This paper presents an extension of the Additive Factors Model to predict learning for students by accounting for aspects of collaboration. The results indicate that student performance is predicted more accurately when the model includes parameters that capture influences of working collaboratively. [This paper was published in: "Proceedings of the 13th International Conference on Intelligent Tutoring Systems, ITS 2016," edited by A. Micarelli, J. Stamper, and K. Panourgia, Springer International Publishing, 2016, pp. 485-487.]