I’ve noticed that quite a few big names in ID (Instructional Design: Papert, Schank, Merrill,..) have backgrounds in AI (Artificial Intelligence, rather than the other AI) I find this a little disconcerting.
In some sense the application of concepts from artificial intelligence to human intelligence and learning is rather circular. Artificial intelligence begins with theories about how humans think, and builds machine systems that model this. Implementations of these models are of necessity distorted by the nature of the machine’s logic and circuitry – there is no reason to believe that humans process or store information in a manner anything like that required by a computer. If we then take these models of machine learning and intelligence, and reapply them to human learning, as has been done, for example, in Merrill’s Instructional Transaction Theory (Simon, 1973), we have created a circular application whose validity depends primarily on how accurate our initial AI assumptions are to reality. In other words, we create ID theories based on models of machine learning, which in turn are based on machine implementations of theories of mind. The soundness of this last connection remains an unresolved debate, as various and sometimes contrasting perspectives on theories of mind remain plausible, from theories of “mind-as-machine” through cultural evolution, the theory of extelligence, and beyond (Merrill, 1999) The notion that we can design models of human learning based on the idea that our minds are like the computers we have invented seems peculiar to this author.
Merrill, M. D. (1999). Instructional Transaction Theory (ITT): Instructional Design Based on Knowledge Objects. In C. M. Reigeluth (Ed.), Instructional-design theories and models : vol. 2, a new paradigm of instructional theory (pp. 397 – 424). Mahwah, N.J.: Lawrence Erlbaum Associates.
Simon, H. A. (1973). The Structure of Ill Structured Problems. Artificial Intelligence, 4(3), 181-201.