## 2 Literature Review
### Previous Studies on Adaptive Learning Systems  
Adaptive learning systems, as the prior confluence between technology and pedagogy, have been given significant research coverage, enabling personalized education to grow. Such systems use algorithms to modify learning content and paths on the fly, considering each learner's specific demands. Earlier research in this area has mostly focused on the effectiveness and implications of these adaptive systems in differing school contexts [18].  
A large body of literature has shown the benefits of adaptive learning systems on students' engagement and attainment in studies. Research has shown that such systems can dramatically improve learning outcomes by offering a tailored, learner-sensitive learning experience [19]. For example, [PERSON] et al. reported a significant increase in student outcomes in mathematics by introducing adaptive learning technologies.  
The research has also addressed the cognitive component of adaptive learning [20]. For instance, in his study, [PERSON] investigated the use of adaptive systems to minimize cognitive overload for learners by offering information in pieces that suit the learners' level of knowledge. This technique demonstrated high rates of comprehension and retention.  
Another area of inquiry has involved adaptive learning systems in developing inclusive education [21]. Studies have been conducted to determine the possibility of designing such systems for varied learners, including special needs students. According to [PERSON] et al. adaptive technologies can be used to provide learning equity for students with a disability, wherein personalized adaptations in the learning material fill in the gap of learning.  
Several other studies have been published that address the combination of adaptive learning systems and other pedagogical strategies. Similarly, [PERSON] and [PERSON] incorporated the use of adaptive technologies into project-based learning, with their research showing that this integration can promote critical thinking and problem-solving skills.  
In conclusion, by reference to existing research about adaptive learning systems, it is clear that they can be transformative in the education sector. Such systems help create a more effective and inclusive educational environment as they personalize learning experiences and address diversified learning needs. The evidence from these studies provides a strong case for the increased use of adaptive learning technologies in education.  
To illustrate the impact of previous studies on adaptive learning systems, Table 2 summarizes key research and their contributions:  
\begin{table}
\begin{tabular}{p{142.3 pt} p{142.3 pt}} \hline
**Theory** & **Contribution to Personalized Learning** \\ \hline \multirow{3}{*}{Constructivist Theory} & Emphasizes active learning where learners build upon existing knowledge; underscores the need for learning experiences tailored to individual cognitive structures. \\ \hline \multirow{3}{*}{Cognitive Load Theory} & Advocates for instructional designs optimized for cognitive resources; aims to balance content complexity and pacing to suit individual learner capacities. \\ \hline \multirow{3}{*}{Theory of Multiple Intelligences} & Suggests varied strengths and learning preferences (linguistic, logical, spatial, kinesthetic, etc.); involves creating diverse learning pathways catering to these intelligences. \\ \hline \multirow{3}{*}{Zone of Proximal Development (ZPD)} & Proposes optimal learning occurs in tasks that are achievable with appropriate guidance; personalized learning adjusts task difficulty to remain within the learner’s ZPD. \\ \hline \multirow{3}{*}{Self-Regulated Learning} & Highlights the importance of learner autonomy and motivation; personalized learning environments empower learners to control their learning journey. \\ \cline{2-3}  & \\ \end{tabular}
\end{table}
Table 1: Theories underpinning personalized learning and their contributions.