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Title: Learning Trajectories through Undergraduate Engineering Curricula and Experiences
This NSF EAGER research paper investigates how undergraduate STEM and engineering students’ learning trajectories evolve over time, from 1st to senior year, along a novice to expert spectrum. We borrow the idea of “learning trajectories” from mathematics education that can paint the evolution of students’ knowledge and skills over time over a set of learning experiences. Curricula for undergraduate engineering programs can reflect an intended pathway of knowledge construction within a discipline. We intend our study of individual students within undergraduate STEM and engineering programs can highlight how this may happen in situ and how it may be similar or might differ from a given, prescribed programs of study among disciplines. We use a theoretical framework based in adaptive expertise and design thinking adaptive expertise to develop a design learning continuum further. Envisioned routes through disciplinary undergraduate curricula and student conceptions of their design process are explored through qualitative, semi-structured interviews with undergraduate 1st year and senior year students across STEM, engineering and non-STEM field such as computer science, mechanical engineering, general engineering, mathematics, science, English, and art. We also conduct similar interviews with faculty in these fields who are responsible and knowledgeable for undergraduate programs about their perceived benefits for the structure of their program’s curriculum. Additional information is collected from noticing the organizational and pedagogical structures of the relative undergraduate curriculum. Initial findings/outcomes suggest that traditions to knowledge construction both differ across disciplinary approaches and have similarities across non-obvious disciplinary relationships. Faculty have a firm understanding of how one class chains from one to another; students have less of a field of view for how mindful chunks of knowledge combine together.  more » « less
Award ID(s):
2010696
NSF-PAR ID:
10214811
Author(s) / Creator(s):
Date Published:
Journal Name:
2020 ASEE Virtual Annual Conference
Format(s):
Medium: X
Sponsoring Org:
National Science Foundation
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