How to build bridges between intelligent tutoring system subfields of research
The plethora of different subfields in intelligent tutoring systems (ITS) are often difficult to integrate theoretically when analyzing how to design an intelligent tutor. Important principles of design are claimed by many subfields, including but not limited to: design, human-computer interaction, perceptual psychology, cognitive psychology, affective and motivation psychology, statistics, artificial intelligence, cognitive neuroscience, constructivist and situated cognition theories. Because these theories and methods sometimes address the same grain size and sometimes different grain sizes they may or may not conflict or be compatible and this has implications for ITS design. These issues of theoretical synthesis also have implications for the experimentation that is used by our various subfields to establish principles. Because our proposal allows the combination of multiple perspectives, it becomes apparent that the current "forward selection" method of theoretical progress might be limited. An alternative "backward elimination" experimental method is explained. Finally, we provide examples to illustrate how to build the bridges we propose. © 2010 Springer-Verlag.
Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Pavlik, P., & Toth, J. (2010). How to build bridges between intelligent tutoring system subfields of research. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 6095 LNCS (PART 2), 103-112. https://doi.org/10.1007/978-3-642-13437-1_11