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This research aims to understand how large language models influence programming skill development and conceptual understanding in students.

July 10, 2026AIOpen Access

How Large Language Models Shape Programming Skill Development Beyond Task Completion

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Randomized trial examines the relationship between LLM use and programming skills in students, suggesting deeper engagement enhances competence.

This research aims to understand how large language models influence programming skill development and conceptual understanding in students.
Analyzed survey data from 189 students regarding LLM usage in educational contexts.
Utilized partial least squares structural equation modeling (PLS-SEM) for analysis.
Focused on associations between student engagement levels, collaboration practices, and self-reported programming skills.
Students who actively engaged with AI outputs reported higher perceived programming competence.
Collaborative use of LLMs was linked to broader programming ability development.
Creative experimentation with AI responses improved stylistic aspects and knowledge retention.

Tihomir Orehovački (2026) studied this question.

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Randomized trial examines the relationship between LLM use and programming skills in students, suggesting deeper engagement enhances competence.