Learning Programming Languages as Shortcuts to Natural Language Token Replacements
Article No.: 1, Pages 1 - 10
Abstract
The basic knowledge of computer programming is generally considered a valuable skill for educated citizens outside computer science and engineering professions. However, learning programming can be a challenging task for beginners of all ages especially outside of formal CS education. This paper presents a novel source code editing method that assists novice users understand the logic and syntax of the computer code they type. The method is based on the concept of text replacements that interactively provide the learners with declarative knowledge and help them transform it to procedural knowledge, which has been shown to be more robust against decay. An active tokenization algorithm splits the typed code into tokens as they are typed and replaces them with a pre-aligned translation in a human natural language. The feasibility of the proposed method is demonstrated in seven structurally different natural languages (English, Chinese, German, Greek, Italian, Spanish, and Turkish) using examples of computer code in ECMAScript (JavaScript).
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Index Terms
- Learning Programming Languages as Shortcuts to Natural Language Token Replacements
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Reviews
Wolfgang Schreiner
Students learning programming languages initially struggle very much with the relationship between the formal syntax of the language and the intuitive interpretation of its meaning. The program text is composed of a sequence of special tokens according to an unfamiliar grammar; it may be difficult for novices to see how these sequences describe actions, which would be expressed very differently in one's native language. The paper's proposed approach bridges this gap between formal syntax and intuitive understanding: an editor applies a simple algorithm to replace programming language tokens, as soon as they are entered, with corresponding phrases in the programmer's native language; the result is a program whose basic elements are natural language phrases. Thus, the program's meaning becomes more transparent, and fundamental errors can be easily detected from unexpected translations. A pilot study demonstrates with statistical significance that, in assignments, students who previously used this editor make significantly less syntactical or logical errors than those students in the control group who used a conventional editor. The paper nicely illustrates how a simple technique can overcome some initial hurdles in programming language education. It may even help to raise interest in non-technically inclined target groups. The technique is, however, limited to the "word by word" translation of basic commands and expressions, without discussing more complex structural translations. Future work will concentrate on larger scale studies with more programming/natural languages and students in different countries.
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Published: 22 November 2018
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Koli Calling '18
Koli Calling '18: 18th Koli Calling International Conference on Computing Education Research
November 22 - 25, 2018
Koli, Finland
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