Thesis Abstract

Abstract
The rapid growth of technology in recent years has significantly transformed the education sector, particularly in the field of programming education. This thesis focuses on the development of an Intelligent Tutoring System (ITS) tailored for programming education to enhance the learning experience of students. The primary goal of this research is to design and implement an ITS that can provide personalized and adaptive support to students learning programming concepts. The first chapter of this thesis provides an introduction to the research topic, including the background of the study, problem statement, objectives, limitations, scope, significance, and structure of the thesis. The second chapter presents a comprehensive literature review covering ten key aspects related to intelligent tutoring systems, programming education, machine learning algorithms, and educational technologies. Chapter three outlines the research methodology employed in this study, detailing the research design, data collection methods, system development approach, evaluation techniques, and ethical considerations. The methodology includes the development of the ITS prototype, incorporating machine learning algorithms for personalized feedback and adaptive learning. In the fourth chapter, the findings from the implementation and evaluation of the ITS are discussed in detail. The results highlight the effectiveness of the system in providing personalized support to students, improving their programming skills, and enhancing their overall learning outcomes. The discussion also addresses challenges encountered during the development process and potential areas for future research and improvement. Finally, the fifth chapter presents the conclusion and summary of the thesis, summarizing the key findings, implications, and contributions of the research. The conclusion highlights the significance of the developed ITS in programming education and its potential impact on improving student learning experiences. Recommendations for further research and the practical implementation of the ITS in educational settings are also provided. Overall, this thesis contributes to the field of programming education by developing an Intelligent Tutoring System that leverages machine learning techniques to enhance the learning process for students. The research outcomes demonstrate the potential of ITS in providing personalized and adaptive support, ultimately improving student engagement, performance, and understanding of programming concepts.

Thesis Overview

The project titled "Developing an Intelligent Tutoring System for Programming Education" aims to address the challenges faced in programming education by creating an advanced system that can provide personalized guidance and support to learners. In recent years, the demand for programming skills has increased significantly, making it crucial for educational institutions to enhance their teaching methods in this area. Traditional classroom settings may not always cater to the individual needs of students, leading to varied levels of understanding and engagement among learners. The proposed Intelligent Tutoring System (ITS) will leverage artificial intelligence and machine learning algorithms to adapt to the unique learning styles and preferences of each student. By analyzing student performance, behavior, and interactions, the system will be able to generate tailored lesson plans, exercises, and feedback to optimize the learning experience. This personalized approach is expected to enhance student engagement, motivation, and ultimately, improve learning outcomes in programming education. Furthermore, the ITS will incorporate interactive features such as real-time coding challenges, virtual programming environments, and instant feedback mechanisms to provide a hands-on learning experience for students. By simulating real-world scenarios and offering immediate guidance, the system aims to cultivate problem-solving skills, critical thinking, and creativity among learners. Additionally, the system will track student progress over time, allowing educators to monitor individual performance and identify areas for improvement. The research will involve the design, development, and evaluation of the ITS, considering factors such as usability, effectiveness, and student satisfaction. Data collected from user interactions, assessments, and surveys will be analyzed to measure the impact of the system on student learning outcomes. The research methodology will include a combination of qualitative and quantitative approaches to gather comprehensive insights into the effectiveness of the ITS in programming education. Ultimately, the project seeks to contribute to the advancement of programming education by introducing an innovative and interactive learning platform that caters to the diverse needs of learners. By harnessing the power of artificial intelligence and personalized learning techniques, the Intelligent Tutoring System aims to revolutionize the way programming is taught and learned, paving the way for a more engaging, effective, and inclusive educational experience.