Conference Session

DSA Technical Session 7

Collection

2024 ASEE Annual Conference & Exposition

Authors

Tony Maricic, New York University Tandon School of Engineering; Nisha Ramanna, New York University Tandon School of Engineering; Alison Reed, New York University Tandon School of Engineering; Rui Li, New York University; Jack Yang, New York University Tandon School of Engineering

Tagged Topics

Data Science & Analytics Constituent Committee (DSA)

Paper ID #41462An Interactive Platform for Team-based Learning Using Machine LearningApproachTony Maricic, New York University Tandon School of EngineeringNisha Ramanna, New York University Tandon School of Engineering Nisha Ramanna is a student at New York University, pursuing her Bachelor’s and Master’s in Computer Science with a concentration in Machine Learning and Artificial Intelligence. She is passionate about all areas of Machine Learning, including Natural Language Processing.Alison Reed, New York University Tandon School of EngineeringDr. Rui Li, New York University Dr. Li earned his master’s degree in Chemical

Conference Session

DSA Technical Session 8

Collection

2024 ASEE Annual Conference & Exposition

Authors

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

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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 3

Collection

2024 ASEE Annual Conference & Exposition

Authors

Aidan Kenny, Northeastern University; Andrew L Gillen, Northeastern University

Tagged Topics

Data Science & Analytics Constituent Committee (DSA), Diversity

developing creative data visualizations, it is important to keep in mind bestpractices in accessible design such as using high contrast colors and alt text for digital works.This paper is just a starting point for exploring more compelling data visualizations. More workneeds to be done to develop these for a variety of potential audiences.ConclusionThe presented case studies explore the critical role of creative data visualization in enhancing theunderstanding and impact of various aspects of engineering education. It is important andbeneficial to look beyond traditional data representation methods and towards more innovative,visually appealing, and creative approaches. The first case study addressed the issue of genderdisparity in engineering. Use

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

minimum required by a standard undergraduate degree (generally120 credit hours), or as the superfluous credits relative to the student’s specific degree program atgraduation [8, 15]. In this paper, we provide a new definition of excess credit hours (introduced byus in [13]) that takes into consideration the applicability(usability) of credits towards the degreerequirements (refer to Section 3). The more commonly used definition of excess credits used sofar in this Section will be referred to as extra credits from here on in this paper. It is clear thatexcess credits are a subset of extra credits. With this in mind, our primary objective in this paperis to explain the extra credit accumulation pattern of undergraduate engineering students

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)

. Pilarz, and M. Stains, “Research-based implementation of peer instruction: A literature review,” CBE—Life Sci. Educ., vol. 14, no. 1, p. es3, Mar. 2015, doi: 10.1187/cbe.14-11-0198.[7] N. Yannier et al., “Active learning: ‘Hands-on’ meets ‘minds-on,’” Science, vol. 374, no. 6563, pp. 26–30, Oct. 2021, doi: 10.1126/science.abj9957.[8] S. Freeman et al., “Active learning increases student performance in science, engineering, and mathematics,” Proc. Natl. Acad. Sci. U. S. A., vol. 111, no. 23, pp. 8410–8415, Jun. 2014, doi: 10.1073/pnas.1319030111.[9] N. Joshi, S.-K. Lau, M. F. Pang, and S. S. Y. Lau, “Clickers in class: Fostering higher cognitive thinking using ConcepTests in a large undergraduate class

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 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 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)

Paper ID #42646Enhancing Academic Pathways: A Data-Driven Approach to Reducing CurriculumComplexity and Improving Graduation Rates in Higher EducationDr. 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 tools that aim to

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)

Paper ID #42410Credit-Hour Analysis of Undergraduate Students Using Sequence DataTushar Ojha, University of New Mexico Tushar Ojha is a graduate (PhD) student in the Department of Electrical and Computer Engineering at the University of New Mexico (UNM). His work is focused on researching and developing data driven methods that are tailored to analyzing/predicting outcomes in the higher education space. He works as a Data Scientist for the Institute of Design & Innovation (IDI), UNM.Don Hush, University of New Mexico Dr. Hush has worked as a technical staff member at Sandia National Laboratories, a tenure-track