Affiliation:
1. The Open Polytechnic, New Zealand
2. Central Queensland University, Australia
3. Sydney International School of Technology and Commerce, Australia
Abstract
The purpose of this chapter is to highlight the current choice of methodologies that are preferred in artificial intelligence in education (AIed) studies and propose a value-added methodology for such studies. After a systematic literature review of the methodologies deployed in AIed studies, it can be seen that object-oriented methodology (OOM), action research (AR), and grounded theory are most often deployed. However, there is a case to be made for design-based research (DBR) methodology. DBR has a natural inclination with AIed (given their common history), is not bound by ontological presuppositions, and has the ability to generate knowledge and theory grounded in practice. These reasons alone show the value-addedness of DBR. A further comparison against the currently methodologies deployed will show that DBR has the ability to compensate for each of the weaknesses of the other methodologies.