Designing for Interdisciplinary Transfer to Reduce Intrinsic Cognitive Load, Increase Self-Efficacy, and Promote Conceptual Understanding in Introductory Programming
Year: 2024
Type: conference-paper
Abstract: In this theoretical design paper, we describe using conjecture mapping to design an introductory computer science course curriculum to facilitate horizontal interdisciplinary transfer between algebra and programming. The bulk of this paper is an extended discussion of the empirical and theoretical justifications for and implications of three major conjectures, that instruction designed to encourage horizontal interdisciplinary transfer between algebra and computer science can (1) fulfill the requirements of horizontal inter-task transfer, increasing conceptual understanding in introductory programming, (2) decrease intrinsic cognitive load by drawing on students' latent prior knowledge in algebra, and (3) increase perceptions of experience in programming, preventing defensive classroom climates and increasing self-efficacy, particularly among students without conventional programming experience, who tend to be from underrepresented/minoritized groups. Next, we describe the design and fielding of this prototype course curriculum during a Summer 2022 synchronous remote introductory programming course at a large public research institution in the USA. Finally, we present a brief instructor experience report, with implications and future work.
Authors: Noah Q. Cowit, Lecia Barker
Institution: University of Colorado Boulder
Language: English
Subfield: Computer Science Applications
Field: Computer Science
Domain: Physical Sciences
SDG: Quality education
Open Access status: hybrid
OpenAlex ID: W4404316069