The main priority tackled in the colMOOC project identifies that there is a need to make MOOCs more collaborative to support teachers and engage and motivate students. Conversational pedagogical agents guide and support student dialogue using natural language both in individual and collaborative settings.

Conversational agents have been produced to meet a wide variety of applications and studies exploring the usage of such agents have led to positive results. Integrating this type of conversational agents into MOOCs to trigger peer interaction in discussion groups is expected to considerably increase the engagement and the commitment of online students (and, consequently, reduce MOOCs dropout rate).

With the usage of learning analytics more meaningful assessment may be achieved, since educators can evaluate the work’s progress during each step and adapt the following steps accordingly. This also enables learners to reflect on each specific step and ensure they have obtained the necessary knowledge to progress effectively.