## 1 Introduction
### Research Gap  
Together, these studies present a comprehensive overview of AI's role in computer science education, yet they reveal critical gaps in the research. While AI has been widely \begin{table}
\begin{tabular}{c c c c} \hline \hline
**Reference** &
\begin{tabular}{c} **Number of Sample Papers** \\ **(Time Range)** \\ \end{tabular} & **Field in Focus** & **Objective** \\ \hline
[3] & 54 (2013–2024) & AI and STEM Education &
\begin{tabular}{c} Analysis of how AI and ML can improve \\ educational outcomes, personalize \\ learning experiences, and address \\ critical issues in STEM fields \\ \end{tabular} \\ \hline
[5] & 28 (2011–2024) & AI and Computer Science
\begin{tabular}{c} Example how the integration of AI \\ affects learning outcomes in CS \\ education \\ \end{tabular} \\ \hline
[2] & 115 (2022–2023) & AI and Education &
\begin{tabular}{c} Explore the potential and challenges of \\ using advanced AI models in education \\ \end{tabular} \\ \hline
[1] & 15 (2012–2023) & AI, ChatGPT, and
\begin{tabular}{c} Explore the possibilities of ChatGPT for \\ education, programming, content \\ creation, and more \\ \end{tabular} \\ \hline
[6] & 26 (2009–2021) & ITS, AI, and Computer
\begin{tabular}{c} Analysis of the development and use of \\ ITS in CS education, with a focus on \\ AI-based techniques \\ \end{tabular} \\ \hline
[4] & 25 (2010–2020) & Educational AI and
\begin{tabular}{c} Analysis of the impact of AI and \\ computational sciences on student \\ achievement \\ \end{tabular} \\ \hline \hline \end{tabular}
\end{table} 
Table 1: Reviews on the use of AI in computer science education. explored in programming education and intelligent tutoring systems, its broader role in computer science instruction remains underexamined. Most existing studies provide a superficial exploration of AI in computer science, without a deeper analysis of its pedagogical frameworks or long-term impact. Notably, only three studies [4; 5; 6] primarily focus on computer science education, while others either address computational sciences partially, as in [1; 3], or do not explore them at all, as in [2]. This fragmented approach leaves important questions unanswered regarding how AI effectively supports learning and teaching strategies beyond programming. Another notable gap is the lack of a unified pedagogical framework for integrating AI into IT education, which raises questions about the consistency and validity of existing approaches. Another critical research gap concerns AI-assisted programming and the educational shift it brings [4]. While existing studies explore AI's role in programming education, they often fail to account for the broader transformation occurring in computer science as a discipline [5; 6]. The emergence of generative AI has ushered in novel paradigms, such as \"AI-native software development\", where programmers transition from their traditional roles as coders to becoming AI curators [1; 3]. However, there is limited research on how these changes should be reflected in educational frameworks. Specifically, the pedagogical implications of AI-driven automation in debugging, testing, and software development remain under-explored [2; 6]. While there has been some examination of AI in the context of intelligent tutoring and adaptive learning, there is a need for more research on how AI can support students in transitioning from conventional programming practices to AI-augmented development workflows [1; 3; 6]. Furthermore, despite the significance of databases as a core discipline in computer science, none of the reviewed studies explicitly examine AI's role in database instruction. While programming education has received substantial attention, databases, relational modeling, and query optimization remain underexplored areas in AI-driven education. Given the complexity of database concepts and students' difficulties in mastering SQL, AI-driven learning tools, such as chatbots or automated tutors, could provide valuable support, yet their effectiveness in this domain has not been systematically evaluated.