Cognitive Load in Programming Education: Easing the Burden on Beginners with REXX.
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| Title: | Cognitive Load in Programming Education: Easing the Burden on Beginners with REXX. |
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| Authors: | Winkler, Till, Flatscher, Rony G. |
| Source: | Central European Conference on Information & Intelligent Systems; 2023, p171-178, 8p |
| Subject Terms: | COGNITIVE load, COMPUTER programming, ARTIFICIAL intelligence |
| Abstract: | To learn and teach programming is very difficult, often leads to poor results, and causes many students to drop out or turn away from the subject. Cognitive load theory can help to understand the challenges students face, improve programming education, and select an appropriate language for instruction. In this paper, we take a theoretical look at programming education and, in particular, language characteristics that reduce students' cognitive load and thus enable rapid learning and frustration-free productivity. We introduce the REXX language and some of its favorable characteristics that make it possible to teach novices programming within a single semester. In this limited time, students are empowered to program Microsoft products (Windows, Office), address the command line, grasp the basics of objectoriented programming, use Java classes, and create portable graphical user interfaces (GUIs) with JavaFX. [ABSTRACT FROM AUTHOR] |
| Copyright of Central European Conference on Information & Intelligent Systems is the property of Faculty of Organization & Informatics and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.) | |
| Database: | Complementary Index |
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