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 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

2022, and Texas around 44 Mwh (about 42% lower). The main takeaway from Figure 3is that there is a huge variation in the solar generation capacity and the last State of SC’s 2022generation is 4.8 Mwh. Although there has been a big push to go solar from the Federalgovernment since 2005 (Energy Policy Act, 2005), it is clear that there is huge variation inembracing solar generation across the States. Figure 3 Solar Generation - Top 10 US StatesIt is to be noted that the price per installed watt of solar energy generation has come downdrastically. Per a report from the National Renewable Energy Laboratory (NREL) report, therehas been a 71.6% reduction in the cost of solar systems, and the cost of the module has reducedfrom

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)

limited to additional examples, practice quizzes, anddetailed homework solutions. All responses associated with Topic 1 were subsequently assignedto a theme of “problem solving”. Topic 4 referred to student concerns about sufficient TAassistance in explaining and completing laboratories and other experiential or active learningactivities; this topic was placed into a theme labelled “experiential learning.” Both Topic 2 andTopic 3 indicated students' preferences for increased interaction with TAs, including extendedoffice hours, online (Zoom) meetings, email correspondence, and other forms of question-and-answer engagement. These codes were combined under a single theme of “TA-studentinteractions”. These three themes are all an essential aspect of

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

Paper ID #42406Extra Credit Analysis of Undergraduate Engineering StudentsTushar 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 for analyzing and 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 professor in the ECE

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 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)

measure in this study.Table 6. The number of the participants’ responses based on the type of courses they teach % of I am not # of participants Course Type No Yes Maybe sure participants First-year engineering 30 course 8 12 20 Capstone 37 course 14 11 25 Laboratory 34

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)

MIL-HDBK-5 Program,” Battelle’s Columbus Laboratories, AFWAL-TR-84-1423, 1984.AppendicesA1. Interview Protocol DetailsTowards the beginning of the protocol, participants were presented with Figure 3. This was toclarify the context of data that was presented in the interview—presented values arise frommultiple independent specimens, rather than repeated measurements on a single specimen. Thiswas to ensure the possibility of real variability in the data, without directly naming the concept.Figure 3. Image used to describe the presented data: independent specimens, rather than repeatedmeasurements.Figure 4. Image used to illustrate the design scenario. This structure was described as being inuniaxial tension.Immediately prior to the “error

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)

,” Asia-Pac. Educ. Res., vol. 30, no. 5, pp. 375–394, Oct. 2021, doi: 10.1007/s40299-020-00525-x.[10] T. Gok and O. Gok, “Peer Instruction in chemistry education: Assessment of students’ learning strategies,” Learn. Strateg., vol. 17, no. 1, 2016.[11] M. F. Golde, C. L. McCreary, and R. Koeske, “Peer Instruction in the general chemistry laboratory: Assessment of student learning,” J. Chem. Educ., vol. 83, no. 5, p. 804, May 2006, doi: 10.1021/ed083p804.[12] N. Lasry, E. Mazur, and J. Watkins, “Peer Instruction: From Harvard to the two-year college,” Am. J. Phys., vol. 76, no. 11, pp. 1066–1069, Nov. 2008, doi: 10.1119/1.2978182.[13] J. Schell and E. Mazur, “Flipping the chemistry classroom with Peer