Background
To succeed in engineering careers, students must be able to create and apply models to certain problems. The different types of models include physical, mathematical, computational, graphical, and financial, which are used both in academics, research, and industry. However, many students struggle to define, create, and apply relevant models in their engineering courses.
Purpose (Research Questions)
The research questions investigated in this study are: (1) What types of models do engineering students identify before and after completing a first-year engineering course? (2) How do students’ responses compare across different courses (a graphical communications course - EGR 120 and a programming course - EGR 115), and sections?
Design/Methods
The data used for this study were collected in two introductory first-year engineering courses offered during Fall 2019, EGR 115 and EGR 120. Students’ responses to a survey about modeling were qualitatively analyzed. The survey was given at the beginning and the end of the courses. The data analyzed consisted of 560 pre and post surveys for EGR 115 and 384 pre and post surveys for EGR 120.
Results
Once the analysis is complete, we are hoping to find that the students can better define and apply models in their engineering courses after they have completed the EGR 115 and/or EGR 120 courses.
more »
« less
Change in student understanding of modeling during first-year engineering courses
All engineers must be able to apply and create models to be effective problem solvers, critical thinkers, and innovative designers. To be more successful in their studies and careers, students need a foundational knowledge about models. An adaptable approach can help students develop their modeling skills across a variety of modeling types, including physical models, mathematical models, logical models, and computational models. Physical models (e.g., prototypes) are the most common type of models that engineering students identify and discuss during the design process. There is a need to explicitly focus on varying types of models, model application, and model development in the engineering curriculum, especially on mathematical and computational models.
This NSF project proposes two approaches to creating a holistic modeling environment for
learning at two universities. These universities require different levels of revision to the existing first-year engineering courses or programs. The proposed approaches change to a unified language and discussion around modeling with the intent of contextualizing modeling as a fundamental tool within engineering. To evaluate student learning on modeling in engineering, we conducted pre and post surveys across three different first-year engineering courses at these two universities with different student demographics. The comparison between the pre and post surveys highlighted student learning on engineering modeling based on different teaching and curriculum change approaches.
more »
« less
- Award ID(s):
- 1827392
- NSF-PAR ID:
- 10182820
- Date Published:
- Journal Name:
- ASEE Annual Conference proceedings
- ISSN:
- 1524-4644
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
More Like this
-
-
As part of the e4usa curriculum, a MATLAB model has been developed and implemented in order to cultivate engineering and computational thinking skills in high school students. The MATLAB model uses a live script that allows students to interact with sliders and dropdown menus to change parameters on a water filtration model. With computational skills increasingly in demand, the literature suggests that adding computational thinking and coding skills as a new form of literacy is crucial for preparing future engineering professionals. Additionally, to ensure that students are better prepared by the time they reach their post-secondary studies, early exposure to computational thinking skills has valuable implications. In this fundamental paper, we describe outcomes resulting from students' interactions with MATLAB in e4usa. The mathematical model allows the students to analyze the effects of different filtration materials, impurities to be removed, length of the water filter, and the space between particles in their filtration material. Using at first a mathematical model rather than testing physical materials will allow them to learn more about their potential filtration materials so that they may make more informed decisions about which filtration materials they want to select for their design and use in the prototype that they build and test. With that said, we focus on student outcomes in this design activity. We hypothesize that this modeling activity prior to design may reduce the time spent in physical testing as well as the volume of materials consumed. Additionally, we are inquisitive about the impact that it has on the subsequent design activities compared to previous semesters where this lesson was taught, where it was observed that students spend a considerable amount of time trying out different materials. As part of our data, we have collected teacher data from surveys, pre and post-responses about their expectations, attitudes, and perceived value of implementing the MATLAB model in their classrooms, class observation data from at least two schools where we noted the interactions between the teachers and students, and teacher and student focus groups at the end of the semester where we expect to collect richer data from these two groups that will allow us to triangulate data collected from surveys and classroom observations.more » « less
-
Generally, the focus of undergraduate engineering programs is on the development of technical skills and how they can be applied to design and problem solving. However, research has shown that there is also a need to expose students to business and society factors that influence design in context. This technical bias is reinforced by the available tools for use in engineering education, which are highly focused on ensuring technical feasibility, and a corresponding lack of tools for engineers to explore other design needs. One important contextual area is market systems, where design decisions are made while considering factors such as consumer choice, competitor behavior, and pricing. This study examines student learning throughout a third-year design course that emphasizes market-driven design through project-based activities and assignments, including a custom-made, interactive market simulation tool. To bridge the gap between market-driven design and engineering education research, this paper explores how students think about and internally organize design concepts before and after learning and practicing market-driven design approaches and tools in the context of an engineering design course. The central research question is: In what ways do student conceptions of product design change after introducing a market-driven design curriculum? In line with the constructivism framework of learning, it is expected that student conceptions of design should evolve to include more market considerations as they learn about and apply market-driven design concepts and techniques to their term projects. Four different types of data instruments are included in the analysis: Concept maps generated by the students before and after the course, open-ended written reflection assignments at various points in the semester, surveys administered after learning the market simulation tool and at the end of the course, and final project reports in which student teams listed their top 3-5 lessons learned in the course. Using the changes between the pre- and post-course concept maps as the primary metric to represent evolving design conceptions, data from the reflections, surveys, and reports are evaluated to assess their influence on such learning. Because market-driven design is a multi-faceted topic, a market-driven design is hierarchically decomposed into specific sub-topics for these evaluations. These include profitability (which itself encompasses pricing and costs), modeling and simulation, and market research (which encompasses consumers and competition). For each topic, correlation analyses are performed and regression models are fit to assess the significance of different factors on learning. The findings provide evidence regarding the effectiveness of the course’s market-driven design curriculum and activities on influencing student conceptions of design.more » « less
-
Generally, the focus of undergraduate engineering programs is on the development of technical skills and how they can be applied to design and problem solving. However, research has shown that there is also a need to expose students to business and society factors that influence design in context. This technical bias is reinforced by the available tools for use in engineering education, which are highly focused on ensuring technical feasibility, and a corresponding lack of tools for engineers to explore other design needs. One important contextual area is market systems, where design decisions are made while considering factors such as consumer choice, competitor behavior, and pricing. This study examines student learning throughout a third-year design course that emphasizes market-driven design through project-based activities and assignments, including a custom-made, interactive market simulation tool. To bridge the gap between market-driven design and engineering education research, this paper explores how students think about and internally organize design concepts before and after learning and practicing market-driven design approaches and tools in the context of an engineering design course. The central research question is: In what ways do student conceptions of product design change after introducing a market-driven design curriculum? In line with the constructivism framework of learning, it is expected that student conceptions of design should evolve to include more market considerations as they learn about and apply market-driven design concepts and techniques to their term projects. Four different types of data instruments are included in the analysis: Concept maps generated by the students before and after the course, open-ended written reflection assignments at various points in the semester, surveys administered after learning the market simulation tool and at the end of the course, and final project reports in which student teams listed their top 3-5 lessons learned in the course. Using the changes between the pre- and post-course concept maps as the primary metric to represent evolving design conceptions, data from the reflections, surveys, and reports are evaluated to assess their influence on such learning. Because market-driven design is a multi-faceted topic, a market-driven design is hierarchically decomposed into specific sub-topics for these evaluations. These include profitability (which itself encompasses pricing and costs), modeling and simulation, and market research (which encompasses consumers and competition). For each topic, correlation analyses are performed and regression models are fit to assess the significance of different factors on learning. The findings provide evidence regarding the effectiveness of the course’s market-driven design curriculum and activities on influencing student conceptions of design.more » « less
-
Economically disadvantaged youth residing in mountain tourist communities represent an important and understudied rural population. These communities typically include a large percentage of children that are English language learners. Our NSF STEM Career Connections project, A Model for Preparing Economically-Disadvantaged Rural Youth for the Future STEM Workplace, investigates strategies that help middle school youth in these communities to envision a broader range of workforce opportunities, especially in STEM and computing careers. This poster highlights the initial findings of an innovative model that involves working with local schools and community partners to support the integration of local career contexts, engineering phenomena, 3D printing technologies, career connections, and mentorship into formal educational experiences to motivate and prepare rural youth for future STEM careers. We focus on select classrooms at two middle schools and describe the implementation of a novel 3D printing curriculum during the 2020-2021 school-year. Two STEM teachers implemented the five-week curriculum with approximately 300 students per quarter. To create a rich inquiry-driven learning environment, the curriculum uses an instructional design approach called storylining. This approach is intended to promote coherence, relevance, and meaning from the students’ perspectives by using students’ questions to drive investigations and lessons. Students worked towards answering the question: “How can we support animals with physical disabilities so they can perform daily activities independently?” Students engaged in the engineering design process by defining, developing, and optimizing solutions to develop and print prosthetic limbs for animals with disabilities using 3D modeling, a unique augmented reality application, and 3D printing. In order to embed connections to STEM careers and career pathways, some students received mentorship and guidance from local STEM professionals who work in related fields. This poster will describe the curriculum and its implementation across two quarters at two middle schools in the US rural mountain west, as well as the impact on students’ interest in STEM and computing careers. During the first quarter students engaged in the 3D printing curriculum, but did not have access to the STEM career and career pathway connections mentorship piece. During the second quarter, the project established a partnership with a local STEM business -- a medical research institute that utilizes 3D printing and scanning for creating human surgical devices and procedures -- to provide mentorship to the students. Volunteers from this institute served as ongoing mentors for the students in each classroom during the second quarter. The STEM mentors guided students through the process of designing, testing, and optimizing their 3D models and 3D printed prosthetics, providing insights into how students’ learning directly applies to the medical industry. Different forms of student data such as cognitive interviews and pre/post STEM interest and spatial thinking surveys were collected and analyzed to understand the benefits of the career connections mentorship component. Preliminary findings suggest the relationship between local STEM businesses and students is important to motivate youth from rural areas to see themselves being successful in STEM careers and helping them to realize the benefits of engaging with emerging engineering technologies.more » « less
- Free Publicly Accessible Full Text
-
Accepted Manuscript1.0
- Conference Paper:
- https://doi.org/10.18260/1-2--34269
