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

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.

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Publication Details

Journal
Computer Science Engineering and Technology
Published
2024-09-06
DOI
https://doi.org/10.46632/cset/2/3/3
Citations
1
Primary Topic
Online Learning and Analytics
Type
article
Field-Weighted Citation Impact
0.41
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article

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

Rohit Kumar Gupta, Aishwarya Gadikar
1 citations
Computer Science Engineering and Technology
Online Learning and Analytics
0.41
article

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

Rohit Kumar Gupta, Aishwarya Gadikar
article en
1 citations

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.

Computer Science Engineering and TechnologyVol. 2(3)
MIT World Peace University (IN)
Openalex Percentile: Top 27%
Online Learning and Analytics
0.41
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Evaluating and Enhancing User Interaction in AI-Driven Educational Tools: A Comparative Study of Machine Learning Algorithms and Design Principles — Rohit Kumar Gupta, Aishwarya Gadikar · Computer Science Engineering and Technology (2024) | TGRS Research Map | TGRS