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Introduction

Automated scoring models have become increasingly popular in educational assessment as a way to efficiently and reliably evaluate student performance. However, concerns have been raised about the fairness of these models, particularly in the context of standardized tests. This thesis examines the fairness evaluation of automated scoring models used in standardized tests, with a focus on understanding the implications for test takers and the validity of test results.

1.2 Background of Study
1.3 Problem Statement
1.4 Objective of Study
1.5 Limitation of Study
1.6 Scope of Study
1.7 Significance of Study
1.8 Structure of the Thesis
1.9 Definition of Terms

Chapter Two: Literature Review
2.1 Overview of Automated Scoring Models
2.2 Fairness in Educational Assessment
2.3 Bias in Automated Scoring Models
2.4 Validity and Reliability in Test Scoring
2.5 Ethical Considerations in Automated Scoring
2.6 Methods for Evaluating Fairness in Test Scoring
2.7 Existing Research on Fairness Evaluation in Automated Scoring
2.8 Implications of Fairness Issues in Standardized Testing
2.9 Best Practices for Ensuring Fairness in Test Scoring
2.10 Future Directions for Research in Fairness Evaluation of Automated Scoring Models

Chapter Three: Research Methodology
3.1 Research Design
3.2 Data Collection Methods
3.3 Sampling Procedures
3.4 Data Analysis Techniques
3.5 Instrument Development
3.6 Ethical Considerations
3.7 Pilot Testing
3.8 Data Analysis Plan

Chapter Four: Discussion of Findings
4.1 Overview of Findings
4.2 Analysis of Fairness Issues in Automated Scoring Models
4.3 Implications of Findings for Validity and Reliability
4.4 Comparison of Different Scoring Models
4.5 Recommendations for Improving Fairness in Test Scoring
4.6 Limitations of the Study
4.7 Future Research Directions
4.8 Conclusion

Chapter Five: Conclusion and Summary
5.1 Summary of Findings
5.2 Conclusion
5.3 Implications for Practice
5.4 Recommendations for Policy
5.5 Contribution to the Field of Educational Assessment

Thesis Overview

Automated scoring models have revolutionized the field of educational assessment by providing a fast and efficient way to evaluate student performance on standardized tests. However, concerns have been raised about the fairness of these models, particularly in terms of bias and validity. This thesis aims to explore the fairness evaluation of automated scoring models used in standardized tests, with a focus on understanding the implications for test takers and the validity of test results.

Chapter one provides an introduction to the thesis, including background information on the topic, the problem statement, objectives of the study, limitations and scope of the study, significance of the study, structure of the thesis, and definition of terms. Chapter two presents a comprehensive literature review on automated scoring models, fairness in educational assessment, bias in scoring models, validity and reliability in test scoring, ethical considerations, methods for evaluating fairness, existing research on fairness evaluation, implications of fairness issues, and best practices for ensuring fairness.

Chapter three outlines the research methodology, including research design, data collection methods, sampling procedures, data analysis techniques, instrument development, ethical considerations, pilot testing, and data analysis plan. Chapter four discusses the findings of the study, including an analysis of fairness issues in automated scoring models, implications for validity and reliability, comparison of scoring models, recommendations for improving fairness, limitations of the study, future research directions, and a conclusion.

Chapter five provides a conclusion and summary of the thesis, including a summary of findings, implications for practice, recommendations for policy, and contribution to the field of educational assessment. Overall, this thesis seeks to contribute to the ongoing dialogue on fairness evaluation in automated scoring models and provide insights for improving the validity and reliability of standardized tests.

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