Abstract:
This research paper aims to develop a natural language processing (NLP) system for automated essay grading. The objective is to create a reliable and efficient tool that can accurately assess and grade essays, reducing the burden on human graders and providing timely feedback to students. The proposed system utilizes advanced NLP techniques to analyze various linguistic features, such as grammar, vocabulary, coherence, and argumentation, to evaluate the quality of essays. The research also explores the challenges and limitations of automated essay grading and suggests potential areas for future improvement.

Table of Contents:

Chapter 1: Introduction
1.1 Background
1.2 Problem Statement
1.3 Research Objectives
1.4 Significance of the Study
1.5 Scope and Limitations
1.6 Organization of the Paper

Chapter 2: Literature Review
2.1 Overview of Automated Essay Grading
2.2 Existing Approaches and Systems
2.3 Evaluation Metrics for Essay Grading
2.4 NLP Techniques for Essay Analysis
2.5 Challenges and Limitations

Chapter 3: Methodology
3.1 Data Collection and Preprocessing
3.2 Feature Extraction
3.3 Machine Learning Algorithms
3.4 Model Training and Evaluation
3.5 System Architecture

Chapter 4: Implementation and Results
4.1 System Implementation
4.2 Experimental Setup
4.3 Evaluation Metrics and Results
4.4 Comparison with Human Graders
4.5 Discussion of Findings

Chapter 5: Conclusion and Future Work
5.1 Summary of Findings
5.2 Contributions of the Study
5.3 Implications and Applications
5.4 Recommendations for Future Research
5.5 Conclusion