Design and Impact: A Comparative Evaluation of User Interfaces in AI Educational Tools

This study investigates the influence of AI-driven educational tools on user experience and learning outcomes, with a focus on intelligent tutoring systems,
automated grading, and predictive analytics. It explores the role of large language models (LLMs) in educational assessment, incorporating insights from STEM
educators utilizing AI-enhanced writing support. Through a systematic review, the research identifies key ethical concerns, risks, and challenges associated with
AI adoption in higher education. The findings underscore the significance of teacher perceptions, ethical AI implementation, personalized learning approaches, and
the enduring necessity of human judgment in AI-augmented educational environments. The study contributes to ongoing discussions on optimizing AI integration
while addressing pedagogical and ethical considerations.
Keywords:Educational Tools, AI In Education, Skills, Availability, Reliability