Abstract:

As artificial intelligence tools become ubiquitous in higher education, educators face a critical choice: resist these technologies or strategically integrate them to enhance learning. This presentation shares findings from a semester-long implementation of AI-enhanced pedagogy in First-Year Experience courses, demonstrating how intentional AI integration can enrich content, scaffold learning, and empower independent learners while preserving essential human connection.

Drawing from Fall 2025 implementation, this study presents a three-pillar framework:
(1) enriching content to make abstract concepts tangible,
(2) scaffolding complex skills development, and
(3) empowering autonomous learners. Student work samples illustrate how AI served as on-demand tutoring, helping students understand budgeting, visualize daily career activities, and develop metacognitive study strategies.

The presentation features authentic student voices revealing both successes and resistance. Students used AI to overcome barriers—one noted it provided "tutoring on demand," while another appreciated how it transformed abstract job descriptions into concrete schedules. However, several explicitly rejected AI for personal storytelling: "This story is mine—I do not want a robot helping me tell it." This resistance offers insights into students' evolving AI relationships and the importance of maintaining student agency.

Key findings address critical educator questions: How can faculty model responsible AI use? What happens when students learn to use AI as a collaborative tool rather than a thinking replacement? Student feedback reveals anxiety about academic integrity ("I'm scared I'll use AI the wrong way and get accused of cheating"), desire for instruction ("I wish professors would show us how to use it correctly"), and concerns about dependency ("I'm worried AI might make me lazy"). These concerns highlight the need for transparent, pedagogically sound AI integration.

The presentation includes detailed assignment design examples, including an AI-enhanced public narrative project where students used AI to brainstorm structures and research context while maintaining authorship. Rubrics, prompts, and assessment strategies demonstrate how to evaluate AI-incorporated work while ensuring genuine learning. Evidence shows that positioning AI as a thinking partner rather than content generator develops stronger metacognitive awareness and more sophisticated work.

This research contributes to AI literacy scholarship by centering student perspectives and providing replicable strategies. Findings challenge binary thinking—neither embracing AI as panacea nor rejecting it as threat—positioning it as an ambient tool that, when thoughtfully integrated, enhances but never replaces irreplaceable human teaching elements: empathy, connection, and helping students envision their potential.

As one student stated, "AI is like training wheels—it helps at first, but I still need my professor to help me learn how to ride the bike." This presentation argues our educator role remains unchanged: to listen, connect, and guide students toward potential, ensuring teaching stays transformational rather than transactional.

Keywords:

Artificial intelligence, pedagogy, first-year experience, AI literacy, student perspectives, educational technology, scaffolding, metacognition.