An Adaptive Approach for Knowledge Acquisition in the Age of AI

Abstract

The exponential growth of big data and artificial intelligence has fundamentally transformed how learners acquire knowledge. They frequently navigate through the internet and artificial intelligence application to gather necessary materials to fulfill their learning needs. In these cases, they often find themselves overwhelmed by the sheer volume and complexity of the available information. The challenge of learning becomes to acquiring meaning and gaining understanding through artificial intelligence generated materials. This study focuses on the core challenges of knowledge acquisition faced by the learners in the context of artificial intelligence generated information overload. By integrating the understandings of information search process with constructivism, this research proposes an adaptive framework comprising knowledge gap bridging component and personalization component. The framework can balance the cognitive load and facilitating knowledge construction. By matching the difficulty level of learning content to learner’ abilities, the study promote the gradual deepening of cognitive development.