Abstract:

In the ever-evolving landscape of education, the pursuit of effective teaching methodologies has led to the exploration of personalized learning experiences tailored to meet the unique needs and preferences of each learner. The traditional educational paradigm, characterized by a uniform, one-size-fits-all approach, has increasingly been recognized for its limitations, particularly in the context of developing critical thinking skills. Critical thinking, defined as the objective analysis, evaluation, and synthesis of information to form a judgment, stands as a cornerstone of lifelong learning and adaptability, essential for navigating the complexities of the modern world.

The emergence of Artificial Intelligence (AI) as a transformative force across various sectors has paved the way for its integration into educational strategies, offering unprecedented opportunities for personalization. By harnessing the power of AI, educators can now create adaptive learning environments that adjust in real-time to the individualized learning trajectories of students. This paper delves into the potential of AI to revolutionize critical thinking education by personalizing learning experiences, thereby enhancing student engagement and learning outcomes. The research question guiding this exploration is: "How can AI be utilized to tailor critical thinking exercises to individual learning styles?"

As a methodology, the study considers a literature review focused on finding intersections of personalized learning, critical thinking, and AI in education, by analyzing studies based on dimensions such as relevance to personalized learning, impact on critical thinking, innovative use of AI, scalability, empirical support, ethical considerations, integration with existing systems, student engagement, and teacher involvement. The literature review was conducted using the AI academic search engine Consensus to identify relevant sources. All 19 research papers that matched the research question raised by the current work were analyzed. The authors made a comparative assessment of each research paper across the relevant dimensions. The analyzed research papers were ranked on a scale from 0 to 5 for each dimension, where: 0 indicates that the dimension is not covered at all; and 5 denotes deep coverage and analysis, providing comprehensive insights, evidence, and forward-looking perspectives.

Key findings indicate that AI-driven adaptive learning can dynamically adjust educational content, promote student engagement, and improve learning outcomes, validating the effectiveness of AI in personalizing learning paths and providing real-time feedback, thereby enhancing critical thinking skills. As a result of the research, an AI-based framework is proposed for integrating personalized learning paths, problem-based learning modules, and advanced AI technologies to enhance critical thinking. The framework also emphasizes ethical considerations, seamless integration with existing systems, and teacher involvement. This research provides a roadmap for leveraging AI in education to meet diverse learner needs and suggests future empirical evaluations of the framework to assess long-term impacts.

Keywords:

Artificial Intelligence in Education, Personalized Learning, Critical Thinking Development, Learning Styles Adaptation, Intelligent Tutoring Systems.