Leveraging Mathematical Modeling to Expand Measurement-Process Opportunities for Engineering Students

Luis E Montero-Moguel; Joel Alejandro Mejia; Guadalupe Carmona

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Conference: 2024 ASEE Annual Conference & Exposition
Location: Portland, Oregon
Publication Date: June 23, 2024
Start Date: June 23, 2024
End Date: July 12, 2024
Conference Session: Mathematics Division (MATH) Technical Session 1
Tagged Division: Mathematics Division (MATH)
Tagged Topic: Diversity
Permanent URL: https://peer.asee.org/47740

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Paper Authors

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Luis E Montero-Moguel The University of Texas at San Antonio orcid.org/0000-0002-9009-1377

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Luis Montero-Moguel is a Ph.D. Candidate in Interdisciplinary Learning and Teaching specializing in STEM education at The University of Texas at San Antonio (UTSA). Luis holds an MSc in Mathematics Education from the University of Guadalajara and a BSc in Mechanical Engineering. Luis is an NSF-CADRE fellow. As part of his doctoral program, Luis has earned a Graduate Certificate in iSTEM Education and a Graduate Certificate in Engineering Education. With experience as an engineer and a mathematics teacher, he promotes the expansion of equitable and high-quality learning opportunities for both engineering and K–12 students through mathematical modeling. His research focuses on exploring the process of refining mathematical ideas and engineering concepts that engineering students develop while engaging in model development sequences built in real engineering contexts.

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Joel Alejandro Mejia The University of Texas at San Antonio orcid.org/0000-0003-3908-9930

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Dr. Joel Alejandro (Alex) Mejia is an Associate Professor with joint appointment in the Department of Biomedical Engineering and Chemical Engineering and the Department of Bicultural-Bilingual Studies at The University of Texas at San Antonio. He received his B.S. in Metallurgical and Materials Engineering from The University of Texas at El Paso in 2007, his M.S. in Metallurgical Engineering from The University of Utah in 2013, and his Ph.D. in Engineering Education from Utah State University in 2014. His research has contributed to the critical analysis engineering knowledge within sociocultural and sociopolitical contexts, the impact of critical consciousness in engineering practice, and the development of culturally responsive pedagogies.

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Guadalupe Carmona The University of Texas at San Antonio

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Abstract

The challenges of the 21st century require students to engage in activities that enable them to “learn the importance of such decisions as what to measure, what to keep constant, and how to select or construct data collection instruments” [1, p. 58]. This is especially critical for engineering students because engineers are required to develop measurement processes during the mathematical modeling process of designs [2]. Nonetheless, ABET student outcomes do not explicitly indicate data analysis within measurement processes. Moreover, mathematics education often provides students with preconceived measures, reducing opportunities for students to confront real situations involving measurement process [3]. First-year engineering students face even more limited opportunities to encounter real-world situations because they are often perceived to have limited experience with the nature of engineering work [4]. Therefore, it is imperative to explore how mathematics education in engineering can better inform the professional development of students with modeling skills that include measurement opportunities. This study, grounded in the Models and Modeling perspective [5], aims to describe the measurement process that two groups of first-year engineering students developed when participating in an activity involving the modeling of a ram water pump’s efficiency. The research question that guided qualitative research was: What opportunities are promoted for first-year engineering students to learn measurement processes when they engage in a modeling activity that involves the use of a ram pump? With the aim of deepening our understanding of the measurement processes generated by students participating in a MEA, we chose to conduct a qualitative case study [6]. Two teams of first-year engineering students were selected for the study. Qualitative analysis focused on examining the measurement processes students developed while solving a Model-eliciting activity (MEA) which involved creating measurement processes for the operation of a ram pump to develop an efficiency manual. This manual is intended to provide instructions for efficiently using a ram pump, enabling “las colonias” community residents to pump water from communal tanks to their homes. The results led us to conclude that the Ram Pump MEA presented numerous learning opportunities for first-year engineering students to learn and elicit measurement processes through the engineering design process cycle. As students gathered data on water pumped and water loss, they iteratively refined their models. Through this process, the students attained a thorough understanding of measurement processes, with both teams successfully identifying the five key characteristics of measurement. We argue that embedding data analysis within engineering measurement processes is critical for engineering preparation programs, and must be considered central to sense-making and problem-solving. This study contributes to the growing knowledge on how students might engage in these processes as part of mathematical modeling, and how this approach can be useful for providing future recommendations for curricula and learning outcomes alignment in engineering education.

Citation
Format

Montero-Moguel, L. E., & Mejia, J. A., & Carmona, G. (2024, June), Leveraging Mathematical Modeling to Expand Measurement-Process Opportunities for Engineering Students Paper presented at 2024 ASEE Annual Conference & Exposition, Portland, Oregon. https://peer.asee.org/47740

TY  - CPAPER
AB  - The challenges of the 21st century require students to engage in activities that enable them to “learn the importance of such decisions as what to measure, what to keep constant, and how to select or construct data collection instruments” [1, p. 58]. This is especially critical for engineering students because engineers are required to develop measurement processes during the mathematical modeling process of designs [2]. Nonetheless, ABET student outcomes do not explicitly indicate data analysis within measurement processes. Moreover, mathematics education often provides students with preconceived measures, reducing opportunities for students to confront real situations involving measurement process [3]. First-year engineering students face even more limited opportunities to encounter real-world situations because they are often perceived to have limited experience with the nature of engineering work [4]. Therefore, it is imperative to explore how mathematics education in engineering can better inform the professional development of students with modeling skills that include measurement opportunities. 
This study, grounded in the Models and Modeling perspective [5], aims to describe the measurement process that two groups of first-year engineering students developed when participating in an activity involving the modeling of a ram water pump’s efficiency. The research question that guided qualitative research was: What opportunities are promoted for first-year engineering students to learn measurement processes when they engage in a modeling activity that involves the use of a ram pump?
With the aim of deepening our understanding of the measurement processes generated by students participating in a MEA, we chose to conduct a qualitative case study [6]. Two teams of first-year engineering students were selected for the study. Qualitative analysis focused on examining the measurement processes students developed while solving a Model-eliciting activity (MEA) which involved creating measurement processes for the operation of a ram pump to develop an efficiency manual. This manual is intended to provide instructions for efficiently using a ram pump, enabling “las colonias” community residents to pump water from communal tanks to their homes. The results led us to conclude that the Ram Pump MEA presented numerous learning opportunities for first-year engineering students to learn and elicit measurement processes through the engineering design process cycle. As students gathered data on water pumped and water loss, they iteratively refined their models. Through this process, the students attained a thorough understanding of measurement processes, with both teams successfully identifying the five key characteristics of measurement. We argue that embedding data analysis within engineering measurement processes is critical for engineering preparation programs, and must be considered central to sense-making and problem-solving. This study contributes to the growing knowledge on how students might engage in these processes as part of mathematical modeling, and how this approach can be useful for providing future recommendations for curricula and learning outcomes alignment in engineering education.
AU  - Luis E Montero-Moguel
AU  - Joel Alejandro Mejia
AU  - Guadalupe Carmona
CY  - Portland, Oregon
DA  - 2024/06/23
PB  - ASEE Conferences
TI  - Leveraging Mathematical Modeling to Expand Measurement-Process Opportunities for Engineering Students
UR  - https://peer.asee.org/47740
ER  -