Conference Session

DSA Technical Session 5

Collection

2024 ASEE Annual Conference & Exposition

Authors

Mehmet Ergezer, Wentworth Institute of Technology; Mark Mixer, Wentworth Institute of Technology; Weijie Pang, Wentworth Institute of Technology

Tagged Topics

Data Science & Analytics Constituent Committee (DSA), Diversity

Paper ID #41792Bridging Theory and Practice: Building an Inclusive Undergraduate Data-ScienceProgramDr. Mehmet Ergezer, Wentworth Institute of Technology Mehmet Ergezer holds a Doctor of Engineering degree from the Department of Electrical and Computer Engineering at Cleveland State University, Cleveland, OH. Currently serving as an Associate Professor of Computing and Data Science at Wentworth Institute of Technology in Boston, MA, Dr. Ergezer’s expertise lies at the intersection of embedded systems and computational intelligence. He has co-authored publications on artificial intelligence and computer science education

Conference Session

DSA Technical Session 8

Collection

2024 ASEE Annual Conference & Exposition

Authors

Amirreza Mehrabi, Purdue Engineering Education; Jason Morphew, Purdue University, West Lafayette

Tagged Topics

Data Science & Analytics Constituent Committee (DSA)

Paper ID #42426Investigating and predicting the Cognitive Fatigue Threshold as a Factor ofPerformance Reduction in AssessmentMr. Amirreza Mehrabi, Purdue Engineering Education I am Amirreza Mehrabi, a Ph.D. student in Engineering Education at Purdue University, West Lafayette. Now I am working in computer adaptive testing (CAT) enhancement with AI and analyzing big data with machine learning (ML) under Prof. J. W. Morphew at the ENE department. My master’s was in engineering education at UNESCO chair on Engineering Education at the University of Tehran. I pursue Human adaptation to technology and modeling human behavior

Conference Session

DSA Technical Session 5

Collection

2024 ASEE Annual Conference & Exposition

Authors

Duo Li, Shenyang Institute of Technology; Elizabeth Milonas, New York City College of Technology; Qiping Zhang, Long Island University

Tagged Topics

Data Science & Analytics Constituent Committee (DSA)

University, where she also serves as director of the Usability Lab. Dr. Zhang holds a Ph.D. and an M.S. in informatio ©American Society for Engineering Education, 2024 Preparing Undergraduate Data Scientists for Success in the Workplace: Aligning Competencies with Job Requirements1. Introduction The increased use of Data Science technologies, particularly artificial intelligence andmachine learning has caused an increase in demand for skilled Data Science professionals[1,2,3]. This demand is driven by the rising dependence of businesses on these technologies toinform strategic decisions [1,2,3]. The Data Science domain is multidisciplinary, encompassingskill sets, including statistics

Conference Session

DSA Technical Session 3

Collection

2024 ASEE Annual Conference & Exposition

Authors

Tushar Ojha, University of New Mexico; Don Hush, University of New Mexico

Tagged Topics

Data Science & Analytics Constituent Committee (DSA), Diversity

-transfer-students-earn-bachelors-degrees- excess-credits.pdf.[10] J. J. Giesey and B. Manhire. An analysis of bsee degree completion time at ohio university. Journal of Engineering Education, 92(3):275–280, 2003.[11] S. K. Hargrove and D. Ding. An Analysis of B.S.I.E. Degree Completion Time at Morgan State University. In International Conference on Engineering Education. International Network for Engineering Education and Research, October 2004.[12] M. M. Hossain and M. G Robinson. How to motivate us students to pursue stem (science, technology, engineering and mathematics) careers. Online Submission, 2012.[13] D. R. Hush, E. S. Lopez, W. Al-Doroubi, T. Ojha, B. Santos, and K. Warne. Analyzing student credits. 2022

Conference Session

DSA Technical Session 4

Collection

2024 ASEE Annual Conference & Exposition

Authors

Duncan Davis, Northeastern University; Nicole Alexandra Batrouny, Northeastern Univeristy; Adetoun Yeaman, Northeastern University

Tagged Topics

Data Science & Analytics Constituent Committee (DSA), Diversity

Paper ID #41739Unfettered ChatGPT Access in First-Year Engineering: Student Usage &PerceptionsDr. Duncan Davis, Northeastern University Duncan Davis is an Associate Teaching Professor in First Year Engineering. His research focuses on using gamification to convey course content in first year classes. He is particularly interested in using the construction of Escape Rooms to teach Engineering Principles.Dr. Nicole Alexandra Batrouny, Northeastern Univeristy Nicole Batrouny is an Assistant Teaching Professor in First Year Engineering at Northeastern University. Her engineering education research interests include the

Conference Session

DSA Technical Session 5

Collection

2024 ASEE Annual Conference & Exposition

Authors

Nicolas Leger, Florida International University; Maimuna Begum Kali, Florida International University; Stephanie Jill Lunn, Florida International University

Tagged Topics

Data Science & Analytics Constituent Committee (DSA)

Engineering Entrepreneurship.Maimuna Begum Kali, Florida International University Maimuna Begum Kali is a Ph.D. candidate in the Engineering and Computing Education program at the School of Universal Computing, Construction, and Engineering Education (SUCCEED) at Florida International University (FIU). She earned her B.Sc. in Computer Science and Engineering from Bangladesh University of Engineering and Technology (BUET). Kali’s research interests center on exploring the experiences of marginalized engineering students, with a particular focus on their hidden identity, mental health, and wellbeing. Her work aims to enhance inclusivity and diversity in engineering education, contributing to the larger body of research in

Conference Session

DSA Technical Session 8

Collection

2024 ASEE Annual Conference & Exposition

Authors

Paula Francisca Larrondo, Queen's University; Brian M Frank P.Eng., Queen's University; Julian Ortiz, Queen's University

Tagged Topics

Data Science & Analytics Constituent Committee (DSA)

(NLP) technologies, through the use of artificialintelligence (AI) agents and Large Language Models (LLM), have already provided significantadvantages in the holistic assessment of high-order features such as argumentation, use ofevidence or scientific thinking [4-6]. With the evolution of Automated Feedback Systems (AFS)[7-9] and, more recently, the release of Open AI’s ChatGPT, LLMs have become commonplacein higher education among students and instructors [10, 11]. The emergence of LLMs in higherand secondary education has triggered an influx of publications on the opportunities andchallenges of incorporating these technologies in instruction and evaluation [10, 12, 13].However, the unique nature of engineering design problems, characterized

Conference Session

DSA Technical Session 7

Collection

2024 ASEE Annual Conference & Exposition

Authors

Harpreet Auby, Tufts University; Namrata Shivagunde, University of Massachusetts, Lowell; Anna Rumshisky, University of Massachusetts, Lowell; Milo Koretsky, Tufts University

Tagged Topics

Data Science & Analytics Constituent Committee (DSA)

. 11, pp. 1747–1765, Jul. 2016, doi: 10.1080/09500693.2016.1214303.[17] M. D. Koretsky and A. J. Magana, “Using technology to enhance learning and engagement in engineering,” Adv. Eng. Educ., 2019, Accessed: Oct. 21, 2023. [Online]. Available: https://eric.ed.gov/?id=EJ1220296[18] R. Gao, H. E. Merzdorf, S. Anwar, M. C. Hipwell, and A. R. Srinivasa, “Automatic assessment of text-based responses in post-secondary education: A systematic review,” Comput. Educ. Artif. Intell., vol. 6, p. 100206, Jun. 2024, doi: 10.1016/j.caeai.2024.100206.[19] X. Zhai, Y. Yin, J. W. Pellegrino, K. C. Haudek, and L. Shi, “Applying machine learning in science assessment: a systematic review,” Stud. Sci. Educ., vol. 56, no

Conference Session

DSA Technical Session 7

Collection

2024 ASEE Annual Conference & Exposition

Authors

Isil Anakok, Virginia Polytechnic Institute and State University; Kai Jun Chew, Embry-Riddle Aeronautical University, Daytona Beach; Holly M Matusovich, Virginia Polytechnic Institute and State University; Andrew Katz, Virginia Polytechnic Institute and State University

Tagged Topics

Data Science & Analytics Constituent Committee (DSA)

1 1 NA 1Table 3 shows participants’ responses based on their home departments. The analysis aimed toidentify potential department-specific responses to the integration and perception of GAI ineducational practices. Focusing on the departments that had the first three highest numbers oftotal responses, participants from Mechanical Engineering recognized the influence of GAI withalmost 32%. Electrical Engineering exhibited that 29% of faculty members indicated an impacton their thinking on assessment practices. Computer Science, a discipline inherently intertwinedwith technological advancements, showed around 33% of faculty members acknowledging theimpact of GAI.Table 3. The number of the participants

Conference Session

DSA Technical Session 2

Collection

2024 ASEE Annual Conference & Exposition

Authors

Ben D Radhakrishnan, National University; James Jay Jaurez, National University; Nelson Altamirano, National University

Tagged Topics

Data Science & Analytics Constituent Committee (DSA), Diversity

Paper ID #42783Application of Data Analysis and Visualization Tools for U.S. Renewable SolarEnergy Generation, Its Sustainability Benefits, and Teaching In EngineeringCurriculumMr. Ben D Radhakrishnan, National University Ben D Radhakrishnan is a Professor of Practice, currently a full time Faculty in the Department of Engineering, School of Technology and Engineering, National University, San Diego, California, USA. He is the Academic Program Director for MS Engineering Management program. He develops and teaches Engineering courses in different programs including engineering and business management schools. His research

Conference Session

DSA Technical Session 6

Collection

2024 ASEE Annual Conference & Exposition

Authors

Kristina A Manasil, The University of Arizona; Gregory L. Heileman, The University of Arizona; Bhavya Sharma, The University of Arizona; Ahmad Slim, The University of Arizona; Aryan Ajay Pathare, The University of Arizona; Husain Al Yusuf, The University of Arizona; Roxana Sharifi, The University of Arizona; Rohit Hemaraja, The University of Arizona; Melika Akbarsharifi, The University of Arizona

Tagged Topics

Data Science & Analytics Constituent Committee (DSA)

University of New Mexico and brings over fifteen years of professional experience as a technology engineer, including significant roles in cloud computing and infrastructure development at a big technologies company and financial services industry.Roxana Sharifi, The University of Arizona ©American Society for Engineering Education, 2024 Paper ID #42637 Roxana Sharifi is a second-year master’s student in Electrical and Computer Engineering at the University of Arizona, where she also serves as a Graduate Research Assistant in the Curricular Analytics Lab. She holds a bachelor’s degree in Software

Conference Session

DSA Technical Session 2

Collection

2024 ASEE Annual Conference & Exposition

Authors

Xiang Zhao, Alabama A&M University; Mebougna L. Drabo, Alabama A&M University

Tagged Topics

Data Science & Analytics Constituent Committee (DSA), Diversity

include STEM education, Additive Manufacturing, Thermoelectric Devices for Energy Harvesting, Digital Twinning Technology, Nuclear Radiation Detectors, Nuclear Security and Safety, Small Nuclear Modular Reactors (SMR), Material Characterization (X-ray Photoelectron Spectroscopy & Infrared Microscopy), Nanotechnology, Data Analytics and Visualization, Biofuels Applications, Computational Fluid Dynamics analysis, Heat Transfer, Energy Conservation in building, and Multi Fuel Optimization. ©American Society for Engineering Education, 2024 2024 ASEE Annual Conference and Exposition Integrating Data Analytics into the Pipeline Building toward a

Conference Session

DSA Technical Session 8

Collection

2024 ASEE Annual Conference & Exposition

Authors

Neha Kardam, University of Washington; Denise Wilson, University of Washington; Sep Makhsous, University of Washington

Tagged Topics

Data Science & Analytics Constituent Committee (DSA)

engineering education ashighlighted by the accreditation board for engineering and technology (ABET) student outcomes[34]. Table 2. Topics and Themes representing Student Responses regarding TA Support Most Frequently Occurring Words associated with Each Topic Topic 1 Topic 2 Topic 3 Topic 4 problems, quiz, lecture, hours, office, available, questions, answer, ask, lab, labs, extra, work, examples, time, times, hour, discussion, emails, explain, things, time, homework, time, feedback, zoom, many, available, question, online, especially, practice, clear, example assignments email, answering, online people

Conference Session

DSA Technical Session 6

Collection

2024 ASEE Annual Conference & Exposition

Authors

Marjan Eggermont, University of Calgary

Tagged Topics

Data Science & Analytics Constituent Committee (DSA), Diversity

complementary studies course. On average the class has 25 students.We start the class with a discussion of the short article What Art Unveils by Alva Noë whichusually allows us to find aspects we agree on so that we have a common understanding of art inthe course. ‘Artists make stuff’ – we were able to agree on that. Noë’s hypothesis is “that artistsmake stuff not because the stuff they make is special in itself, but because making stuff is specialfor us. Making activities — technology, for short — constitute us as a species. Artists make stuffbecause in doing so they reveal something deep and important about our nature, indeed, … aboutour biological nature [4].” He continues the article that ‘art makes things strange’: take a groupof engineering

Conference Session

DSA Technical Session 4

Collection

2024 ASEE Annual Conference & Exposition

Authors

Fengbo Ma, Northeastern University; Xuemin Jin, Northeastern University

Tagged Topics

Data Science & Analytics Constituent Committee (DSA)

. ©American Society for Engineering Education, 2024 Continuous Speech Emotion Recognition from Audio Segments with Supervised Learning and Reinforcement Learning Approaches1. IntroductionEmotion plays an important role in communications, conveying essential information beyondwords. This is particularly evident in enhancing Human-Computer Interaction (HCI) and SpeechEmotion Recognition (SER). The latter is a specialized area within Automatic SpeechRecognition (ASR) and focuses on identifying human emotions, which is crucial to advancingHCI. Recognizing emotions in speech, such as anger or joy, allows AI systems to interpret andrespond more effectively to human expressions.Emotion recognition technology can be integrated into engineering

Conference Session

DSA Technical Session 7

Collection

2024 ASEE Annual Conference & Exposition

Authors

Abdulrahman Alsharif, Virginia Polytechnic Institute and State University; Andrew Katz, Virginia Polytechnic Institute and State University

Tagged Topics

Data Science & Analytics Constituent Committee (DSA), Diversity

Paper ID #41721From Manual Coding to Machine Understanding: Students’ Feedback AnalysisMr. Abdulrahman Alsharif, Virginia Polytechnic Institute and State University Abdulrahman M. Alsharif is a research assistant for the Engineering Education Department and a PhD candidate at Virginia Tech.Dr. Andrew Katz, Virginia Polytechnic Institute and State University Andrew Katz is an assistant professor in the Department of Engineering Education at Virginia Tech. He leads the Improving Decisions in Engineering Education Agents and Systems (IDEEAS) Lab. ©American Society for Engineering Education, 2024From Manual

Conference Session

DSA Technical Session 5

Collection

2024 ASEE Annual Conference & Exposition

Authors

Safia Malallah, Kansas State University; Ejiro U Osiobe, Baker University; Zahraa Marafie, Kuwait University; Patricia Henriquez-Coronel; Lior Shamir, Kansas State University; Ella Lucille Carlson, Kansas State University; Joshua Levi Weese, Kansas State University

Tagged Topics

Data Science & Analytics Constituent Committee (DSA)

, Baker University .Zahraa Marafie, Kuwait UniversityPatricia Henriquez-CoronelLior Shamir, Kansas State University Associate professor of computer science at Kansas State University.Ella Lucille Carlson, Kansas State UniversityJoshua Levi Weese, Kansas State University Dr. Josh Weese is a Teaching Assistant Professor at Kansas State University in the department of Computer Science. Dr. Weese joined K-State as faculty in the Fall of 2017. He has expertise in data science, software engineering, web technologies, computer science education research, and primary and secondary outreach programs. Dr. Weese has been a highly active member in advocating for computer science education in Kansas including PK-12 model standards

Conference Session

DSA Technical Session 4

Collection

2024 ASEE Annual Conference & Exposition

Authors

Galen I. Papkov, Florida Gulf Coast University; Jiehong Liao, Florida Gulf Coast University

Tagged Topics

Data Science & Analytics Constituent Committee (DSA), Diversity

Millennium Scholars. Before joining FGCU, she was a visiting Assistant Professor of Biotechnology in the Division of Science and Technology at the United International College (UIC) in Zhuhai China. She has trained with ASCE’s Excellence in Civil Engineering Education (ExCEEd) initiative, been exploring and applying evidence-based strategies for instruction, and is a proponent of Learning Assistants (LAs). Her scholarship of teaching and learning interests are in motivation and mindset, teamwork and collaboration, and learning through failure and reflection. Her bioengineering research interests and collaborations are in the areas of biomaterials, cellular microenvironments, and tissue engineering and regenerative

Conference Session

DSA Technical Session 1

Collection

2024 ASEE Annual Conference & Exposition

Authors

Ahmad Slim, The University of Arizona; Gregory L. Heileman, The University of Arizona; Husain Al Yusuf, The University of Arizona; Yiming Zhang, The University of Arizona; Asma Wasfi; Mohammad Hayajneh; Bisni Fahad Mon, United Arab Emirates University; Ameer Slim, University of New Mexico

Tagged Topics

Data Science & Analytics Constituent Committee (DSA)

on applying machine learning and data analytics to higher education, aiming to enhance student outcomes and optimize educational processes. Husain Al Yusuf holds an M.Sc in Computer Engineering from the University of New Mexico and brings over fifteen years of professional experience as a technology engineer, including significant roles in cloud computing and infrastructure development at a big technologies company and financial services industry.Dr. Yiming Zhang, The University of Arizona Yiming Zhang completed his doctoral degree in Electrical and Computer Engineering from the University of Arizona in 2023. His research focuses on machine learning, data analytics, and optimization in the application of

Conference Session

DSA Technical Session 6

Collection

2024 ASEE Annual Conference & Exposition

Authors

Smitesh Bakrania, Rowan University

Tagged Topics

Data Science & Analytics Constituent Committee (DSA)

Paper ID #41136The Value and Instructor Perceptions of Learning Analytics for Small ClassesDr. Smitesh Bakrania, Rowan University Dr. Smitesh Bakrania is an associate professor in Mechanical Engineering at Rowan University. He received his Ph.D. from University of Michigan in 2008 and his B.S. from Union College in 2003. His technical focus area is nanomaterials research. He is primarily involved in educational research with educational app development and instructional tools to engage students, including online learning and instructional video production. ©American Society for Engineering Education

Conference Session

DSA Technical Session 6

Collection

2024 ASEE Annual Conference & Exposition

Authors

tonghui xu, University of Massachusetts, Lowell; Hsien-Yuan Hsu, University of Massachusetts, Lowell

Tagged Topics

Data Science & Analytics Constituent Committee (DSA)

of King Saud University - Computer and Information Sciences. https://doi.org/10.1016/j.jksuci.2019.06.012[12] Chaudhury, P., & Tripathy, H. K. (2017). “An empirical study on attribute selection of student performance prediction model,” International Journal of Learning Technology, 12(3), 241-252.[13] Tan, L., Main, J. B., & Darolia, R. (2021). “Using random forest analysis to identify student demographic and high school‐level factors that predict college engineering major choice,” Journal of Engineering Education, 110(3), 572-593.[14] Kursa, M. B., & Rudnicki, W. R. (2010). “Feature selection with the Boruta package,” Journal of statistical software, 36, 1-13.[15] Ingels, S. J., Pratt, D. J., Wilson, D., Burns, L. J

Conference Session

DSA Technical Session 7

Collection

2024 ASEE Annual Conference & Exposition

Authors

Saquib Ahmed, The State University of New York Buffalo State University

Tagged Topics

Data Science & Analytics Constituent Committee (DSA)

green channel correlation method for versatile identification.Miah Abdullah Sahriar1†, Mohd. Rakibul Hasan Abed1†, Ratchanok Somphonsane2, Houk Jang3,Chang-Yong Nam3, Saquib Ahmed5,6*1 Department of Materials and Metallurgical Engineering (MME), Bangladesh University ofEngineering and Technology (BUET), East Campus, Dhaka-1000, Bangladesh2 Department of Physics, School of Science, King Mongkut’s Institute of TechnologyLadkrabang, Bangkok 10520, Thailand3 Center for Functional Nanomaterials, Brookhaven National Laboratory, Upton, New York11973, USA5 Department of Mechanical Engineering Technology, SUNY – Buffalo State University, 1300Elmwood Avenue, Buffalo, NY 14222, USACenter for Integrated Studies in Nanoscience and Nanotechnology

Conference Session

DSA Technical Session 5

Collection

2024 ASEE Annual Conference & Exposition

Authors

Karl D. Schubert FIET, University of Arkansas; Shantel Romer, University of Arkansas; Stephen R. Addison, IEEE Educational Activities; Tina D Moore; Laura J Berry, North Arkansas College; Jennifer Marie Fowler, Arkansas State University; Lee Shoultz, University of Arkansas; Christine C Davis

Tagged Topics

Data Science & Analytics Constituent Committee (DSA)

Paper ID #42697Envisioning and Realizing a Statewide Data Science EcosystemDr. Karl D. Schubert FIET, University of Arkansas Dr. Karl D. Schubert is a Professor of Practice and serves as the Associate Director for the Data Science Program at the University of Arkansas College of Engineering, the Sam M. Walton College of Business, and the Fulbright College of Arts & Sciences.Shantel Romer, University of ArkansasStephen R. Addison, IEEE Educational ActivitiesTina D MooreLaura J Berry, North Arkansas CollegeJennifer Marie Fowler, Arkansas State UniversityLee Shoultz, University of ArkansasChristine C Davis

Conference Session

DSA Technical Session 3

Collection

2024 ASEE Annual Conference & Exposition

Authors

Yiming Zhang, The University of Arizona; Gregory L. Heileman, The University of Arizona; Ahmad Slim, The University of Arizona; Husain Al Yusuf, The University of Arizona

Tagged Topics

Data Science & Analytics Constituent Committee (DSA)

outcomes and optimize educational processes. Husain Al Yusuf holds an M.Sc in Computer Engineering from the University of New Mexico and brings over fifteen years of professional experience as a technology engineer, including significant roles in cloud computing and infrastructure development at a big technologies company and financial services industry. ©American Society for Engineering Education, 2024 Optimizing Transfer Pathways in Higher Education Yiming Zhang, Gregory L. Heileman, and Ahmad Slim {yimingzhang1, heileman, ahslim}@arizona.edu Department of Electrical & Computer Engineering

Conference Session

DSA Technical Session 6

Collection

2024 ASEE Annual Conference & Exposition

Authors

Emily Nutwell, The Ohio State University; Thomas Bihari, The Ohio State University; Thomas Metzger, The Ohio State University

Tagged Topics

Data Science & Analytics Constituent Committee (DSA), Diversity

computer science track in the interdisciplinary curriculum, wherethe goal is to provide a foundational presentation of computer science principles within thecontext of an interdisciplinary graduate program. The courses are designed to support learners inidentifying common data structures and sources, using information technology and relevantprogramming environments to convey and retrieve information, and identifying processes andmechanisms commonly used to retrieve, assess, re-engineer, manipulate, and visualize data. Thediverse backgrounds of the learners make this an interesting challenge for curriculum designers.How can a professional master’s degree successfully introduce foundational computer scienceconcepts for adult learners from diverse

Conference Session

DSA Technical Session 1

Collection

2024 ASEE Annual Conference & Exposition

Authors

Ahmad Slim, The University of Arizona; Gregory L. Heileman, The University of Arizona; Melika Akbarsharifi, The University of Arizona; Kristina A Manasil, The University of Arizona; Ameer Slim, University of New Mexico

Tagged Topics

Data Science & Analytics Constituent Committee (DSA), Diversity

Paper ID #44170Causal Inference Networks: Unraveling the Complex Relationships BetweenCurriculum Complexity, Student Characteristics, and Performance in HigherEducationDr. Ahmad Slim, The University of Arizona Dr. Ahmad Slim is a PostDoc researcher at the University of Arizona, where he specializes in educational data mining and machine learning. With a Ph.D. in Computer Engineering from the University of New Mexico, he leads initiatives to develop analytics solutions that support strategic decision-making in academic and administrative domains. His work includes the creation of predictive models and data visualization