Basic-element Based Learning Method Integrate Fragmented Knowledge.

In the era of big data, the fragmentation of knowledge poses significant challenges to learners, especially college students, who often struggle to integrate disparate pieces of information into a coherent knowledge system. To address this issue, this paper introduces a novel Basic-Element Learning Method (BELM), which is deeply rooted in the theoretical framework of Extenics, to address the integration of fragmented knowledge. The BELM utilizes basic-element models to represent knowledge, and through the application of extensible analysis and conjugate analysis, it effectively integrates fragmented knowledge. The basic-element learning method represents knowledge using basic-element models and then employs extensible analysis and conjugate analysis to achieve knowledge integration. This study applies the basic-element learning method to the knowledge learned by college students and demonstrates its effectiveness. Experimental results demonstrate the efficacy of the BELM in improving students' ability to synthesize information and build robust knowledge frameworks. This study not only contributes to the field of educational technology but also provides valuable insights for educators and learners alike in the face of the ever-increasing complexity of knowledge in the modern world. [ABSTRACT FROM AUTHOR]