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

programs incorporated lectures,hands-on labs, group projects and/or national lab intern experience. In the last three-year’simplementation, the student assessment and project completion result all showed theeffectiveness of the approach in enhancing students’ ability to understand the science foundation,identify real-world problems, analyze data and develop data-driven solutions in nuclear energyand security areas. The feedback from student surveys is also satisfactory and positive. Thisresearch is sponsored by Department of Energy/NNSA and intends to share the project team’sexperience and lessons learned with the STEM education community.KeywordsData Science, Workforce Development, STEM Education, Nuclear Energy and SecurityIntroductionData

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

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Data Science & Analytics Constituent Committee (DSA)

Engineering in 2009 from the Imperial College of London and his doctoral degree in 2020 from the University of Georgia, College of Engineering.Jack Yang, New York University Tandon School of Engineering ©American Society for Engineering Education, 2024 An Interactive Platform for Team-based Learning Using Machine Learning ApproachAbstractThis complete evidence-based paper explores the feasibility of developing an interactiveplatform with chatbot feature to facilitate project-based learning. Teamwork pedagogy is widelyused in engineering courses, particularly in first year (cornerstone) and senior-year (capstone)design courses, but also across the curriculum. Faculty have several

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

with little to noprior data science, computing, or math background. Courses use both synchronous andasynchronous delivery methods to maximize learner flexibility while providing opportunities toengage in real time with instructors and peers. All courses emphasize projects to provideopportunities for learners to apply courses concepts to real-world problems. A terminal 2-semester capstone course incorporates all three disciplines into a final culminating team project.This paper will focus on the conceptualization of the computer science (CS) portion of thecurriculum. As an applied master’s program, much of the CS curriculum takes inspiration fromindustry frameworks such as CRISP-DM and Agile project management to contextualizeconcepts. The

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

, Geometric Abstraction, and Mathematics as they relate toengineering and art. Woven into the theoretical content are hands-on projects where studentslearn basic sketching skills, hand build a ceramic still-life piece, visit local galleries andmuseums, and, using elements or art and principles of design, turn data into data visualizationsand data physicalizations: data-driven physical artefacts whose geometry or material propertiesencode data. Students use an adapted Jansen and Dragicevic [1] information visualizationpipeline to move from raw data to data wrangling to visual and physical presentation. This paperpresents examples of the process and concludes with observations and lessons learned.Figure 1. Informa0on visualiza0on pipeline. Jansen and

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

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Data Science & Analytics Constituent Committee (DSA)

Paper ID #44344Developing an Instrument for Assessing Self-Efficacy Confidence in Data ScienceDr. Safia Malallah, Kansas State University Safia Malallah is a postdoc in the computer science department at Kansas State University working with Vision and Data science projects. She has ten years of experience as a computer analyst and graphic designer. Besides, she’s passionate about developing curriculums for teaching coding, data science, AI, and engineering to young children by modeling playground environments. She tries to expand her experience by facilitating and volunteering for many STEM workshops.Dr. Ejiro U Osiobe

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

includes application of AI for project management, sustainability and data center energy.Mr. James Jay Jaurez, National University Dr. Jaurez is a dedicated Academic Program Director and Associate Professor in Information Technology Management at National University where he has served since 2004. Dr. Jaurez is also a FIRST Robotics Head Coach since 2014 and leads outreach in robotiNelson Altamirano, National University ©American Society for Engineering Education, 2024Application of Data Analysis and Visualization Tools for US Renewable SolarEnergy Generation, its Sustainability Benefits, and Teaching In Engineering Curriculum Ben D Radhakrishnan, M.Tech., M.S

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

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Data Science & Analytics Constituent Committee (DSA)

GovernorAsa Hutchinson made headlines in 2015 with the enactment of new legislation requiring allArkansas public high schools to offer at least one computer science course. At the time, only afew states had implemented such requirements, and Information Technology & Informationestimated that computer science courses were offered at only one in ten schools nationwide(Armitage, 2015). The same Arkansas legislation, Act 187, also called for the establishment of astatewide task force to oversee the project and declared the overall lack of graduates withcomputer science skills to be a public emergency (Arkansas State Legislature, 2015). In late2020, the Arkansas Board of Education adopted new rules for the 2021-22 school year thatemphasized computer

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

, the visualizations notonly illuminated racial disparities but also underscored the need for social change. Furthermore,his visualizations showcased the connection between visualization and the public's response.DuBois's works demonstrate that properly presented data can affect audiences’ opinions, evokeemotions, raise awareness, and prompt action. His work shows that understanding the public'sresponse to data allows for effective visualization techniques and demonstrates the necessity formore creative visualizations in modern fields to inspire change. A selection of DuBois’svisualizations is shown below. W.E.B DuBois Visualizations for the 1900 Paris World’s Fair [4]This project bridges fields of data science, engineering

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

the DS program in the fourth year encompasses a compulsory Machine Learning class,complemented by a diverse array of electives within the Data Science program. Further enriching theirskill set, students embark on their second Co-op work experience during the Spring semester, gaininghands-on exposure to real-world Data Science applications. The program concludes in the Summer with acombination of additional electives and a mandatory Senior Design class. In this concluding phase,students collaborate on a group project throughout the semester, applying their accumulated knowledgeand skills to address complex challenges in the field of Data Science.D. Educational ObjectivesIn this program design, we envision that integrating Computer Science

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)

projects” [28, p.1 ], or the “procedure of automatic extraction ofdata from websites using software” [34], or “an interactive method for website and some otheronline sources to browse for and access data” [35]. Other definitions also extend thesedefinitions by suggesting the collection of unstructured data from the web into structured ones in“a central database or spreadsheet” [36]. Web scraping is also referred to as web crawling, butsome argue that web scraping is the extraction of data from a website, whereas web crawling isthe identification of target Uniform Resource Locator (URL) links [34]. Broucke et al. extend onthis and suggest that the crawling term refers to the ability of the program to navigate web pageson its own with 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)

Supervisor Spotlight Award in 2014, received the College of Engineering Graduate Student Mentor Award in 2018, and was inducted into the Virginia Tech Academy of Faculty Leadership in 2020. Dr. Matusovich has been a PI/Co-PI on 19 funded research projects including the NSF CAREER Award, with her share of funding being nearly $3 million. She has co-authored 2 book chapters, 34 journal publications, and more than 80 conference papers. She is recognized for her research and teaching, including Dean’s Awards for Outstanding New Faculty, Outstanding Teacher Award, and a Faculty Fellow. Dr. Matusovich has served the Educational Research and Methods (ERM) division of ASEE in many capacities over the past 10+ years including

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)

programming, intelligence design, data warehousing),programming (problem-solving, languages such as Python, Java), project management (planning,project analysis, risk reporting), data analytics (computer learning, programming, statisticalmodeling), and business impact (consulting, market delivery, strategic management). Results [7]from an analysis of 1050 unique records of Data Science job requirements showed that technicalskills are in high demand when seeking Data Scientists. These skills include proficiency in BigData Technologies, software development, data management, analytic methods, algorithms,programming languages, and analytic tools. In addition, the study findings [7] showed demandfor soft skills (non-technical and interpersonal skills

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)

opposed to the average page views by the lower quartile.This is an expected outcome if one assumes pages views as a proxy for student engagement andthus performance. This trend is less pronounced for the Nano course, however, where the pageview averages for different quartiles often overlap. A secondary trend is that the average pageviews spike right before a major assessment for iTFS. This, however, is not the case for Nano. 6The average page views during the project phase is highly dependent on the type of the projectassigned. The instructor's insight here is that for iTFS, the majority of the efforts relied onexternal resources, whereas for Nano, the majority of the project required interaction

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)

entity recognition [33]. While early automated feedback systemsrelied on domain-expert rules and were limited in addressing the diversity of open-endedassignments [34-36], data-driven approaches, though promising in highly semantically diverseresponses, often face challenges due to the lack of extensive training datasets [4, 37, 38].AFS based on LLMs holds the potential for a more effective and efficient solution. Applicationsrange from personalized hints for programming assignments [39] to reflective writing [40],including feedback on the appropriateness of the topic of a data science project proposal and thedescription clarity of goals, benefits, novelty and overall clarity of the report [41]. Despite thepromising results from studies like Dai

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)

general observation of the authors that the accuracy of the results might be improved byconsidering certain factors, such as capturing images in a well-lit central zone with highmagnification and in a dark room to avoid interference from surrounding light.5. Development of Interdisciplinary Curriculum: 11As a critical by-product of the current project, the methods highlighted can be utilized across amultitude of disciplines (from bioengineering to electrical, materials, nanoengineering, etc.) forone of the most fundamental areas of experimental research in STEM at the undergraduate level:accurately identifying multiple systems from optical images. A broad, relevant, and timelycurriculum can be built

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)

2020 degree share 24%), race (sample white 33% vs 2020 degreeshare 56%), and nationality (including participants residing in Canada, Turkey, and thePhilippines). Aligned with the goals of the larger study, participants were drawn from Aerospace,Civil, and Mechanical engineering disciplines. Demographics are summarized in Table 1.Our sample size of n=24 is in line with recommendations for qualitative research [22], and iscomparable with other peer-reviewed qualitative research projects [23], [24], [25].Table 1. Summary of participant demographics. Experience 2 years: 3 3 years: 2 4 years: 8 5+ years: 11 Race Asian: 10 Black: 2 White: 8 Other: 4 Subfield Aerospace

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

and fosters a positive attitude towards data science. 2. Overcoming Barriers to Learning: By identifying any misconceptions or apprehensions students may have about data science, educators can design interventions that address these issues directly. This might include demystifying data science, showcasing its integral role in solving real-world chemical engineering problems, and providing supportive learning environments that encourage experimentation and inquiry. 3. Enhancing Motivation and Engagement: Understanding students' willingness to engage with data science can help educators employ strategies that boost motivation. For example, integrating practical, hands-on projects that

Conference Session

DSA Technical Session 4

Collection

2024 ASEE Annual Conference & Exposition

Authors

Sami Khorbotly, Valparaiso University; Daniel White, Valparaiso University

Tagged Topics

Data Science & Analytics Constituent Committee (DSA)

of studies exploring factors of effective teaching,” Teaching and Teacher Education, vol. 36, 2013, pp. 143-152.[9] B. Trammell, & R. Aldrich, “Undergraduate Students’ Perspectives of Essential Instructor Qualities,” Journal of the Scholarship of Teaching and Learning, vol. 16. 2016.[10] https://pypi.org/project/PuLP/

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

engineering design, collaboration in engineering, decision making in engineering teams, and elementary engineering education.Dr. Adetoun Yeaman, Northeastern University Adetoun Yeaman is an Assistant Teaching Professor in the First Year Engineering Program at Northeastern University. Her research interests include empathy, design education, ethics education and community engagement in engineering. She currently teaches Cornerstone of Engineering, a first-year two-semester course series that integrates computer programming, computer aided design, ethics and the engineering design process within a project based learning environment. She was previously an engineering education postdoctoral fellow at Wake Forest University

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

human topics please see ourprevious work [3]. Figure 4. Q1 GAI-generated topics mapped to human-generated topics (themes) The GAI and the manual qualitative coding approach identified several main topicsrelated to the online learning experience during the pandemic, suggesting alignment in capturingcore student concerns. Both highlighted topics around interactivity/engagement, communication,instructor support, feedback, instructions/resources, flexibility, and teaching methods. Forexample, the "Interactivity and Engagement" topic from the GAI aligned with human codesaround class participation, teamwork, and project assignments - all factors impacting howengaged students felt. The "Feedback" topic also directly matched between GAI

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)

Paper ID #43642Using Machine Learning to Analyze Short-Answer Responses to ConceptuallyChallenging Chemical Engineering Thermodynamics QuestionsHarpreet Auby, Tufts University Harpreet is a graduate student in Chemical Engineering and STEM Education. He works with Dr. Milo Koretsky and helps study the role of learning assistants in the classroom as well as machine learning applications within educational research and evaluation. He is also involved in projects studying the uptake of the Concept Warehouse. His research interests include chemical engineering education, learning sciences, and social justice.Namrata

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)

analysis with traditional, fullymanual domain expert coding using Cohen’s kappa to understand the potential for hybridmethods to be used more extensively by education researchers.MethodsThis paper is part of a comprehensive research project conducted within a single institutionacross multiple academic years. The overall goal of the research is to explore the relationshipbetween different types of learning support (provided by faculty, teaching assistants (TAs), andpeers) and various aspects of engagement at the course level, encompassing both behavioral andemotional dimensions, across diverse learning environments including traditional and remotesettings [7]. The survey used to support this research incorporated several short-answer questionsto

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)

(with machine learning and cognitive research). My background is in Industrial Engineering (B.Sc. at the Sharif University of Technology and ”Gold medal” of Industrial Engineering Olympiad (Iran-2021- the highest-level prize in Iran)). Now I am working as a researcher in the Erasmus project, which is funded by European Unions (1M $ European Union & 7 Iranian Universities) which focus on TEL and students as well as professors’ adoption of technology(modern Education technology). Moreover, I cooperated with Dr. Taheri to write the ”R application in Engineering statistics” (an attachment of his new book ”Engineering probability and statistics.”)Dr. Jason Morphew, Purdue University, West Lafayette Jason W. Morphew is

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

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Data Science & Analytics Constituent Committee (DSA)