Algorithmic Recommendation-Driven Value Cognition in the Practical Teaching of Ideological and Political Theory Courses: Double-Edged Effects and Intervention Paths

Abstract

The algorithmic recommendation technology has been deeply involved into the information receiving environment of educational subjects that not only change the way of presenting value issues, but also profoundly influence the construction of value cognition. From the theoretical perspective of the interaction between algorithmic recommendation and value cognition, we explained the generative logic of algorithmic recommendation's embedding in constructing value cognition by analyzing the dual effect (positive empowerment and negative erosion) upon value cognition through three pathways including cognitive focusing, cognitive expansion, and cognitive adaptation; algorithmic recommendation realized positive construction with cognitive damage via information narrowing, preference solidification, and cognitive offloading. By revealing the double-edged effects completely, we proposed intervention paths from three aspects – algorithmic transparency, diversified information exposure, and adjusting recommendation logic, providing theoretical references for the healthy development of value cognition in the algorithmic age.