Research on the Algorithm for Enhancing Cohesion of Part-time Student Groups Based on Network Structure

Part-time education programs face inherent challenges in fostering group cohesion due to students' dispersed schedules and limited interaction opportunities. To address this, this study proposes a novel network optimization algorithm (INLMC) that enhances social connectivity in part-time student networks. Leveraging complex network hierarchies, our method identifies structurally pivotal students through influence analysis and strategically establishes cross-layer connections to maximize cohesion. Validated on real academic networks, INLMC significantly outperforms conventional approaches in computational efficiency while achieving near-optimal cohesion improvement. This work provides educators with a theoretically grounded tool to strengthen collaborative learning in flexible education models.