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Asking Questions About Data: First-year Engineering Students' Introduction to Data Analytics

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Conference

2020 ASEE Virtual Annual Conference Content Access

Location

Virtual On line

Publication Date

June 22, 2020

Start Date

June 22, 2020

End Date

June 26, 2021

Conference Session

First-year Programs: Professional Development and Skills

Tagged Division

First-Year Programs

Page Count

16

DOI

10.18260/1-2--34167

Permanent URL

https://cms.jee.org/34167

Download Count

21

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Paper Authors

biography

Ruben D. Lopez-Parra P.E. Purdue University, West Lafayette

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Ruben D. Lopez-Parra is a graduate research assistant at Purdue University pursuing a Ph.D. in Engineering Education. Previously, he worked as a Natural Science teacher in High School where he, as a scholarly teacher, constantly assessed his performance to design better learning environments that promote students’ conceptual understanding. In 2015, Ruben earned the M.S in Chemical Engineering at Universidad de los Andes in Colombia where he also received the title of Chemical Engineer in 2012. His research interests include cognition and metacognition in the engineering curriculum.

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biography

Arístides Carrillo Fernández Purdue University, West Lafayette

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Arístides Carrillo Fernández is a Ph.D student in School of Engineering Education at Purdue University. He was previously an export business development manager at a Spanish radio communications company in Madrid, Spain. For over six years., he was developing new distribution dealer networks in South Europe and West Africa countries. He earned his M.S. in Electronics and Systems of Telecommunication at ESIGELEC (École Supérieur D'Ingénieurs en Génie Électrique) at Rouen, France in 2009, and his B.S. in Systems of Telecommunication at Polytechnic University of Madrid at Madrid, Spain in 2006.
Arístides' research interests include the role of empathy and reflection in learning in engineering education and practice contexts, and professional development in global environments.

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Amanda Johnston Purdue University, West Lafayette

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Amanda Johnston is a PhD candidate in engineering education at Purdue University.

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Tamara J. Moore Purdue University, West Lafayette Orcid 16x16 orcid.org/0000-0002-7956-4479

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Tamara J. Moore, Ph.D., is a Professor in the School of Engineering Education and Interim Executive Director of the INSPIRE Institute at Purdue University. Dr. Moore’s research is centered on the integration of STEM concepts in K-12 and postsecondary classrooms in order to help students make connections among the STEM disciplines and achieve deep understanding. Her work focuses on defining STEM integration and investigating its power for student learning. Tamara Moore received an NSF Early CAREER award in 2010 and a Presidential Early Career Award for Scientists and Engineers (PECASE) in 2012.

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Sean P. Brophy Purdue University, West Lafayette

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Dr. Sean Brophy is the Co-Leader of the Educational, Outreach and Training them for the George E. Brown Network for Earthquake Engineering Simulation (NEES). His research in engineering education and learning sciences explores how children learn through interactions with technologies ranging from manual manipulative like structures students design build and test with shake tables to digital manipulative with mobile devices. He continues to explore new methods to enhance informal and formal learning experiences.

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Abstract

This complete research paper aims to understand the question design’s process of first-year engineering students when performing data analytics. Specifically, we aim to answer the research question: How do first-year engineering students use a large data set to ask questions focused on the client’s needs? While most research in the area of analytics has focused on how to perform the data analytics cycle successfully, the learning process behind the practice of data analytics is still not totally understood. This study was conducted with 53 first-year engineering students who worked in 14 teams to solve an open-ended problem of data analytics called: The Bike-share Problem. Students were tasked to download the freely available data from Capital Bikeshare company (~3 million data points) and do a preliminary analysis to understand the data set and the company itself. Students proposed questions individually to explore the data and, as a team, design a team question focused on the client’s needs. We used content analysis to develop a codebook and analyze the 92 individual and 13 team questions. Our results showed students were able to take the data and frame a problem until designing a question that considered the client’s perspective. However, some students ended up writing questions that were not clear due to ambiguous terms, so simple as not to be useful to the client, or too complex to be answerable with the date and time they had. Additionally, students’ questions often focused on a single, simple variable of the data and not utilizing the breadth of the data available to them. Finally, the student’s previous knowledge of statistics could have mediated their question design practice and limited their ability to answer their questions. We presented some suggestions for researchers and professors who want to study and teach analytics. The Bike-share problem is an example of how analytics can be successfully integrated early in engineering curricula, and we animate professors to implement similar activities in their courses.

Lopez-Parra, R. D., & Carrillo Fernández, A., & Johnston, A., & Moore, T. J., & Brophy, S. P. (2020, June), Asking Questions About Data: First-year Engineering Students' Introduction to Data Analytics Paper presented at 2020 ASEE Virtual Annual Conference Content Access, Virtual On line . 10.18260/1-2--34167

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