Integrating neuroscience and health social science approaches to online learning burnout

Online learning burnout has emerged as a critical concern in higher education, prompting researchers to develop computational approaches for detecting and analyzing social support in digital learning environments. While recent advances in natural language processing and machine learning have yielded insights into the relationship between social support and student burnout, current research approaches may benefit from deeper theoretical grounding. This short communication proposes integrated approaches combining Iain McGilchrist's bihemispheric theory and health social science perspectives to enrich our understanding and mitigate online learning burnout. These approaches advocate for online learning designs that foster authentic engagement while emphasizing the sociocultural dimensions of burnout.