Faculty Advisor

Richards, Brad

Area of Study

Science and Mathematics

Publication Date

Summer 2019

Abstract

Growth in demand for employees with programming proficiency necessitates a workforce that is correctly and efficiently trained in programming fundamentals. Previous research has found correlations between intermediate programmers’ program-development habits and their success in computer science courses, but to date, these approaches have not worked well when predicting the success of students in their first course. This research project is an examination of the Normalized Programming State Model’s applicability to novice programmers, after modifying it to potentially improve its ability to detect flaws in the programs these students write. We compared the adapted model’s predictive power with that of the previous implementation of the model for novice programming data collected by BlueJ.

Award

McCormick

Publisher

University of Puget Sound

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