Collaborative learning is an educational method used by teachers to impact learning in a positive way and enhance the learners' performances. It can occur within a group of two or more students. Therefore, the learners' grouping is an essential task for establishing collaboration and cooperation among them to achieve a common goal. However, with the increasing number of students as well as their different settings (academic, cognitive, emotional, social, etc.), the students grouping task becomes harder and more complex to build a good collaborative learn- ing environment. Hence, several researchers proposed different approaches for obtaining approximate solutions to handle this diversity and take advantages from it. In this context, this paper presents a systematic literature review (SLR) to pinpoint the relevant research works that address the students grouping problem. We also we focus on the ACO bio-inspired approach to discuss its advantages and how students group formation can be initially constructed by ACO method. In accordance with this, we adapt and simulate an existing ACO algorithm with randomly generated data. The obtained results show an interesting starting point for further works in order to develop a new approach based on real educational data.