There is a more fundamental reason for lack of progress in computer-based tutorial systems and this relates to the fundamental lack of intelligence on the part of the computer. It is easy to generate drill and practice exercises which test a students ability to produce response. It is quite another matter to provide useful advice if the response is wrong. The human teacher has a mental model of the student and can make a reasonable estimate of why a particular wrong answer has been produced. The longer the teacher has been in contact with that student the better he or she is able to offer constructive advice. The kind of system discussed above has no such model of the student on which to make decisions, nor does it have access to the large body of subject knowledge which is held by the human teacher. Its responses therefore must be stereotyped and unintelligent.
Further evidence of the lack of machine intelligence is the failure to make computer understand natural language. We talk about programming languages for computers, but these are not languages in the ordinary sense. They are just systems of coding which provide a highly stylized way of writing down the solutions to particular sorts of problems. The tact that programs in these languages, although made up largely of English words and some well-known mathematical symbols, are unintelligible to the layC^f-ff W) reader indi cates the gulf which still exists between the kind of verbal instructions which can be given to another human, and the coded instructions required by the compu ter. One expert has argued that the construction of an intelligent machine is a logical impossibility. Many researchers in this area would dispute such a claim, but so far they cannot provide the essential demonstration to the contrary.
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