AI in Online Education

Abstract

As artificial intelligence (AI) becomes an integral component of online education, important questions arise about how it influences learner trust, engagement, and preferences for various instructional models. This study investigates user perceptions of AI-powered tools in online learning by performing a structured survey. The survey evaluates trust in AI-generated study materials, engagement with AI-driven features, and preferences for AI-assisted instructional formats. To analyze these perceptions, the authors test four main hypotheses: (H1) trust in AI-generated educational content and AI-powered instructors, (H2) the impact of AI-driven tools on engagement and personalization, (H3) AI's influence on learning preferences and instructional models, and (H4) perceptions of AI-powered tools in engineering design education. The study uses statistical analyses, including ANOVA, to assess differences in trust and engagement based on prior AI experience and K-Means clustering to identify separate user trust profiles. Results show that frequent AI users are more comfortable with AI-generated study materials but are cautious about fully autonomous AI-driven instruction. Responses about engagement with AI-powered features showed mixed interest in real-time AI feedback, chat moderation, and interactive learning tools. Instructional preferences show a strong preference for hybrid models where AI supplements, rather than replaces, human instruction. In engineering design education, respondents value AI-assisted design tools, particularly for simulations and automated feedback, but emphasize the need for human validation.

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