GenAI in the futrue
In the next decade, GenAI will become a core part of learning platforms, providing AI-powered tutoring agents that personalize learning experiences. This aligns with Vygotsky's social constructivist theory (1978), where knowledge is co-constructed through social interaction. AI will support collaboration between students and virtual agents, enabling personalized feedback and adaptive learning paths tailored to individual needs. Moreover, Zimmerman's theory of self-regulated learning (2000) suggests that learners can enhance their outcomes through goal setting and self-monitoring, which can be further supported by AI-driven learning analytics and personalized dashboards. A study by Luckin et al. (2016) explores how AI-based systems can enhance learning by adapting educational experiences in real-time. This work highlights the role of AI in fostering individualized learning, supporting learners’ cognitive and emotional needs, and creating more inclusive educational environments.
In 20 years, GenAI will be fully integrated into intelligent tutoring systems (ITS) and immersive learning environments. The connectivist theory proposed by Siemens (2005) suggests that learning is a process of connecting nodes of information. GenAI could function as a facilitator in these networks, guiding students through learning pathways and enhancing their ability to acquire new knowledge by interacting with virtual peers and tutors. Additionally, AI-enhanced immersive technologies like Virtual Reality (VR) and Augmented Reality (AR) will allow students to engage in experiential learning, applying theoretical knowledge in practical, simulated environments. Holmes et al. (2019) discuss the future of AI in education, proposing that AI will move beyond providing personalized content to creating entire learning ecosystems that adapt to students’ evolving needs. This vision emphasizes AI's role in fostering deep, experiential, and collaborative learning.
For the theoretical framework for integration, The TPACK framework (Technological Pedagogical Content Knowledge) by Mishra and Koehler (2006) provides a solid foundation for integrating GenAI in educational contexts. Effective integration of technology in education requires a balance between technological knowledge, pedagogy, and content. Educators will need to acquire new competencies to effectively leverage GenAI’s capabilities in the classroom, ensuring that it enhances rather than replaces traditional pedagogical approaches.
References：
Luckin, R., Holmes, W., Griffiths, M., & Forcier, L. B. (2016). Intelligence unleashed: An argument for AI in education. Pearson.
Mishra, P., & Koehler, M. J. (2006). Technological pedagogical content knowledge: A framework for teacher knowledge. Teachers College Record, 108(6), 1017-1054.
Siemens, G. (2005). Connectivism: A learning theory for the digital age. International Journal of Instructional Technology and Distance Learning, 2(1), 3-10.
Vygotsky, L. S. (1978). Mind in society: The development of higher psychological processes. Harvard University Press.
Zimmerman, B. J. (2000). Attaining self-regulation: A social cognitive perspective. In M. Boekaerts, P. R. Pintrich, & M. Zeidner (Eds.), Handbook of self-regulation (pp. 13-39). Academic Press.