Development of an Intelligent Tutoring System for Personalized Learning

Thesis Abstract

Abstract
This thesis presents the development of an Intelligent Tutoring System (ITS) for personalized learning, aiming to enhance the learning experience by providing individualized instruction tailored to the unique needs and learning styles of students. The system incorporates artificial intelligence techniques to adapt and personalize the learning process, offering students a more engaging and effective way to acquire knowledge and skills. The research focuses on designing and implementing an ITS that can analyze student performance, provide targeted feedback, and generate customized learning paths to optimize learning outcomes. The introduction section provides an overview of the project, highlighting the importance of personalized learning in education and the potential benefits of using an ITS to support this approach. The background of the study reviews existing literature on ITS, personalized learning, and artificial intelligence in education, laying the foundation for the research. The problem statement identifies the gaps in current educational systems and the need for personalized learning solutions to address individual differences among students. The objectives of the study outline the specific goals of developing the ITS, including improving student engagement, increasing retention rates, and enhancing learning outcomes. The limitations of the study acknowledge the constraints and challenges faced during the research process, such as resource limitations and technical constraints. The scope of the study defines the boundaries of the research, specifying the target audience, learning objectives, and technologies used in the development of the ITS. The significance of the study emphasizes the potential impact of the ITS on education, highlighting its role in promoting personalized learning, fostering student autonomy, and enhancing overall learning experiences. The structure of the thesis provides an overview of the organization of the research, outlining the chapters and sub-sections included in the document. The definition of terms clarifies key concepts and terminology used throughout the thesis, ensuring a common understanding of the project scope and objectives. The literature review chapter explores existing research on ITS, personalized learning models, and artificial intelligence applications in education. It examines relevant studies, frameworks, and technologies to inform the design and development of the ITS. The research methodology chapter details the research design, data collection methods, participant selection criteria, and evaluation metrics used to assess the effectiveness of the ITS. The discussion of findings chapter presents the results of the research, including user feedback, performance metrics, and system evaluations. It analyzes the impact of the ITS on student learning outcomes, engagement levels, and satisfaction rates. The conclusion and summary chapter provides a comprehensive overview of the research findings, implications for practice, and recommendations for future work. In conclusion, the development of an Intelligent Tutoring System for personalized learning represents a significant contribution to the field of educational technology. By leveraging artificial intelligence and personalized learning approaches, the ITS offers a promising solution to address the diverse learning needs of students and enhance the overall quality of education. This research lays the groundwork for future advancements in adaptive learning systems and underscores the importance of individualized instruction in promoting student success and academic achievement.