C

Collection

2025 ASEE Annual Conference & Exposition

Authors

Sandra Monika Wiktor, University of North Carolina at Charlotte; Mohsen M Dorodchi, University of North Carolina at Charlotte

Tagged Divisions

Computers in Education Division (COED)

FIE, ICER, and ASEE, and brings years of teaching experience in software engineering and foundational computing courses.Dr. Mohsen M Dorodchi, University of North Carolina at Charlotte Dr. Dorodchi has been teaching in the field of computing for over 35 years of which 25 years as an educator. He has taught the majority of the courses in the computer science and engineering curriculum over the past 25 years such as introductory programming, data structures, databases, software engineering, system programming, etc. He has been involved in a number of National Science Foundation supported grant projects including Scholarship for STEM students (S-STEM), Researcher Practitioner Partnership (RPP), IUSE, and EAGER

Conference Session

Computers in Education Division (COED) Track 4.B

Collection

2025 ASEE Annual Conference & Exposition

Authors

Arezou Harraf; Yuetong Lin, Embry-Riddle Aeronautical University - Worldwide; A. Mehran Shahhosseini, Indiana State University

Tagged Divisions

Computers in Education Division (COED)

Enhanced Search using Perplexity The second step involved using Perplexity as an AIsearch tool. The student wrote the topic, then applied the prompt “List published scholarlyarticles on this topic for literature review.” While this approach saved time, the student found thatPerplexity’s suggestions did not fully address the complexity of the research question and wereless relevant overall.Below is the List of articles provided by Perplexity: • Smith, J. A., & Brown, T. L. (2024). Artificial Intelligence in Supply Chain Negotiations: A Comprehensive Review. Journal of Supply Chain Management, 60(2), 145-163. https://doi.org/10.1111/jscm.12345 • Johnson, M. R., Lee, S. H., & Garcia, P. (2024). Leveraging AI for Optimal Bidding

Conference Session

Computers in Education Division (COED) Track 6.C

Collection

2025 ASEE Annual Conference & Exposition

Authors

Aimee Allard, North Carolina State University at Raleigh

Tagged Divisions

Computers in Education Division (COED)

students collaboratively fill out the team’s project timeline on the whiteboard using course due dates and noting check-in days, sponsor meetings, team- or sponsor-driven deadlines, etc. • 10–20 minutes: Definite preliminary requirements (or refine them/elaborate on features for teams that have already developed a list of requirements). Group requirements by iterations. For traditional software projects, teams might opt to express requirements functionally, as use cases, or as user stories. For games projects, teams will need to define the genre of the game, who the playable characters are, and the goal(s) of the game (may include win/lose conditions), in addition to gameplay rules and mechanics. Reflect on

Conference Session

Teaching with ML and Generative AI

Collection

2024 ASEE Annual Conference & Exposition

Authors

Abdulrahman AlRabah, University of Illinois Urbana-Champaign; Sophia Yang, University of Illinois Urbana-Champaign; Abdussalam Alawini, University of Illinois Urbana-Champaign

Tagged Divisions

Computers in Education Division (COED)

e.CRN, 2 (SELECT SUM(Score * Credits)/SUM(Credits) 3 FROM Enrollments e2 4 WHERE e.CRN = e2.CRN) AS CourseAvgScore, 5 s.NetId, 6 e.Score 7 FROM Students s 8 JOIN Enrollments e ON s.ID = e.CourseID -- Error: Incorrect JOIN condition, should be based on a valid relational key 9 WHERE (SELECT SUM(Score * Credits)/SUM(Credits)10 FROM Enrollments e211 WHERE e.CRN = e2.CRN) >= 8012 AND e.Score > 8513 ORDER BY e.CRN DESC, e.Score DESC; Instructor Query: 1 SELECT e.CRN, 2 (SELECT SUM(Score * Credits)/SUM(Credits) 3 FROM Enrollments e2 4 WHERE e.CRN = e2.CRN) AS CourseAvgScore, 5 s.NetId, 6 e.Score 7 FROM

Conference Session

Computers in Education Division (COED) Track 5.D

Collection

2025 ASEE Annual Conference & Exposition

Authors

Sung Je Bang, Texas A&M University; Anna Stepanova, Texas A&M University; Syeda Fizza Ali, Texas A&M University; Christina Belanger, Texas A&M University; Tracy Anne Hammond, Texas A&M University; Saira Anwar, Texas A&M University

Tagged Divisions

Computers in Education Division (COED)

. Ericson and G. Wollin, “Micropaleontology,” Sci. Am., vol. 207, no. 1, pp. 96–108.[2] R. W. Jones, Foraminifera and their applications, 1st ed. Cambridge: Cambridge university press, 2014.[3] L. Capotondi, C. Bergami, G. Orsini, M. Ravaioli, P. Colantoni, and S. Galeotti, “Benthic foraminifera for environmental monitoring: a case study in the central Adriatic continental shelf,” Environ. Sci. Pollut. Res., vol. 22, no. 8, pp. 6034–6049, Apr. 2015, doi: 10.1007/s11356-014-3778-7.[4] F. R. Gío Argáez, B. B. Martínez Villa, X. A. Nava Fernández, and V. Zamora Pérez, “Microfossils as proxies: Paleoecological and paleoceanographic indicators,” in Past Environments of Mexico, R. Guerrero-Arenas and E. Jiménez-Hidalgo, Eds., in

Conference Session

Computers in Education Division (COED) Best of CoED Paper Session (Track 1.B)

Collection

2025 ASEE Annual Conference & Exposition

Authors

Jesan Ahammed Ovi, Colorado School of Mines; Gabriel Tomas Fierro, Colorado School of Mines; C. Estelle Smith, Colorado School of Mines

Tagged Divisions

Computers in Education Division (COED)

Conference Session

Computers in Education Division (COED) Poster Session

Collection

2024 ASEE Annual Conference & Exposition

Authors

Ella Kokinda, Clemson University; D. Matthew Boyer, Clemson University

Tagged Divisions

Computers in Education Division (COED)

technical, relating to the stream content, technology in general, technicalemployment, or general encouragement and suggestions from viewers. Some streams had mixedsocial and technical interactions where streamers might go off-topic due to a chat message orbuilt-in social time.RQ2 Knowledge Transfer Knowledge transfer in streams occurs most generally through thethink-aloud nature of streamers who, at a high level, talk through what they are working on orplan to work on during stream. In most streams, a viewer may pose a question to the streamerseeking information about what they are working on or something entirely different, but stilltechnology related. In S3’s stream, a viewer asks why the streamer works on a particular project,S3 responds:7 “I

Conference Session

Spotlight on Diverse Learners

Collection

2024 ASEE Annual Conference & Exposition

Authors

Sung Je Bang, Texas A&M University; Saira Anwar, Texas A and M University

Tagged Divisions

Computers in Education Division (COED)

practice,” Engl. Specif. Purp., vol. 23, no. 4, pp. 425– 445, Jan. 2004, doi: 10.1016/j.esp.2004.01.002.[2] Eun Gyong Kim and A. Shin, “Seeking an Effective Program to Improve Communication Skills of Non-English-Speaking Graduate Engineering Students: The Case of a Korean Engineering School,” IEEE Trans. Prof. Commun., vol. 57, no. 1, pp. 41–55, Mar. 2014, doi: 10.1109/TPC.2014.2310784.[3] Y.-R. Tsai, C.-S. Ouyang, and Y. Chang, “Identifying Engineering Students’ English Sentence Reading Comprehension Errors: Applying a Data Mining Technique,” J. Educ. Comput. Res., vol. 54, no. 1, pp. 62–84, Mar. 2016, doi: 10.1177/0735633115605591.[4] L. R. Cox and K. G. Lough, “The importance of writing skill to the engineering students

Conference Session

Computers in Education Division (COED) Track 3.B

Collection

2025 ASEE Annual Conference & Exposition

Authors

Wesley A Brashear, Texas A&M University; Sandra B Nite, Texas A&M University; Richard Lawrence, Texas A&M University; Dhruva Chakravorty, Texas A&M University

Tagged Topics

Diversity

Tagged Divisions

Computers in Education Division (COED)

camps, clubs, or after school activities cangive students a sense of success and increase students’ interest in learning more about Python orother programming languages [14]. This strategy could also be used in formal education with acareful selection of projects that lead to learning the programming language in depth over thecourse of the year. Over the long run such strategies can broaden participation in computing byincreasing interest and confidence in learning programming languages.AcknowledgementsWe gratefully acknowledge the GenCyber Program for the support to offer cybersecurity campsfree of charge to U.S. students.References[1] J. R. Warner, C. L. Fletcher, R. Torbey, and L. S. Garbrecht, “Increasing capacity forcomputer science in

Conference Session

Computers in Education Division (COED) Track 3.A

Collection

2025 ASEE Annual Conference & Exposition

Authors

Sierra Zoe Bennett-Manke, United States Military Academy; Maria R. Ebling, United States Military Academy

Tagged Divisions

Computers in Education Division (COED)

’ incoming major GPA toaccount for the effect of student ability.AcknowledgmentsThe authors wish to thank the students who participated in the study for their valuable feedbackand guidance as well as COL Christa Chewar for the inspiration and encouragement. The authorsalso wish to thank LTC Mike Powell who helped them with using RStudio, the method ofevaluation for the quantitative results, and the evaluation of the quantitative results. The viewsexpressed here are those of the authors and do not reflect the official policy or position of theDepartment of the Army, Department of Defense, or the U.S. Government.References [1] S. Z. Bennett-Manke and M. R. Ebling. “GraySim: An OS Scheduling Simulator”. In: J. Comput. Sci. Coll. 39.8 (May 2024), pp

Conference Session

Computers in Education Division (COED) Poster Session (Track 1.A)

Collection

2025 ASEE Annual Conference & Exposition

Authors

Siddharthsinh B Jadeja, University at Buffalo, The State University of New York; Corey T Schimpf, University at Buffalo, The State University of New York; A Lynn Stephens

Tagged Divisions

Computers in Education Division (COED)

LearningSciences, 2005, pp. 1–16.[2] S. Doroudi, “What happened to the interdisciplinary study of learning in humans andmachines?,” J. Learn. Sci., vol. 32, no. 4–5, pp. 663–681, Oct. 2023, doi:10.1080/10508406.2023.2260159.[3] S. Ritter and S. B. Blessing, “Authoring Tools for Component-Based LearningEnvironments,” J. Learn. Sci., vol. 7, no. 1, pp. 107–132, Jan. 1998, doi:10.1207/s15327809jls0701_4.[4] J. Siemer-Matravers, “Intelligent Tutoring Systems and Learning as a Social Activity,”Educ. Technol. Publ. Inc, vol. 39, no. 5, pp. 29–32, 1999.[5] J. Wertch, “PSYCHOLOGY: L. S. Vygotsky’s ‘New’ Theory of Mind,” Am. Sch., vol. 57,no. 1, pp. 81–89, 1988.[6] X. Li, Y. Sun, and Z. Sha, “LLM4CAD: Multimodal Large Language Models for Three

Conference Session

Computers in Education Division (COED) Track 3.E

Collection

2025 ASEE Annual Conference & Exposition

Authors

Ella Kokinda, Clemson University; D. Matthew Boyer, Clemson University; Paige Rodeghero, Clemson University

Tagged Divisions

Computers in Education Division (COED)

the perceived challenges of live streaming as an informal learning opportunity forcomputer science students?Through this work, we aim to understand and evaluate whether or not live streaming impacts anundergraduate student’s perceived self-efficacy in software or game development, RQ1 . Toquantitatively measure self-efficacy, we have adapted questions from Ramalingam andWiedenbeck’s Computer Programming Self-Efficacy Scale and Hiranrat et al.’s surveymeasurements for software development career [41, 42]. As we allow the students to choose theirown projects and set their own goals, we expect there to be some division among the participantson how quickly they believe themselves to be improved based on the gravity of the goals they setfor

Conference Session

Computers in Education Division (COED) Poster Session (Track 1.A)

Collection

2025 ASEE Annual Conference & Exposition

Authors

Rawan Adnan Alturkistani, Virginia Tech Department of Engineering Education; Mohammed Seyam, Virginia Polytechnic Institute and State University

Tagged Divisions

Computers in Education Division (COED)

Conference Session

COED: Computing in K-12 / Early Childhood Education

Collection

2023 ASEE Annual Conference & Exposition

Authors

Safia A. Malallah, Kansas State University; Lior Shamir, Kansas State University; William Henry Hsu, Kansas State University; Joshua Levi Weese, Kansas State University; Salah Alfailakawi, Kansas State University

Tagged Topics

Diversity

Tagged Divisions

Computers in Education Division (COED)

Practices and Processes,” Hollylynne S. Lee etel. developed a framework using the work of statistics educators and researchers to investigatehow data science practices can inform work in K–12 education. Their framework buildsfundamental practices and processes from data science [19]. The math field has contributed to data science research via the Common Core StateStandards Initiative (CCSSI), which is a joint project to develop common K–12 reading andmath standards designed to prepare students for college and careers. The CCSSI includes a datascience section for elementary students that focuses on data collection, data type, function,analysis type, and sample [20]. Similarly, the Launch Years Data Science Course Frameworkprovides broad

Conference Session

Computers in Education Division (COED) Track 2.D

Collection

2025 ASEE Annual Conference & Exposition

Authors

Ryan Tsang, University of California, Davis; SYDNEY Y WOOD, University of California, Davis

Tagged Topics

Diversity

Tagged Divisions

Computers in Education Division (COED)

form for the study.Checkpoint assessment results were collected and graded using a 3-pass process. Graders con-ducted a first pass to familiarize themselves with questions and the range of answers, then a secondpass to create detailed rubric items based on answer classifications, ending with a final pass withthe finalized rubric to ensure all students were scored by the same metrics. Rubrics were createdon a per-question basis and credit was assigned based on answers’ resemblance to solution keysand demonstrated understanding of the questions’ underlying concepts.Post-assessment surveys asked students to report the perceived usefulness of the chatbot(s) theyused during preparation and prompted an open-ended reflection on how they used the

Conference Session

Computers in Education Division (COED) Poster Session (Track 1.A)

Collection

2025 ASEE Annual Conference & Exposition

Authors

Alan Marchiori, Bucknell University

Tagged Divisions

Computers in Education Division (COED)

; def testbench():14 reg a, b; wire out; a = reg(); b = reg()15 andgate device (out, a, b); device = andgate(a, b)16 initial begin def monitor():17 $monitor("a=%b, b=%b, out=%b", print("a=%s, b=%s, out=%s" %\18 a, b, out); (a(), b(), device()))19 // step through the inputs # step through the inputs20 #10 a = 0; b = 0; a.set(0); b.set(0); monitor()21 #10 a = 0; b = 1; a.set(0); b.set(1); monitor()22 #10 a = 1; b = 0; a.set(1); b.set(0); monitor

Conference Session

COED: Online and Remote Learning

Collection

2023 ASEE Annual Conference & Exposition

Authors

Rishi Sunny Gulati; Matthew West, University of Illinois, Urbana-Champaign; Craig Zilles, University of Illinois, Urbana-Champaign; Mariana Silva, University of Illinois, Urbana-Champaign

Tagged Topics

Diversity

Tagged Divisions

Computers in Education Division (COED)

offering online sections of courses to students that want the flexibilitythat they facilitate, if their primary concern is student performance. We found no statistically sig-nificant difference in the overall performance of students that elect to take a course online relativeto those that elect to take it in person. Taking courses online may, however, have a substantialnegative impact on a student’s sense of belonging. This effect is particularly pronounced for un-derrepresented minority students and first generation students, but not present in women.References [1] B. Bizot and S. Zweben, “Generation cs, three years later,” On the Internet at https://cra. org/generation-cs- three-years-later/(visited August 2019), 2019. [2] T. Camp, W. R

Conference Session

Computers in Education Division (COED) Track 3.C

Collection

2025 ASEE Annual Conference & Exposition

Authors

Randy McDonald, Texas A&M University; Salvatore Enrico Paolo Indiogine; Nasiha Lachaud, Texas A&M University; Wei Lu, Texas A&M University; Mohammad Affan Khokhar

Tagged Divisions

Computers in Education Division (COED)

developing academic course content.References[1] T. Petricini, C. Wu, and S. T. Zipf, "Perceptions about generative AI and ChatGPT use by faculty and college students," Aug. 13, 2023. [Online]. Available: osf.io/preprints/edarxiv/jyma4[2] R. Soledad, O. Córdova, and I. Azeneth, "Training teaching personnel in incorporating generative artificial intelligence in higher education: A complex thinking approach," Repositorio.tec.mx, 2023. [Online]. Available: https://hdl.handle.net/11285/651093[3] S. Memis, "The use of ChatGPT in engineering education: Innovative education methods of the future," presented at the 3rd Rumeli Engineering Education Symp., Istanbul, Turkey, 2023, pp. 287–295.[4] G. Alphonso, "Generative

Conference Session

COED: Skills for Moving from Computing Student to Professional

Collection

2023 ASEE Annual Conference & Exposition

Authors

Rachel Field, Morgan State University; Steven J. Fuller; Edward Dillon, Morgan State University

Tagged Divisions

Computers in Education Division (COED)

institutions are beginning toimplement technical interview practices into the classroom as assignments, group projects,warm-ups, class exercises, and dedicating a class to the topic. For instance, literature shows thatexposing students to technical interview exercises in their Data Structure course(s) is one of themost effective methods. One reason being that students are exposed to the process early on but itbecomes natural for them to think as interviewees based on the construct of these particularcourses. Likewise, literature suggests that introducing the technical interview process early in astudent’s computational development could better gauge the overall effectiveness of thisemployed initiative. Yet, the number of studies that reflect such

Conference Session

Computers in Education Division (COED) Poster Session (Track 1.A)

Collection

2025 ASEE Annual Conference & Exposition

Authors

MALEK EL KOUZI, Queen's University; Omar I.M Bani-Taha, Carleton University; Richard Reeve, Queen's University

Tagged Divisions

Computers in Education Division (COED)

active contributors in their educational journey, cultivating anenvironment where learning is characterized by collaboration, interactivity, andprofound engagement.References[1] T. K. F. Chiu, “School learning support for teacher technology integration from a self-determination theory perspective,” Educ. Technol. Res. Dev., vol. 70, no. 3, p. 931, Jun. 2022.[2] Y. Wen, “Augmented reality enhanced cognitive engagement: designing classroom-based collaborative learning activities for young language learners,” Educ. Technol. Res. Dev., vol. 69, no. 2, pp. 843–860, Apr. 2021.[3] J. Bacca, S. Baldiris, R. Fabregat, and S. Graf, “Augmented Reality Trends in Education: A Systematic Review of Research and

Conference Session

Computers in Education Division (COED) Poster Session (Track 1.A)

Collection

2025 ASEE Annual Conference & Exposition

Authors

Kangxuan Rong, Cornell University; Campbell James McColley, Cornell University; Ted Karanja Mburu, University of Colorado Boulder; Alexandra Werth, Cornell University

Tagged Divisions

Computers in Education Division (COED)

.1365-2648.1995.22010048.x.PMID: 7560535.[6] I.H.Y. Yim, J. Su, Artificial intelligence (AI) learning tools in K-12 education: A scopingreview, J. Comput. Educ. (2024). https://doi.org/10.1007/s40692-023-00304-9.[7] J. Pulgar, C. Candia, P. Leonardi, Undergrad classroom cooperation and academicperformance: Beneficial for real-world-like problems but detrimental for algebra-basedproblems, arXiv, 2019. https://arxiv.org/abs/1912.06923.[8] J. Rogers, S. Peecksen, M. Douglas, M. Simmons, Validation of a reflection rubric for highereducation, Reflect. Pract. 20, 6 (2019) 761–776.https://doi.org/10.1080/14623943.2019.1676712.[9] K.A. Treibergs, D. Esparza, J.A. Yamazaki, M.K. Smith, Journal reflections shed light onchallenges students face in an

Conference Session

Computers in Education Division (COED) Poster Session (Track 1.A)

Collection

2025 ASEE Annual Conference & Exposition

Authors

Eesha tur razia babar; Ahmed Ashraf Butt, University of Oklahoma

Tagged Divisions

Computers in Education Division (COED)

work will expand toregression problems and incorporate local interpretability techniques like LIME and Eli5.References [1] O. Scheuer and B. M. McLaren, “Educational data mining,” in Encyclopedia of the Sciences of Learning, Boston, MA: Springer US, 2012, pp. 1075–1079. [2] F. Alshareef, H. Alhakami, T. Alsubait, and A. Baz, “Educational Data Mining Applications and Techniques,” International Journal of Advanced Computer Science and Applications, vol. 11, 2020. [3] T. Zarsky, “Transparency in data mining: From theory to practice,” in Studies in Applied Philosophy, Epistemology and Rational Ethics, Berlin, Heidelberg: Springer Berlin Heidelberg, 2013, pp. 301–324. [4] S. Roy and A. Garg, “Predicting academic performance of

Conference Session

COED: Computing in K-12 / Early Childhood Education

Collection

2023 ASEE Annual Conference & Exposition

Authors

Safia Malallah, Kansas State University; Lior Shamir, Kansas State University; William Henry Hsu, Kansas State University; Joshua Levi Weese, Kansas State University; Salah Alfailakawi, Kansas State University

Tagged Divisions

Computers in Education Division (COED)

forearly childhood. As a future work, the models and framework developed could be branched intoseveral qualitative research studies for validation. Additionally, AI inclusion for early childhoodlearning could be studied.AcknowledgementsThis work was funded by the National Science Foundation (NSF) with Grant No DRLGEGI008182. However, the authors alone are responsible for the opinions expressed in thiswork and do not reflect the views of the NSF.References[1] A. Strawhacker and M. U. Bers, "Promoting positive technological development in a Kindergarten makerspace: A qualitative case study," European Journal of STEM Education, vol. 3, no. 3, p. 9, 2018.[2] B. Vittrup, S. Snider, K. K. Rose, and J. Rippy, "Parental perceptions of the

Conference Session

COED: AI and ML Topics

Collection

2023 ASEE Annual Conference & Exposition

Authors

Nebojsa I. Jaksic, Colorado State University, Pueblo; Bahaa Ansaf, Colorado State University, Pueblo

Tagged Topics

Diversity

Tagged Divisions

Computers in Education Division (COED)

of applications that were introduced in the workshop.Upon completion of the workshop, the participants were given an eight-question exit post-trainingsurvey shown in Figure 2. There were six quantitative questions using a five point or a three-pointLikert scale as well as two qualitative questions. The two qualitative questions were also used aspedagogical tools based on experiential learning best practices. Question 7’s goal was to elicit apositive self-reflection while Question 8 reinforced learning through internalization andsummarization. 1. Exiting this workshop, I learned something new about AI concepts, applications, and ethics (1 - strongly disagree to 5 - strongly agree). 2. I have a better understanding of AI and how to

Conference Session

COED: Online and Remote Learning

Collection

2023 ASEE Annual Conference & Exposition

Authors

Janardhanan Gangathulasi, National Institute of Technical Teachers Training and Research, Chennai, India; Shanmuganeethi Velu, P.E.; P. Malliga; Dinesh Kumar K.S.A.

Tagged Divisions

Computers in Education Division (COED)

University, India. He extensively traveled within and abroad for technical lectures viz., USA, Germany, Belarus, China, Hong Kong, Thailand, Malaysia, Singapore.Dr. Shanmuganeethi Velu, P.E., Dr. V.Shanmuganeethi, Professor, Department of Computer Science and Engineering. He has been work- ing in the domain of Education Learning Analytics, web technologies, programming Paradigm, Instruc- tional technologies and Teaching aˆ C” Learning PraDr. P. MalligaDr. Dinesh Kumar K.S.A. Dr. K S A Dineshkumar, Assistant Professor, Department of Civil Engineering. He has been working in the domain of Structural Engineering, Geographical Information System, Sustainable development, Smart City, Instructional technologies and Teaching

Conference Session

COED: AI and ML Topics

Collection

2023 ASEE Annual Conference & Exposition

Authors

Shatha Jawad, National University; Ronald P. Uhlig, National University; Pradip Peter Dey; Mohammad N. Amin, National University; Bhaskar Sinha, National University

Tagged Divisions

Computers in Education Division (COED)

back on trackfaster by alerting teachers to potential problems. This paper proposes a Deep Learning NeuralNetworks approach that helps students select their best-fit specialization in a specific category.Deep learning is a subset of machine learning, but it can determine whether a prediction isaccurate through its own neural network- no human help is required [1]. The proposed systemwill use a dataset that contains student data that is related to the general education coursesrequired for their program, such as grades, the number of hours spent on each course's materials,the opinion of the student about the content of each course, and the course(s) that the studentenjoyed the most. Additional data will be included in the dataset such as the

Conference Session

The Best of Computers in Education

Collection

2023 ASEE Annual Conference & Exposition

Authors

Sarah L. Harris, University of Nevada, Las Vegas; Daniel Chaver Martinez, University Complutense of Madrid, Spain; Luis Piñuel; Olof Kindgren; Robert C.W. Owen

Tagged Divisions

Computers in Education Division (COED)

, Thong Doan, Oliver Rew, NikoNikolay, and Guanyang He. We also acknowledge the support of projects PID2021-123041OB-I00, funded by MCIN/AEI/ 10.13039/501100011033 and by “ERDF A way of making Europe”,and by the CM under grant S2018/TCS-4423.References[1] RISC-V International: https://riscv.org/. Accessed February 21, 2023.[2] VeeR (SweRV) Cores: https://github.com/chipsalliance/Cores-VeeR-EH1, https://github.com/chipsalliance/Cores-VeeR-EL2, https://github.com/chipsalliance/Cores- VeeR-EH2. Accessed February 21, 2023.[3] Arm Introduction to Computer Architecture: https://www.arm.com/resources/education/education-kits/computer-architecture. Accessed February 21, 2023.[4] S. Harris, D. Harris, D. Chaver, R. Owen, Z. Kakakhel, E

Conference Session

Programming Education 1

Collection

2024 ASEE Annual Conference & Exposition

Authors

Sunjae Park, Wentworth Institute of Technology

Tagged Divisions

Computers in Education Division (COED)

problem for sufficiently large numbers, for most introductory C programming this is not aproblem. For example, strlen returns an unsigned integer. This means the following code can leadto a compiler warning.f o r ( i n t i = 0 ; i < s t r l e n ( ” H e l l o ” ) ; i ++)Some other issues were the sluggishness of every operation. Running Ubuntu inside a virtualmachine is taxing on the graphics card, and the slow build times of catch2 was a frequent complaint.Novice students tend to write relatively small programs, so the additional compile time can slowdown their development cycle.In subsequent iterations, students running Windows were instructed to use Windows Subsystem forLinux (WSL) instead of a hypervisor. Visual Studio Code (and CLion) both