izvorni znanstveni rad
The adoption of generative artificial intelligence (GAI) tools has experienced rapid growth and widespread
usage, significantly impacting various industries, including software development. Recently, various AI
tools and services, commonly based on large language models, have demonstrated significant potential in
automatic code generation, code completion, and test case generation, but also more complex refactoring,
reverse engineering, and code comprehension in explaining and reasoning the code. These tools work
standalone or as extensions into integrated development environments (IDEs) to assist software developers
and elevate programming productivity, thus revolutionizing and streamlining the entire software
development process. Teaching and conducting programming and software development courses in higher
education have often posed various challenges, especially in an online environment with students with
insufficient programming experience. In recent years, various education programs in computing, computer
science, software engineering, and software development have faced many challenges and have taken
diverse approaches to solve them, particularly related to academic integrity and plagiarism detection.
However, the recent wide availability and omnipresence of GAI tools and services that are easily used by
students for various tasks in software development in an uncontrolled environment outside of a classroom
brought another considerable disruption that needs to be addressed. Our research presents a preliminary
analysis of the possibilities of using GAI tools and services in programming and software development
courses at the undergraduate level at the university of applied sciences in Croatia. Our goal was to elucidate
how these tools could enhance students' learning related to software development and motivate them to
acquire better programming skills based on practical assignments from the AI-assisted learning process in
an ethical and legal way. At the same time, we aimed to mitigate potential risks associated with academic
honesty, specifically related to plagiarism and the unallowed use of code generation. We base our research
on using these GAI tools to solve individual programming tasks and software development assignments in
undergraduate courses. We analyze the applicability of these tools for various programming tasks students
need to perform in a responsible way and compare their performance and the level of help they offer, as
well as the correctness and accuracy of results. Finally, we summarize the findings of our preliminary
analysis of examined GAI tools and services that could be used in undergraduate programming and software
development courses to enrich student comprehension and help educators.
Artificial intelligence tools; software development; programming; course; generative artificial intelligence
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