In the last ten years, it was observed that the continuous upgrades in mobile device's technology have increased and demonstrated their great potential in various learning environments. Besides, it has motivated researchers to apply more innovative computational techniques regarding context-aware and a set of variables that have been used at different virtual learning proposals. This paper presents a Systematic Mapping Review that focuses on context-aware analysis and its approach to learning processes in mobile learning (m-learning) and ubiquitous learning (u-learning). Furthermore, the study identifies variables that have been used in the past decade for context-awareness analytics and that have been applied to those learning processes. Especially at systems' adaptations to learning styles and student-specific characteristics. A methodological process was applied to address problems through identification, critical evaluation, and integration of the most relevant works, where high-quality individual studies address one or several research questions. Results show that external variables, including location, time, and software, are the most used variables in the context-aware analysis, with 52.25% prevalence in research papers. Internal variables, including personal information, learning styles, and teaching styles, had a prevalence of 33.33%; variables less frequently used in the research included socioeconomic information and emotional content. The remaining 14.41% represents academic activities. These findings provide a basis for future research and development in the field of m-learning.