Engineers must understand how to build, apply, and adapt various types of models in order to be successful. Throughout undergraduate engineering education, modeling is fundamental for many core concepts, though it is rarely explicitly taught. There are many benefits to explicitly teaching modeling, particularly in the first years of an engineering program. The research questions that drove this study are: (1) How do students’ solutions to a complex, open-ended problem (both written and coded solutions) develop over the course of multiple submissions? and (2) How do these developments compare across groups of students that did and did not participate in a course centered around modeling?. Students’ solutions to an open-ended problem across multiple sections of an introductory programming course were explored. These sections were all divided across two groups: (1) experimental group - these sections discussed and utilized mathematical and computational models explicitly throughout the course, and (2) comparison group - these sections focused on developing algorithms and writing code with a more traditional approach. All sections required students to complete a common open-ended problem that consisted of two versions of the problem (the first version with smaller data set and the other a larger data set). Each version hadmore »
Comparing Students’ Solutions to an Open-ended Problem in an Introductory Programming Course with and without Explicit Modeling Interventions
Engineers must understand how to build, apply, and adapt various types of models in order to be successful. Throughout undergraduate engineering education, modeling is fundamental for many core concepts, though it is rarely explicitly taught. There are many benefits to explicitly teaching modeling, particularly in the first years of an engineering program. The research questions that drove this study are: (1) How do students’ solutions to a complex, open-ended problem (both written and coded solutions) develop over the course of multiple submissions? and (2) How do these developments compare across groups of students that did and did not participate in a course centered around modeling?.
Students’ solutions to an open-ended problem across multiple sections of an introductory programming course were explored. These sections were all divided across two groups: (1) experimental group - these sections discussed and utilized mathematical and computational models explicitly throughout the course, and (2) comparison group - these sections focused on developing algorithms and writing code with a more traditional approach. All sections required students to complete a common open-ended problem that consisted of two versions of the problem (the first version with smaller data set and the other a larger data set). Each version had two more »
- Award ID(s):
- 1827600
- Publication Date:
- NSF-PAR ID:
- 10192274
- Journal Name:
- ASEE Annual Conference proceedings
- Sponsoring Org:
- National Science Foundation
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This complete research paper describes the impact of a modeling intervention on first-year engineering students’ modeling skills in an introductory computer programming course. Five sections of the first-year engineering introductory programming course at a private, STEM+Business institution were revised to center around modeling concepts. These five sections made up the experimental group for this study. The comparison group consisted of four sections of the course that were not revised. Students in all these sections were given two different versions of a modeling problem two times in the semester to test their progress in gaining modeling skills. Each version required two submissions – a written solution and a coded solution. The assessment of these four submissions based on the three established dimensions of modeling were quantitatively analyzed in this study. The three dimensions within mathematical modeling that were the focus of this study were mathematical model complexity, modifiability, and reusability. Mathematical model complexity is being able to address the complexity of the problem. Modifiability addresses the generalizability of the model solution. Reusability is showing an understanding of the problem and the user. Statistical analysis showed that students in the experimental group had more gains in their demonstrated modeling abilities across allmore »
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