Development of a Machine Learning-Based Intelligent Career Guidance System for High School Students in Rwanda Using Random Forest Algorithm

1. Introduction 1.1 Background of Study 1.2 Problem Statement 1.3 Objectives of the Study 1.4 Significance of the Study 1.5 Structure of the Thesis 2. Literature Review 2.1 Overview of Career Guidance Systems 2.2 Machine Learning in Education 2.3 Random Forest Algorithm 2.4 Career Guidance in Rwanda 2.5 Existing Systems Analysis 3. Methodology 3.1 Research Design 3.2 Data Collection Techniques 3.3 Description of Dataset 3.4 Implementation of Random Forest 3.5 System Evaluation Metrics 4. System Design and Implementation 4.1 System Architecture Overview 4.2 User Interface Design 4.3 Backend Development Process 4.4 Integration of Machine Learning 4.5 System Testing Procedures 5. Results and Discussion 5.1 Analysis of System Performance 5.2 Interpretation of Results 5.3 Comparison with Traditional Methods 5.4 Challenges Faced 5.5 Improvements and Modifications 6. Impact on High School Students 6.1 User Feedback and Satisfaction 6.2 Influence on Career Choices 6.3 Educational Outcomes 6.4 Accessibility and Reach 6.5 Long-term Benefits 7. Limitations and Future Work 7.1 Identified Limitations 7.2 Proposed Enhancements 7.3 Scalability Considerations 7.4 Future Research Directions 7.5 Technological Advancements 8. Conclusion 8.1 Summary of Findings 8.2 Contributions to Field 8.3 Final Remarks 8.4 Policy Implications 8.5 Recommendations for Implementation