Adaptive intelligent tutoring using machine learning techniques could help academic performance for students. But, the ideal aspect of such tutoring should really be about positive reinforcement while avoiding excessive negative feedback from collaborative techniques or comparison against other students of merit. Although, students do learn in a collaborative manner, individualized tutoring may be more useful. As a tutor the subject matter understanding becomes critical in this context in order to replace a human skill. Also, the tutor needs to adapt the pace and understand the pattern of learning of each human individual. Online learning and classrooms are slowly but surely becoming the norm as MOOCS are taking the trend. Online universities accessible for everyone is pretty much the future. However, such practices do need to extend towards research as well. Hence, an intelligent agent researcher could also form an aspect of practice towards extending subject matter rather than just teaching it. At same time, the intelligent agent could publish peer reviewed papers on the subject of interest and produce a Latex equivalent publication. Peer review process could also involve other multiagent interactions and search for the right citations. Furthermore, other intelligent agent roles could include plagiarism detection agent, proctor agent, and an instructor agent. It is still very early days for when an intelligent agent becomes a researcher as even tutoring agents have not quite reached the ability to match the human potential. Moreover, one needs to look towards linked data in order to connect so many distributed educational institutions as a global decentralized hub for open access knowledge sharing.
