Conference Session

DSA Technical Session 8

Collection

2024 ASEE Annual Conference & Exposition

Authors

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

Tagged Topics

Data Science & Analytics Constituent Committee (DSA)

Internal Review Board (IRB) under the code STUDY00000378.The study recruited undergraduate students from 21 courses in mechanical and electrical engineering,but the researchers did not engage directly with the students. All participants were informed that theirresponses would be kept confidential. Additional academic incentives, in the form of extra credit,were provided to students to support increased survey participation and all surveys were conductedelectronically.Data AnalysisRaw data from student responses was initially processed using Term Frequency-Inverse DocumentFrequency (TF-IDF) Vectorizer to convert the unstructured data into structured format [12]. TheTF-IDF Vectorizer provided by Sklearn.org calculates a score that reflects the

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

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Data Science & Analytics Constituent Committee (DSA)

passionate about teaching and research, and he strives to produce knowledge that informs better teaching. His research intersects assessment and evaluation, motivation, and equity. His research goal is to promote engineering as a way to advance social justice causes.Dr. Holly M Matusovich, Virginia Polytechnic Institute and State University Dr. Holly Matusovich is the Associate Dean for Graduate and Professional Studies in the College of Engineering at Virginia Tech and a Professor in the Department of Engineering Education where she has also served in key leadership positions. Dr. Matusovich is recognized for her research and leadership related to graduate student mentoring and faculty development. She won the Hokie

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

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)

Paper ID #44069A Comparative Analysis of Natural Language Processing Techniques for AnalyzingStudent Feedback about TA SupportNeha Kardam, University of Washington Neha Kardam is a PhD candidate in Electrical and Computer Engineering at the University of Washington, Seattle. She is an interdisciplinary researcher with experience in statistics, predictive analytics, mixed methods research, and machine learning techniques in data-driven research.Dr. Denise Wilson, University of Washington Denise Wilson is a professor and associate chair of diversity, equity, and inclusion in electrical and computer engineering at the

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)

curricular efficiency, curricular equity, and student progression.Bhavya Sharma, The University of ArizonaAhmad 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 improve student recruitment, retention, and success metrics. Dr. Slim’s scholarly contributions include numerous articles on the application of data science

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)

the institution, allowing for athorough understanding of their existing academic offerings. Our Graduate Research Assistantcollaborates with the various academic representatives to design a program that integrates theirinstitution’s offerings into the statewide ecosystem.As part of this collaborative effort, a preliminary course equivalency assessment is conducted.This involves an examination and comparison of the courses already established at theinstitutions. This initial evaluation allows us to identify potential areas of alignment and establishthe groundwork for the integration of those courses into the program.Through these engagements, we not only provide valuable insights into the benefits of optinginto the program but also actively

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

initial stage of the research involved a literature review to gain more understanding of datavisualization techniques, engineering education topics, and visual design principles. Academicdatabases, journals, and research papers were consulted to develop case studies that investigatedrelevant engineering education topics. While exploring data visualization methods, we made noteof techniques that resulted in more creative final products. Simultaneously, publicly availableengineering education data was procured from sources such as the National Center for EducationStatistics (NCES). Engineering education is a colorful, dynamic, and deep field that addresses awide range of topics. Thus, data was narrowed to focus on insights into student demographics

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)

visualizations to comprehend team dynamics and performanceeffectively.Virtual AssistantTo optimize ease of use, we initially decided to create a chatbot user interface. Our goal was toallow users to prompt the chatbot with a question about a project or student and, in response, thechatbot would identify and return the relevant information. The chatbot classifies the intent of auser prompt using a Tensorflow Sequential model. The neural network is composed of oneembedding layer, a global average pooling layer, and 3 dense layers (the first two have 16 nodesand use Relu as an activation function, the output layer has a node for each possible user intentand uses a softmax activation function). After intent classification, we use NLTK to performName Entity

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)

industry recommendations. Data saturation determined the depth of the review.The third stage aimed to establish a coherent sequence of data science concepts within thesurvey, satisfying interdisciplinary needs. This involved identifying the appropriate datascience cycle to guide the arrangement of concepts. Finally, the survey questions were craftedin stage four, drawing from the intersection of the data science cycle steps and the necessaryknowledge to fulfill them. The research implementation phase spanned 8 weeks. Initially, thesurvey underwent review and modification based on feedback from experts in statistics,computer science, and business analytics. Subsequently, the survey was distributed online to163 participants enrolled in data science

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

and holds consumer electronics patents in the USA and Europe. Beyond his technical pursuits, Dr. Ergezer is deeply committed to fostering intercultural competence among undergraduate students. He has spearheaded initiatives to broaden participation in artificial intelligence, including co-founding and co-chairing the AAAI Undergraduate Consortium. Additionally, he has led transformative study abroad programs, such as a semester-long immersion experience in Berlin, Germany, providing students with invaluable global perspectives.Dr. Mark Mixer, Wentworth Institute of Technology Mark Mixer is an associate professor in the School of Computing and Data Science at Wentworth Institute of Technology. After completing a

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

accelerating and scaling up the coding process.The models can extract high-level insights that may be difficult for human analysts to see whendealing with thousands of individual responses. However, the terminology distinctionsemphasize the importance of incorporating human oversight and validation into the analysisprocess. The GAI outputs are viewed as an initial pass to rapidly acquire potential themes, but toproperly refine how the themes are framed, and named, and how to hierarchically organize thethemes to best fit the research context and goals. In this process feedback and revision from anexpert is still required. With this human-in-the-loop step, there is a chance that importantnuances could be recovered or themes could be over-generalized [19

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

Paper ID #41074Integrating Data Science into the Pipeline Building Toward a Diversified Workforcein Nuclear Energy and SecurityDr. Xiang Zhao, Alabama A&M University Dr. Xiang (Susie) Zhao, Professor in the Department of Electrical Engineering and Computer Science at the Alabama A&M University, has over 20 years of teaching experience in traditional on-campus settings or online format at several universities in US and aboard. Her teaching and research interests include programming languages, high performance algorithm design, data science, and evidence-based STEM teaching pedagogies. Her recent research work has been

Conference Session

DSA Technical Session 2

Collection

2024 ASEE Annual Conference & Exposition

Authors

Emma Fox, Franklin W. Olin College of Engineering; Zachary del Rosario, Olin College of Engineering

Tagged Topics

Data Science & Analytics Constituent Committee (DSA)

inference. For instance, consider this passage from an introductorystatistics textbook, Theoretically, the true score is the mean that would be approached as the number of trials increases indefinitely. An individual response time can be thought of as being composed of two parts: the true score and the error of measurement. [10]In this example, the mean is reified as a “true value;” the goal of inference is then to rejectvariations from the mean. This particular reification of the mean will enter into our data analysis,detailed below.Given this background, our research questions are: 1. How do engineers interpret variability if it is described as “error”? Do they associate “error” with real/erroneous sources, or some other

Conference Session

DSA Technical Session 1

Collection

2024 ASEE Annual Conference & Exposition

Authors

Betul Bilgin, The University of Illinois at Chicago; Naomi Groza, The University of Illinois at Chicago

Tagged Topics

Data Science & Analytics Constituent Committee (DSA), Diversity

concepts, their recognition of data science's relevance in chemical engineering, and theirreadiness to engage with data science tools and techniques. Students, both seniors, juniors andsophomores in CHE, participated in the interviews. The study's findings reveal that, despitelimited exposure within their coursework, most students acknowledge the growing significanceof data science in the chemical engineering field. The majority express a keen interest inexpanding their knowledge of data science and are receptive to its integration into their academicand future career paths.Moreover, this research identifies barriers to the incorporation of data science in the CHEcurriculum, such as the need for additional resources and training for both students

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 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 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)

quick, inexpensive, and effective means of non-destructively identifying graphene layers from optical images. Its versatility and performanceunder varying conditions make it a promising approach for practical applications in grapheneresearch. Additionally, and critically: the methods highlighted in this research can be utilizedacross a multitude of disciplines (from bioengineering to electrical, materials, nanoengineering,etc.) for one of the most fundamental areas of experimental research in STEM at theundergraduate level: accurately identifying multiple systems from optical images. A broad,relevant, and timely curriculum can be built around data analytics and application to solvingSTEM problems – including components such as data mining

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)

an M.Sc. in Mining Engineering (Geostatistics) from the University of Alberta (Canada).Prof. Brian M Frank P.Eng., Queen’s University Brian Frank is the DuPont Canada Chair in Engineering Education Research and Development, and the Director of Program Development in the Faculty of Engineering and Applied Science at Queen’s University where he works on engineering curriculum development,Julian Ortiz, Queen’s University Dr. Ortiz is a Mining Engineer from Universidad de Chile and Ph.D. from University of Alberta. Currently, he is Professor and Mark Cutifani / Anglo American Chair in Mining Innovation at University of Exeter - Camborne School of Mines, in the United Kingdom, where he conducts research related to

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)

Paper ID #41785Integrating Data-Driven and Career Development Theory-Driven Approachesto Study High School Student Persistence in STEM Career Aspirationstonghui xu, University of Massachusetts, Lowell PhD studentDr. Hsien-Yuan Hsu, University of Massachusetts, Lowell Dr. Hsien-Yuan Hsu is an Assistant Professor in Research and Evaluation in the College of Education at the University of Massachusetts Lowell. Dr. Hsu received his PhD in Educational Psychology from Texas A&M University and has a background of statistics ©American Society for Engineering Education, 2024 Integrating Features Selection

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

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)

Paper ID #41210Data-Science Perceptions: A Textual Analysis of Reddit Posts from Non-ComputingEngineersMr. Nicolas Leger, Florida International University Nicolas L´eger is currently an engineering and computing education Ph.D. student in the School of Universal Computing, Construction, and Engineering Education (SUCCEED) at Florida International University. He earned a B.S. in Chemical and Biomolecular Engineering from the University of Maryland at College Park in May 2021 and began his Ph.D. studies the following fall semester. His research interests center on numerical and computational methods in STEM education and in

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 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

engineering students with respect to campus-wide students. Prior research is limited in comparative assessment, the insights from which can help inform intervention strategies aimed at improving the credit efficiency of STEM students (at institutional and/or government levels). • A data-driven way to approximate and remove surplus credits (explained in Section 3.2) - credits that are not expected to contribute towards the student’s degree program and thus can potentially bias the analysis, e.g., Transfer students starting out with more credits than required by their intended degree program contribute to surplus.This work is currently limited to graduated students. Our initial findings, using actual data from alarge

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)

. Xuemin Jin is a teaching professor at the Department of Mechanical and Industrial Engineering at Northeastern University. He teaches two core courses for the Data Analytics Engineering Graduate Program, Data Management for Analytics and Data Mining in Engineering. His current research interests include emotion detection, remote sensing and atmospheric compensation. Before joining Northeastern University, Dr. Jin was a data scientist at State Street Corporation, a principal scientist at Spectral Sciences, Inc., a software engineer at eXcelon Corp, and a scientist at SerOptics, Inc. Dr. Jin received his Ph.D. in physics from University of Maryland at College Park. He was a postdoctoral at MIT and at TRIUMF Canada

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

. She holds a BS in mechanical engineering, MA in educational studies, and a PhD in Engineering Education where her research focuses on digital learning environments for the STEM workforce.Thomas Bihari, The Ohio State UniversityThomas Metzger, The Ohio State University ©American Society for Engineering Education, 2024 An Online Interdisciplinary Professional Master’s Program in Translational Data AnalyticsAbstractThis paper describes an interdisciplinary data analytics professional master’s program whichincludes courses from the disciplines of computer science, statistics, and design. The onlinecurriculum structure specifically addresses the needs of working professionals

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)

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 improve student recruitment, retention, and success metrics. Dr. Slim’s scholarly contributions include numerous articles on the application of data science in enhancing educational practices.Husain Al Yusuf, The University of Arizona Husain Al Yusuf is a third-year PhD candidate in the Electrical and Computer Engineering Department at the University of Arizona. He is currently pursuing his PhD with a research focus on applying machine learning and data analytics to higher education, aiming to enhance student

Conference Session

DSA Technical Session 1

Collection

2024 ASEE Annual Conference & Exposition

Authors

Gregory L. Heileman, The University of Arizona; Yiming Zhang, The University of Arizona

Tagged Topics

Data Science & Analytics Constituent Committee (DSA)

Executive Committee of AZTransfer, an organization that works across the system of higher education in the State of Arizona to ensure students have access to efficient, seamless, and simple ways to transfer from a community college to a university in Arizona. He serves on the board of the Association for Undergraduate Education at Research Universities, a consortium that brings together research university leaders with expertise in the theory and practice of undergraduate education and student success. In addition, he is a fellow at the John N. Gardner Institute for Excellence in Undergraduate Education. Professor Heileman’s work on analytics related to student success has led to the development of a theory of

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