Coming out of school as a Ph.D in instructional technology, I had accumulated quite amount of reading (if not knowledge) of psychology, education, and sociology. However, how much you should know about technology? As a researcher of human learning, what should be the composition of your knowledge domain?
Right now I work as an instructional designer at a research university, designing online courses for the professional education sector. The university I work at is Georgia Tech, ranking #7 in public universities of USA and heavily focusing on STEM. We have some world top level professors and researchers. Being in this environment, I try to take advantage of it, and to understand more about what our faculty on campus on doing in the field of learning research. Therefore, in my self learning time, I started reading articles about research projects done by our faculty. Soon, I notice that these articles heavily focus on AI (Artificial Intelligence) and ML (Machine Learning). I started feeling interested – what are the definitions of AI and ML, and what are the knowledges scopes of these two areas? How are they related to our traditional educational research fields, i.e. education, psychology and sociology? Are they completely are two different parallel universes? Or most likely, they intercorrelate and overlap? If they do intercorrelate and overlap, how do they do that?
It will be interesting to conduct a literature review on papers published on main streamed journals on both side: AI and ML research led by STEM faculties, and educational research led by educational faculty.
Things to be considered: names of journals in the areas of instructional technology and AI/ML, conference names; main knowledge models/theoretical frameworks; main research methods; main research participants; main funding resources and funding amount.