Pedagogy with generative artificial intelligence: Opportunities and challenges in education
Abstract
Students using ChatGPT demonstrated significantly superior performance on AI-assisted assignments (p < 0.001), reporting benefits including time efficiency, personalized learning experiences, and enhanced conceptual understanding. However, these advantages came with notable trade-offs: the AI group scored lower on proctored examinations (p < 0.01), suggesting potential overreliance that may hinder independent learning capabilities. Student perceptions revealed this tension, with 71% acknowledging AI dependence for task completion while 58% expressed concerns about compromised learning depth. The research identifies critical risks accompanying AI integration: concerns about content accuracy, plagiarism vulnerabilities, ethical dilemmas, and the potential erosion of deep learning. Traditional assessment methods, particularly take-home assignments, proved inadequate in AI-enabled environments, highlighting the need for fundamental pedagogical restructuring. The authors advocate for comprehensive educational reform encompassing redesigned assessments that prioritize genuine understanding over AI-generated responses, institutional policy frameworks governing ethical AI use, and systematic AI literacy development among students and educators. The study emphasizes that generative AI's transformative potential, including personalized tutoring, immediate feedback, and content generation efficiency can only be realized through deliberate pedagogical innovation. The research calls for longitudinal studies examining sustained learning outcomes, discipline-specific AI applications, and development of evidence-based guidelines balancing educational enhancement with academic integrity preservation. Ultimately, the study positions generative AI as a "double-edged sword" requiring proactive adaptation from educational stakeholders to ensure it serves as a pedagogical ally rather than undermining educational foundations.
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