Abstract:

This study explores the application of artificial intelligence (AI) and machine learning (ML) in educational settings to enhance student learning outcomes, with a focus on evaluating interactions and trust between students and AI systems. The paper introduces an AI-based virtual assistant framework, emphasizing personalization and interactive learning.

Understanding the interaction between students and AI is becoming increasingly important in the technology-infused landscape of education. This research addresses the challenge of comprehensively grasping how students engage with AI tools and the extent of their trust in these technologies. It examines the role of AI and ML in enriching traditional educational methods by integrating technological innovation into human-centric educational practices.

The study aims to demonstrate the positive effects of AI and ML in education, with an emphasis on improving educational outcomes. It investigates the level of student engagement and trust in AI assistants and assesses how these factors influence the learning process. Additionally, the paper provides strategic insights into integrating AI into educational environments, aiming to enhance learning experiences and student-teacher interactions.

The design of the application involves AI-driven virtual assistants, customized to individual student needs and learning styles. These assistants offer personalized educational resources and track student progress, focusing on adaptive and responsive learning experiences. The impact of AI interactions is measured through various metrics, including student engagement, academic performance, and trust in the technology.

Initial findings of this work-in-progress study highlight that regular interaction with AI assistants leads to enhanced understanding and memory retention in students. The study also investigates the factors contributing to building trust in AI systems, with preliminary observations indicating the importance of the ethical dimensions of AI in education. Factors like accuracy, adaptability, and personalization are examined for their role in ethical AI usage and in cultivating trust among students. These observations are fundamental in understanding how AI can effectively enhance learning and establish engaging, trusted human-machine relationships. The study is ongoing, with further data gathering and detailed analysis planned to enrich our understanding of these crucial aspects.

Keywords:

Artificial Intelligence, machine learning, human-machine interaction, trust in AI, personalization in education, AI-based virtual assistants, adaptive learning, technology integration in education.