Enhancing AI-Driven Education: Integrating Cognitive Frameworks, Linguistic Feedback Analysis, and Ethical Considerations for Improved Content Generation

TL;DR

This paper proposes a comprehensive framework combining cognitive, linguistic, and ethical considerations to improve AI-driven educational content generation, demonstrated through an AI-powered quiz tool.

Contribution

It introduces an integrated approach for developing responsible AI educational tools using cognitive assessment, linguistic feedback analysis, and ethical principles.

Findings

Framework effectively guides AI content development in education

Integration of cognitive and ethical considerations improves content quality

Demonstrated application in Moodle plugin enhances quiz generation

Abstract

Artificial intelligence (AI) is rapidly transforming education, presenting unprecedented opportunities for personalized learning and streamlined content creation. However, realizing the full potential of AI in educational settings necessitates careful consideration of the quality, cognitive depth, and ethical implications of AI-generated materials. This paper synthesizes insights from four related studies to propose a comprehensive framework for enhancing AI-driven educational tools. We integrate cognitive assessment frameworks (Bloom's Taxonomy and SOLO Taxonomy), linguistic analysis of AI-generated feedback, and ethical design principles to guide the development of effective and responsible AI tools. We outline a structured three-phase approach encompassing cognitive alignment, linguistic feedback integration, and ethical safeguards. The practical application of this framework is demonstrated through its integration into OneClickQuiz, an AI-powered Moodle plugin for quiz generation. This work contributes a comprehensive and actionable guide for educators, researchers, and developers aiming to harness AI's potential while upholding pedagogical and ethical standards in educational content generation.