Scaffolding model for efficient programming learning based on cognitive load theory

Quick take
Worked-example and goal free problem solutions reduce mental effort in learning programming.

Syahanim Mohd Salleh, Zarina Shukur and Hairulliza Mohamad Judi

International Journal of Pure and Applied Mathematics

Volume 118 No. 7 2018, 77-83

ISSN: 1311-8080 (printed version); ISSN: 1314-3395 (on-line version)

Abstract: Programming learning for beginners requires tremendous amount of exposure to understand the logic in each programming solution using the basic concepts despite the overwhelming syntax it might carries. Learning programming through examples with careful walkthrough builds learners' confidence to embark with problems of any designs, avoids frustration due to syntax error and unintentional bugs. Scaffolding involves meta-programming approach of building software applications using supported materials that provides some inspiration of how the program could be developed. This research identifies important attributes in programming and proposes a scaffold model to enhance programming learning efficiency especially among novice programmers. The study applies cognitive load theory by providing users with two types of instructional design as learning support to reduce mental effort applied in the working memory i.e. worked-example and goal free programming problem solutions. The model is expected to help instructors in systematically organizing programming materials for any language or programming environment for efficient programming learning.