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This content will become publicly available on June 1, 2023

Title: Reevaluating the relationship between explaining, tracing, and writing skills in CS1 in a replication study
Background and Context Lopez and Lister first presented evidence for a skill hierarchy of code reading, tracing, and writing for introductory programming students. Further support for this hierarchy could help computer science educators sequence course content to best build student programming skill. Objective This study aims to replicate a slightly simplified hierarchy of skills in CS1 using a larger body of students (600+ vs. 38) in a non-major introductory Python course with computer-based exams. We also explore the validity of other possible hierarchies. Method We collected student score data on 4 kinds of exam questions. Structural equation modeling was used to derive the hierarchy for each exam. Findings We find multiple best-fitting structural models. The original hierarchy does not appear among the “best” candidates, but similar models do. We also determined that our methods provide us with correlations between skills and do not answer a more fundamental question: what is the ideal teaching order for these skills? Implications This modeling work is valuable for understanding the possible correlations between fundamental code-related skills. However, analyzing student performance on these skills at a moment in time is not sufficient to determine teaching order. We present possible study designs for exploring this more actionable research question.
Authors:
; ; ; ; ;
Editors:
Dorn, Brian; Vahrenhold, Jan
Award ID(s):
2121424
Publication Date:
NSF-PAR ID:
10340072
Journal Name:
Computer Science Education
Page Range or eLocation-ID:
1 to 29
ISSN:
0899-3408
Sponsoring Org:
National Science Foundation
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