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Introduction

The integration of artificial intelligence (AI) technology in educational testing has brought about numerous benefits, such as personalized learning experiences and efficient assessment processes. However, the use of AI in educational testing also raises complex legal issues related to student rights, privacy, and accountability. This thesis aims to explore these legal implications of AI in educational testing and examine the extent to which current legal frameworks protect students in the context of AI-driven testing.

Background of Study

This section provides an overview of the evolution of educational testing and the growing role of AI technology in shaping assessment practices. It also discusses the legal foundations that govern educational testing and highlights the need for updated regulations to address the unique challenges posed by AI.

Problem Statement

The increasing reliance on AI in educational testing raises concerns about the fairness, transparency, and accountability of assessment practices. This section identifies the key legal issues that arise from the use of AI in testing and highlights the potential impact on student rights and educational outcomes.

Objective of Study

This thesis aims to examine the legal implications of AI in educational testing with a focus on protecting student rights and ensuring accountability in assessment practices. The study seeks to identify gaps in current legal frameworks and propose recommendations for addressing emerging challenges in the use of AI in educational testing.

Limitation of Study

This section acknowledges the limitations of the study, including potential biases in the analysis of legal issues related to AI in educational testing. It also highlights the complex and rapidly evolving nature of AI technology, which may impact the generalizability of the study findings.

Scope of Study

The study will focus on legal implications of AI in educational testing within the context of student rights and accountability. It will examine relevant laws, regulations, and ethical guidelines that govern educational testing practices and assess their adequacy in addressing the challenges posed by AI technology.

Significance of Study

This thesis contributes to the ongoing debate on the legal implications of AI in educational testing and highlights the need for updated regulations to protect student rights and ensure the fairness of assessment practices. The findings of the study can inform policymakers, educators, and stakeholders in the development of legal frameworks that address the unique challenges posed by AI technology in educational testing.

Structure of the Thesis

This thesis is organized into five chapters. Chapter One provides an introduction to the study, including background information, problem statement, objectives, limitations, scope, significance, and the structure of the thesis. Chapter Two presents a literature review on the legal implications of AI in educational testing. Chapter Three outlines the research methodology, including data collection methods and analysis techniques. Chapter Four discusses the findings of the study, with a focus on the legal challenges and opportunities presented by AI in educational testing. Finally, Chapter Five offers a conclusion and summary of the key findings and recommendations.

Definition of Terms

– Artificial Intelligence (AI): The simulation of human intelligence processes by machines, especially computer systems.
– Educational Testing: The assessment of students’ knowledge, skills, and abilities through various assessment methods.
– Student Rights: Legal protections and entitlements afforded to students in educational settings.
– Accountability: The obligation of individuals or organizations to take responsibility for their actions and decisions.

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