In this COVID-19 pandemic, learners across the world are encouraged to stay at home receiving online education, which has nearly caused various learning outcomes. It is thus necessary to analyze online learning outcomes, as well as their gender differences to provide constructive references for learners, teachers, and technology developers. This study obtained reliable data from various databases using searching techniques. The study also selected the research articles based on inclusion and exclusion criteria. After analyzing the forest and funnel plots drawn via Review Manager 5.3, the study arrived at the conclusion that online learning outcomes were significantly higher than the traditional learning outcomes with a large effect size (d = 1.24), while the gender differences in learning outcomes were not significant with a small effect size (d = -0.03). In the future, experts could make every effort to develop advanced emotion detection applications via interdisciplinary cooperation to improve online learning outcomes.