Conference Session

Computer-Supported Pedagogy and Assessment

Collection

2024 ASEE Annual Conference & Exposition

Authors

Jim Sosnowski, University of Illinois Urbana-Champaign; Julie M Baker, University of Illinois Urbana-Champaign; Olivia Arnold, University of Illinois Urbana-Champaign; Mariana Silva, University of Illinois Urbana-Champaign; David Mussulman, University of Illinois Urbana-Champaign; Craig Zilles, University of Illinois Urbana-Champaign; Matthew West, University of Illinois Urbana-Champaign

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Diversity

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Computers in Education Division (COED)

Paper ID #44303Reflections on 10 years of Operating a Computer-based Testing Facility: LessonsLearned, Best PracticesDr. Jim Sosnowski, University of Illinois Urbana-Champaign Jim Sosnowski is the Assistant Director of the Computer-Based Testing Facility (CBTF) at the University of Illinois Urbana-Champaign.Dr. Julie M Baker, University of Illinois Urbana-Champaign Julie Baker is a Learning Design Specialist for the Applied Technologies for Learning in the Arts and Sciences (ATLAS) group in the College of Liberal Arts and Sciences (LAS). She helps LAS faculty implement best practices for computer-based assessment and

Conference Session

Spotlight on Diverse Learners

Collection

2024 ASEE Annual Conference & Exposition

Authors

Isabella Gransbury, North Carolina State University; Monica M. McGill, Institute for Advancing Computing Education; Leigh Ann DeLyser

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Diversity

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Computers in Education Division (COED)

://CSEdResearch.org.[26] Mazyar Seraj, Eva-Sophie Katterfeldt, Serge Autexier, and Rolf Drechsler. Impacts of creating smart everyday objects on young female students’ programming skills and attitudes. In Proceedings of the 51st ACM Technical Symposium on Computer Science Education, pages 1234–1240, 2020.[27] Monique M Jethwani, Nasir Memon, Won Seo, and Ariel Richer. “i can actually be a super sleuth” promising practices for engaging adolescent girls in cybersecurity education. Journal of Educational Computing Research, 55(1):3–25, 2017.[28] Lauren E Margulieux, Briana B Morrison, Baker Franke, and Harivololona Ramilison. Effect of implementing subgoals in code. org’s intro to programming unit in computer science principles. ACM

Conference Session

ML and Generative AI Tools and Policies

Collection

2024 ASEE Annual Conference & Exposition

Authors

Sofia M Vidalis, Pennsylvania State University; Rajarajan Subramanian, Pennsylvania State University; Fazil T. Najafi, University of Florida

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Computers in Education Division (COED)

outcomes and improve student engagement. The integration of AI tools has the potential to significantly impact student learning, bridging the gap between theoretical knowledge and practical application. This paper explores the impact of AI tools on student learning in engineering education, particularly in civil engineering. AI tools offer numerous benefits in engineering education, providing students with interactive and immersive learning experiences. These tools enable students to apply their theoretical knowledge in real-world scenarios, enhancing their understanding and problem-solving skills. A survey was distributed to engineering students in civil engineering courses to gather feedback on the effectiveness of using AI tools, allowing for

Conference Session

Computer-Supported Pedagogy and Assessment

Collection

2024 ASEE Annual Conference & Exposition

Authors

Zulal Sevkli, Miami University

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Computers in Education Division (COED)

wide range of courses across the computer science curriculum and supervised undergraduate and graduate research. ©American Society for Engineering Education, 2024 Assessing the Impact of Open-Resource Access on Student Performance in Computer-Based Examinations Zulal Sevkli Computer Science and Software Engineering Miami University Oxford, OH sevkliaz@miamioh.eduAbstractThis study explored the effects of permitting digital resource access during computer-basedexams in the context of System Programming course. Two

Conference Session

The Best of Computers in Education Division (COED)

Collection

2024 ASEE Annual Conference & Exposition

Authors

John K. Estell, Ohio Northern University; Lisa Graham Robeson, Ohio Northern University; Ye Hong, Ohio Northern University; Stephany Coffman-Wolph, Ohio Northern University

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Diversity

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Computers in Education Division (COED)

differing perspectives based on thedocumented experiences of women along the Oregon and similar Overland Trails in the late1840s and early 1850s. Games were implemented using the Inform programming language,characterized by coding statements taking the form of complete sentences. This approachprovided a natural language syntax environment, making it inclusive for individuals outsidetraditional programming disciplines. To assess the course's effectiveness, pre- and post-activitysurveys with a Diversity, Equity, and Inclusion (DEI) focus were designed and administered. Thesubsequent statistical analysis revealed a significant positive impact, with a large effect sizedemonstrated in raising students' awareness of gender representation

Conference Session

Programming Education 2

Collection

2024 ASEE Annual Conference & Exposition

Authors

Edward Dillon, Morgan State University; Krystal L. Williams, University of Georgia; Ashley Simone Pryor, Morgan State University; Theodore Wimberly Jr., Morgan State University; Mariah McMichael, Morgan State University; Abisola Mercy Arowolaju; Donald Bernard Davis, Morgan State University; Toluwanimi Ayodele, Morgan State University

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Computers in Education Division (COED)

-2013), and a Postdoctoral Researcher at Clemson University (2013-2014) and the University of Florida (2014-2016). His research focuses on human-centered computing, computer science education, social computing, and broadening participation in computing. Dr. Dillon has received >$750k in research funding and awards from external agencies and non-profit organizations, including the National Science Foundation (NSF), the Maryland Pre-Service Computer Science Teacher Education Program (MCCE), and the Collaborative Research Experience for Undergraduates (CREU - CRA-WP). Dr. Dillon currently serves as a Co-PI for the STARS Computing Corps, which recently has been renewed for funding by NSF. He has also conducted a

Conference Session

Cybersecurity Topics

Collection

2024 ASEE Annual Conference & Exposition

Authors

Anyi Liu, Oakland University; Bruce R Maxim, University of Michigan, Dearborn; Xiaohong Yuan, North Carolina A&T State University; Yuan Cheng, Grand Valley State University

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Diversity

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Computers in Education Division (COED)

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

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

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Computers in Education Division (COED)

upper-levelundergraduate and graduate students at the University of Illinois Urbana-Champaign. The datasetcontains a mix of 100 correct and 400 incorrect submissions and underwent an extensivefine-tuning process with OpenAI’s advanced GPT-3.5-turbo-1106 model [15]. Therefore, ourresearch questions include: • RQ1: How can a proof of concept be designed and implemented to assess the feasibility of utilizing a generative AI model for providing semantic error feedback in educational settings, ensuring that the system avoids disclosing correct answers while enhancing the learning experience? • RQ2: How does the feedback from the fine-tuned GPT model differ in specificity and relevance compared to standard GPT models in the

Conference Session

Computers in Education Division (COED) Poster Session

Collection

2024 ASEE Annual Conference & Exposition

Authors

Alexander Hicks, Virginia Polytechnic Institute and State University; Cliff Shaffer, Virginia Polytechnic Institute and State University

Tagged Divisions

Computers in Education Division (COED)

, “A Practical Strategy for Training Graduate CS Teaching Assistants to Provide Effective Feedback,” in Proceedings of the 2023 Conference on Innovation and Technology in Computer Science Education V. 1, (Turku Finland), pp. 285–291, ACM, June 2023.[10] D. Mirza, P. T. Conrad, C. Lloyd, Z. Matni, and A. Gatin, “Undergraduate Teaching Assistants in Computer Science: A Systematic Literature Review,” in Proceedings of the 2019 ACM Conference on International Computing Education Research, (Toronto ON Canada), pp. 31–40, ACM, July 2019.[11] E. Patitsas and P. Belleville, “What can we learn from quantitative teaching assistant evaluations?,” in Proceedings of the Seventeenth Western Canadian Conference on Computing Education

Conference Session

Computer Engineering Topics

Collection

2024 ASEE Annual Conference & Exposition

Authors

Timothy Sellers, Mississippi State University; Tingjun Lei, Mississippi State University; Chaomin Luo, Mississippi State University; Gene Eu Jan; Zhuming Bi, Purdue University, Fort Wayne

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Diversity

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Computers in Education Division (COED)

engineering from the New York Institute of Technology, Old Westbury, NY, USA, in 2016, and the B.S. degree in intelligent transportation engineering from Shanghai Maritime University, Shanghai, China, in 2014. He was Graduate Teaching Assistant for ECE1013 Foundations in ECE, ECE1022 Foundations in Design, ECE4713/6713 Computer Architecture, and ECE4753/6753 Introduction to Robotics at the undergraduate level and as a guest lecturer delivered graduate-level courses, ECE 8743 Advanced Robotics and ECE8833 Computational Intelligence. He received the ECE Best Graduate Researcher Award from the Department of Electrical and Computer Engineering, Mississippi State University in 2023. He received the Research Travel Award

Conference Session

ML and Generative AI Tools and Policies

Collection

2024 ASEE Annual Conference & Exposition

Authors

Alyson G. Eggleston, Pennsylvania State University; Robert J. Rabb P.E., Pennsylvania State University

Tagged Divisions

Computers in Education Division (COED)

) 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

Conference Session

Teaching with ML and Generative AI

Collection

2024 ASEE Annual Conference & Exposition

Authors

Han Kyul Kim, University of Southern California; Aleyeh Roknaldin, University of Southern California; Shriniwas Prakash Nayak, University of Southern California; Xiaoci Zhang, University of Southern California; Muyao Yang, University of Southern California; Marlon Twyman, University of Southern California; Angel Hsing-Chi Hwang, Cornell University; Stephen Lu, University of Southern California

Tagged Divisions

Computers in Education Division (COED)

example,[11] conducted a comprehensive survey of 65 collaboration researchers around the world. Itelicited diverse perspectives on the evolving role of AI in team collaboration, emphasizing theneed for a systematic understanding of team, task, and work practice design in the context ofhuman-AI collaboration. Furthermore, it calls for AI systems that can proactively capture, adjust,and coordinate their responses according to complex contextual nuances, similarly raised by otherrecent works [12, 13, 14, 15, 16].While the present state of AI, including genAI, may not fully embody the ideal envisioned bythese works, it is crucial to recognize that genAI’s generation capability, empowered by largetraining data and pre-trained models, stands as a

Conference Session

Computers in Education Division (COED) Poster Session

Collection

2024 ASEE Annual Conference & Exposition

Authors

David Reeping, University of Cincinnati; Aarohi Shah, University of Cincinnati

Tagged Divisions

Computers in Education Division (COED)

broaderset of educational applications for ChatGPT – including areas like finance, language, medicine,and law – and catalogued several applications of ChatGPT, including identifying student needs,scaling assessment, personalized tutoring, and generating material. Although the findings fromthese reviews – including others such as [14], [15], [16], [17], [18] – can help conceptualize thedifferent possibilities, guidance about how to implement LLM-powered tools like ChatGPT isunderstandably sparse across these literature reviews.The best practices for using LLM-powered tools in educational research are developing as well,specifically how we go about unlocking their proclaimed benefits. The key is determining whatprompts and practices can be used to

Conference Session

Programming Education 2

Collection

2024 ASEE Annual Conference & Exposition

Authors

Tyler James Stump, The Ohio State University; Abbey Darya Kashani Motlagh, The Ohio State University; Krista M Kecskemety, The Ohio State University

Tagged Divisions

Computers in Education Division (COED)

technological age, the need to study and understand computation and the scholarship andteaching employed to prepare the next generation of engineers has become a priority for currenteducation researchers. The National Academies of Sciences, Engineering, and Medicine,reported in a 2018 report by stating, “It is a time for institutions to consider their missions andconstituencies they serve and to determine what role computing should play in the experience,knowledge, and skills of its graduates 2025 and beyond,” [1]. Computing has been identified as anecessary skillset for engineers entering the workforce to employ computational solutions tocomplex global issues. Computing educational researchers have embarked on the journey touncover the evidence-based

Conference Session

Spotlight on Diverse Learners

Collection

2024 ASEE Annual Conference & Exposition

Authors

Minkyung Lee, Pennsylvania State University; Stephanie Cutler, Pennsylvania State University; Sarah E Zappe, Pennsylvania State University; Sam Spiegel, Colorado School of Mines; Ibukun Samuel Osunbunmi, Pennsylvania State University

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Computers in Education Division (COED)

in Science and as Associate Director, Engineering Education Research Center at the University of Pittsburgh; Director of Research & Development for a multimedia company; and as founding Director of the Center for Integrating Research & Learning (CIRL) at the National High Magnetic Field Laboratory. His current efforts focus on innovation of teaching practices in STEM fields and systemic change within higher education.Dr. Ibukun Samuel Osunbunmi, Pennsylvania State University Ibukun Samuel Osunbunmi is an Assistant Research Professor, and Assessment and Instructional Specialist at Pennsylvania State University. He holds a Ph.D. degree in Engineering Education from Utah State University. Also, he has BSc and

Conference Session

Computers in Education Division (COED) Poster Session

Collection

2024 ASEE Annual Conference & Exposition

Authors

Ibukun Samuel Osunbunmi, Pennsylvania State University; Stephanie Cutler, Pennsylvania State University; Viyon Dansu, Florida International University; Yashin Brijmohan, University of Nebraska, Lincoln; Bolaji Ruth Bamidele, Utah State University; Abasiafak Ndifreke Udosen, Purdue University, West Lafayette; Lexy Chiwete Arinze, Purdue University, West Lafayette; Adurangba Victor Oje, University of Georgia; Deborah Moyaki, University of Georgia; Melissa J Hicks, Pennsylvania State University; Bono Po-Jen Shih, Pennsylvania State University

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Diversity

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Computers in Education Division (COED)

, research, and teaching.Considering these challenges, there is an urgent need for empirical studies to assess the impact ofGAI on engineering learning experiences to address the potential challenges and concerns relatedto their implementation. This study aims to inform the field about the best practices forintegrating GAI tools into engineering education pedagogy and assessment.Purpose of this studyThis work-in-progress paper aims to describe our efforts to explore the impact of integrating GAIas a tool for enhancing engineering education. In this paper, we will discuss the methodology weplan to use to assess the impact of GAI tools on engineering learning experiences, including theselection of participants, data collection methods, and analysis

Conference Session

Computers in Education Division (COED) Poster Session

Collection

2024 ASEE Annual Conference & Exposition

Authors

Lisa Cullington, Sacred Heart University; Mary V Villani, Farmingdale State College, SUNY, New York; Nur Dean, Farmingdale State College, SUNY, New York; Moaath Alrajab, Farmingdale State College, SUNY, New York; Arthur Hoskey, Farmingdale State College SUNY, New York; Ilknur Aydin, Farmingdale State College, SUNY, New York

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Diversity

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Computers in Education Division (COED)

students in the United States.Despite this growing interest, retention and graduation rates are a concern for many regional publicuniversities such as Farmingdale State College (FSC). Educational researchers have demonstratedthe benefits of increasing student sense of belonging (SoB) and academic self-concept (ASC) onacademic outcomes. This study explores the interaction between implementing collaborativelearning techniques (CoLT) in a CSC 101 Introduction to Computing course with students’ SoBand ASC. Given the social constructivist perspective that frames CoLTs and these techniques’ability to engage students authentically in course content, the implementation of CoLTs ishypothesized to positively impact students’ SoB and ASC. Students in the