Content area

Abstract

Background: In times when the ability to program is becoming increasingly important, it is still difficult to teach students to become successful programmers. One remarkable aspect are recent findings from neuro-imaging studies, which suggest a consistent role of language competency of novice programmers when they learn programming. Thus, for effectively teaching programming, it might be beneficial to draw from linguistic research, especially from foreign language acquisition. Objective: The goal of this study is to investigate the feasibility of this idea, such that we can enhance learning programming by activating language learning mechanisms. Method: To this end, we conducted an empirical study, in which we taught one group of students an artificial language, while another group received an introduction into Git as control condition, before we taught both groups basic programming knowledge in a programming course. Result: We observed that the training of the artificial language can be easily integrated into our curriculum. Furthermore, we observed that language learning strategies were activated and that participants perceived similarities between learning the artificial language and the programming language. However, within the context of our study, we did not find a significant benefit for programming competency when students learned an artificial language first. Conclusion: Our study lays the methodological foundation to explore the use of natural language acquisition research and expand this field step by step. We report our experience here to guide research and to open up the possibilities from the field of linguistic research to improve programming acquisition.

Details

1009240
Title
Tapping into the Natural Language System with Artificial Languages when Learning Programming
Publication title
arXiv.org; Ithaca
Publication year
2024
Publication date
Jan 12, 2024
Section
Computer Science
Publisher
Cornell University Library, arXiv.org
Source
arXiv.org
Place of publication
Ithaca
Country of publication
United States
University/institution
Cornell University Library arXiv.org
e-ISSN
2331-8422
Source type
Working Paper
Language of publication
English
Document type
Working Paper
Publication history
 
 
Online publication date
2024-02-06
Milestone dates
2024-01-12 (Submission v1)
Publication history
 
 
   First posting date
06 Feb 2024
ProQuest document ID
2922679061
Document URL
https://www.proquest.com/working-papers/tapping-into-natural-language-system-with/docview/2922679061/se-2?accountid=208611
Full text outside of ProQuest
Copyright
© 2024. This work is published under http://creativecommons.org/licenses/by/4.0/ (the “License”). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License.
Last updated
2024-02-07
Database
ProQuest One Academic