Comparison of Text-Based and Visual-Based Programming Input Methods for First-Time Learners

Abstract

Aim/Purpose: When learning to program, both text-based and visual-based input methods are common. However, it is unclear which method is more appropriate for first-time learners (first learners). Background: The differences in the learning effect between text-based and visual-based input methods for first learners are compared the using a questionnaire and problems to assess first learners’ understanding of programming. In addition, we study the benefits and feasibility of both methods. Methodology: In this research, we used the sandbox game Minecraft and the extended function ComputerCraftEdu (CCEdu). CCEdu provides a Lua programming environments for the two (text and visual) methods inside Minecraft. We conducted a lecture course on both methods for first learners in Japan ranging in age from 6 to about 15 years old. The lecture taught the basics and concepts of programming. Furthermore, we implemented a questionnaire about the attitude of programming before and after the lecture. Contribution: This research is more than a comparison between the visual method and the text method. It compares visual input and text input methods in the same environment. It clearly shows the difference between the programming learning effects of visual input and text input for first learners. In addition, it shows the more suitable input method for introductory education of first learners in programming learning. Findings: The following results are revealed: (1) The visual input method induces a larger change in attitude toward programming; (2) The number of operations and input quantity influence both groups; (3) The overall results suggest that a visual input is advantageous in a programming implementation environment for first learners. Impact on Society: A visual input method is better suited for first learners as it improves the attitude toward programming. Future Research: In the future, we plan to collect and analyze additional data as well as elucidate the correlation between attitudes and understanding of programming.

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