This innovative practice paper examines how Artificial Intelligence (AI) and Machine Learning (ML) can be integrated into education to improve student engagement and foster trust through prompt engineering, a method for designing AI prompts that encourage meaningful interactions. In the evolving landscape of educational technology, AI can personalize learning experiences, tailoring them to each student’s needs, abilities, and preferences. This paper reviews existing practices to show how AI can enhance engagement, comprehension, and retention by using adaptive virtual assistants that respond to students’ individual progress and provide tailored feedback.

A central focus is the role of trust in AI-based educational tools, as students are more likely to engage with AI when they find it reliable. The paper discusses how prompt engineering supports trust by making AI interactions feel transparent and dependable. This trust is essential for the success of AI in education, highlighting that effectiveness depends on technical functionality and ethical considerations like data privacy, security, and alignment with educational goals. These factors ensure AI benefits students fairly and respectfully.

This study finds that AI-powered virtual assistants can significantly enhance understanding and retention by offering on-demand support, guiding students through complex topics, and addressing gaps in knowledge. AI’s capacity to deliver personalized assistance outside the classroom allows students to gain deeper insights and engage with challenging material on their own terms.

The paper also discusses emerging trends such as adaptive learning, automated grading, and data-driven feedback systems that contribute to efficient, responsive educational environments. It advocates for continued research into AI’s long-term effects on education, particularly regarding its impact on student-teacher relationships, critical thinking skills, and the balance between automation and human oversight.

This work underscores the importance of integrating AI into education ethically and responsibly. As AI technology progresses, establishing guidelines becomes crucial to ensure that these tools support positive, meaningful learning experiences. A balanced approach to AI integration has the potential to transform educational outcomes, making learning accessible, personalized, and aligned with principles of equity and respect.

Keywords: Artificial intelligence, machine learning, graduate education, educational technology, student engagement, personalized learning, AI ethics, trust in AI, educational policy, adaptive learning, prompt engineering, philosophy of engineering education.