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Evaluating and Enhancing User Interaction in AI-Driven Educational Tools: A Comparative Study of Machine Learning Algorithms and Design Principles

Year: 2024

Type: article

Abstract: The integration of AI technologies in educational tools presents both opportunities and challenges in enhancing user interaction and learning outcomes. This paper explores the impact of various machine learning algorithms on the effectiveness of AI-driven educational tools, investigates ethical considerations in AI integration, and evaluates design principles to improve user experience. A comprehensive evaluation framework is proposed, combining performance metrics of machine learning algorithms with user-centered design principles. The study provides actionable insights for developing more effective and engaging educational tools, aiming to bridge the gap between technology and pedagogy.

Source: Computer Science Engineering and Technology

DOI: 10.46632/cset/2/3/3

Authors: Rohit Kumar Gupta, Aishwarya Gadikar

Institution: MIT World Peace University

Language: English

Topic: Artificial Intelligence in Education

Subfield: Information Systems

Field: Computer Science

Domain: Physical Sciences

SDG: Quality education

Open Access status: bronze

OpenAlex ID: W4402321359

FWCI: 0.387

Cites:

Cited by: 1

Related to: 10