The widespread adoption of social networking platforms by university students has fundamentally altered scholastic interaction, information dissemination, and pedagogical methodologies. Digital applications like Facebook, WhatsApp, YouTube, Instagram, Twitter, and TikTok are progressively integrated into students' lives for both academic endeavors and recreational pursuits. Nonetheless, the precise consequences of social media engagement on student performance remain highly debated, given that existing literature presents conflicting evidence regarding positive and negative educational returns. Accordingly, this meta-synthesis aims to thoroughly investigate the connection between digital network usage and academic metrics among college students, categorize its constructive and disruptive influences on scholarship, and examine the underlying parameters that mediate academic performance. Adopting a systematic qualitative literature review framework, this study analyzes secondary data derived from 51 empirical investigations published between 2011 and 2025. The results suggest that social media functions as an asset for education when leveraged for collaborative study, academic dialogue, peer information exchange, and intellectual advancement. Conversely, compulsive, or uncontrolled network immersion exerts a detrimental toll on academic outcomes by shrinking available study windows, accelerating procrastination, impeding concentration, and causing sleep fragmentation. Furthermore, the synthesis highlights critical mediating elements including time management efficacy, cognitive student engagement, intrinsic academic motivation, self-regulatory behavior, mental well-being, stress, and the precise intent behind platform usage. Ultimately, the study concludes that social media operates as a double-edged sword, whose net effect on scholastic performance relies fundamentally on the students' capacity to regulate and direct their digital habits. Consequently, balanced, intentional, and disciplined application of digital networks is imperative to optimize learning metrics and mitigate adverse academic consequences.
Kumura et al. (Mon,) studied this question.