From AI to We: Harnessing Generative AI Tools to Cultivate Collaborative Learning Ecosystems in Universities

FX. Risang Baskara

Abstract


This paper proposes a new descriptive framework that offers the adoption of Generative AI towards building ecology-based collaborative learning platforms in higher education. With the exponential growth of advanced technologies like ChatGPT, Claude, Google Gemini, and many other AI-based platforms entering new boundaries, redefining education frameworks has enormous potential. We present the AI-enabled collaborative Learning Ecosystems (AI-CLE) model, which combines socio-constructivist theory, connectivism, and the Community of Inquiry framework to reconceptualise how learners, educators, and AI can function together as dynamic educational ecosystems. The paper explores mechanisms through which AI can facilitate personalised learning pathways, cognitive augmentation, collaborative problem-solving, and peer learning. We also examine the opportunities and challenges of using AI-CLEs in education; these include questions relating to equity, academic integrity, and data privacy. The implications for higher education pedagogy are mentioned, focusing on the need for curriculum redesign, the changing face of educators' roles, and innovative assessment methodologies. This paper provides a theoretical basis for the interaction between humans and artificial intelligence in educational ecosystems, thereby suggesting research directions and practical implementations of AI technologies that can make interactions much more effective before being deployed on a bigger scale.

 

Keywords


Educational Technology; EFL Pedagogy; Generative AI; Higher Education; Language Learning

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References


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