2024 ASEE Annual Conference & Exposition

Student Experiences with Parsons Problems in a First-Year Engineering Course

Presented at Programming Education 2

Computational skillsets have become ubiquitous in introductory engineering courses to equip the next generation of engineers to solve modern-day problems during the technological age. Computing Education Researchers focused on improving computing curriculum development, assessment mechanisms, and computational activities to support learning in these contexts. Programmers in the elementary stages of development are challenged with disentangling the dense syntactical thinking prescribed in code creation requiring innovative approaches to pedagogical decisions in aligning activities that proactively mitigate these challenges. One such computational activity, Parsons Problems, is an effective tool to support introductory programmers in mitigating frustration associated with syntactical debugging for students, contributing to attrition in beginner programmers. Parsons Problems are grounded in Cognitive Load Theory to reduce extrinsic cognitive load by separating syntactical thinking from code writing, thus supporting a wide range of computing mastery as well, which is often the landscape in first-year engineering programs. Despite the support that Parsons Problems provides they have not been significantly studied to better understand diverse student experiences when engaging with these computational activities. This study, at a First-Year Engineering Program at a large midwestern university, works to identify the features of these activities that impact the student experience and prioritize these features for optimization by understanding the prevalence of student experiences by feature. Using a thematic codebook, eleven unique features of Parsons Problems were identified that impact student experiences when engaging with them including difficulty, group dynamics, and accessibility. Utility value and group dynamics were found to be the most frequent features to positively impact student experiences, while the difficulty was found to be the most consistent critique suggested further investigation into ways to optimize these learning tools to better support student learning in computing concepts.

Authors
  1. Abbey Darya Kashani Motlagh The Ohio State University
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