Online learning participation continues to grow across the US, with over 7.1 million students enrolled in at least one course. Based on this fact and the changing educational paradigm, the authors present a method to classify online students using a gaming approach that has four categories: collaborative, gamification, pedagogical, and social. Each category represents a particular type of online persona with specific interactions and interests. Using the pedagogical recommendation process (PRP), the paper describes a case study that classifies students based on how they interact with the learning environment. By using the data from a real online learning environment called MeuTutor, the authors engaged the PRP steps to classify students and then create content to suit these groups. Whilst the conclusions did achieve the initial objectives, there is limited application for the results. The authors do acknowledge the need for future studies, and I would suggest the practical outcomes from this research could be considered by educators. Therefore, I would recommend this paper as a general source of information for teachers who are involved with online learning environments.