The present meta-analysis employs meta-analytic structural equation modeling (MASEM) to quantitatively synthesize studies that investigates college students' acceptance of online learning managements systems. This study combined meta-analysis and path analysis to extend and refine the Technology Acceptance Model (TAM) within a higher education online learning environment context. Analyses of 13 studies representing 3407 undergraduate students from world- wide universities were conducted. The study investigated four path models (e.g., fixed-effects and random-effects) measuring different combinations of variables and formed conclusions about the relationships between the variables that were available. The model fit of each path model suggested mixed-results. Some models resulted in an acceptable fit, while others resulted in poor fit. Invariance tests resulted in statistically different findings across multiple parameter estimates, suggesting little to no replicability of findings across studies. Educational technology researchers should be cautious when forming conclusions about undergraduate online learning management systems based on the TAM.