Deep Embedding of Literature Logical Structure in LBL-RBL Pedagogy: A Novel Pathway to Enhance Thesis Proposal Competency in Neuropathophysiology Courses

Abstract

Graduate students universally struggle with vague topics, insufficient innovation, and logical gaps in research proposals, highlighting the need for structured scientific training. This study presents an innovative pedagogical model embedding scholarly literature’s logical architecture into LBL-RBL hybrid teaching, implemented in Kunming Medical University’s Neuropathophysiology course. Targeting the complexity of neurological disease mechanisms, the course integrates lecture-based learning (LBL) and research-based learning (RBL) through a small-cohort framework featuring personalized literature-logic embedding → targeted lecture reinforcement → multi-round proposal iteration. Faculty deconstructed domain literature to establish a three-phase training system (“Logic Demonstration-Methodology Mapping-Proposal Embedding”), systematically merging academic logic with research methodology over 9 weeks. Results demonstrate that this problem-driven approach creates authentic scientific inquiry scenarios, activating student knowledge co-construction and collaborative exploration. It successfully enables dynamic competency progression through “cognitive deconstruction → methodological practice → proposal refinement,” significantly enhancing proposal rigor and innovation. This study offers a scalable dual-track solution for cultivating advanced scientific capabilities in medical graduate education.