Nursing teaching path personalized recommendation method and system fusing experience and scene

Abstract

The application relates to the technical field of intelligent teaching, and discloses a nursing teaching path personalized recommendation method and system fusing experience and scenes. The method comprises the following steps: collecting interactive data and behavior logs of learners in a nursing teaching process, extracting behavior characteristics, and constructing preliminary ability distribution data; comparing the ability distribution with a nursing scene adaptation standard to determine the current ability state of the learners; generating a phased learning target based on the ability state and constructing a preliminary teaching path sequence, dynamically adjusting the preliminary teaching path sequence in a path execution process in combination with learning feedback data; performing scene adaptation verification on the optimized teaching path structure to generate a final personalized teaching recommendation path, and determining a path adjustment direction through a nursing skill improvement effect evaluation. The application can realize personalized recommendation and dynamic optimization of a nursing teaching path, improve the matching degree of the teaching path and the nursing scene, enhance the pertinence and effectiveness of skill training, and improve the intelligence of nursing teaching.

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