抄録
Against the backdrop of the deep embedding of digital technologies in educational settings, university students’ knowledge acquisition behaviors are increasingly mediated by algorithm-centered digital platforms, including search engines, social media, video applications, and online education systems. Traditional teacher-led and linearly structured learning pathways are being reconfigured by platform-driven recommendation mechanisms. Drawing on questionnaire survey data and in-depth interviews with undergraduate students at a comprehensive university, this study systematically examines how algorithmic recommendations shape students’ knowledge selection, the construction of learning pathways, and their judgments of knowledge authority. The findings indicate that platform recommendation mechanisms enhance the immediacy and fragmentation of knowledge acquisition, fostering tendencies toward “cognitive echo chambers” and “path dependence,” which in turn constrain knowledge diversity and critical thinking. At the same time, students’ trust in content from informal platforms has increased markedly, leading to a partial erosion of traditional academic authority. This study contributes in three main respects: first, it introduces a perspective from the sociology of algorithms to construct an analytical framework of interactions among technology, knowledge, and power; second, it centers on learners’ subjective experiences to reveal how algorithmic logics reshape cognitive structures and learning behaviors at the micro level; and third, it proposes the concept of a “platformized learning ecology,” offering theoretical support and practical implications for information literacy education and curricular reform in higher education. Overall, this research extends sociological understandings of learning mechanisms in the digital era and provides empirical evidence and strategic insights for educational governance amid the digital transformation of universities.
