Much of the debate over minimally guided instruction is of
minimal value, due to a lack of precision on what is being discussed.
Kirschner, Sweller, and Clark (2006) explain minimally guided
instruction as "one in which learners, rather than being presented with essential information, must discover or construct essential information for
themselves". This has an obvious appeal, in terms of student engagement
and saving in teacher time, but without more details as to what the
student has to discover and how much help the student is given, this is a
pointless argument.
It would not be practical to give physics students some light spectra data and expect them to discover the special theory of relativity. Medical students, given some patient data could not be expected to discover that stomach ulcers are cased by one particular bacteria. These are discoveries which came only after years of work by people of exceptional talent.
Kirschner, Sweller, and Clark (2006) cite research to show that experts draw on their experience. However, this hardly seems a startling revelation. The obvious question, which Kirschner, Sweller, and Clark (2006) don't seem to ask, is what is the most efficient way to get beginners that experience? At the extreme you could just tell the student to learn "something" on a topic and to submit to testing when they feel they have accomplished it. This is what PHD students do and we provide even them with some help.
The way the discoverer of new knowledge expresses what they have found is rarely an efficient way to understand their discovery. Later researchers will create simpler explanations, of more practical value. It is not feasible to expect very student to undertake this work.
In addition Kirschner, Sweller, and Clark (2006) do not discuss the different aims of learning. Someone undertaking a PHD in order to be able to do fundamental research may be justified in spending years investigating their own theory in a very narrow area of a discipline. However, for someone learning to be a practitioner in industry, this is not a good way to get trained up.
It would not be practical to give physics students some light spectra data and expect them to discover the special theory of relativity. Medical students, given some patient data could not be expected to discover that stomach ulcers are cased by one particular bacteria. These are discoveries which came only after years of work by people of exceptional talent.
Kirschner, Sweller, and Clark (2006) cite research to show that experts draw on their experience. However, this hardly seems a startling revelation. The obvious question, which Kirschner, Sweller, and Clark (2006) don't seem to ask, is what is the most efficient way to get beginners that experience? At the extreme you could just tell the student to learn "something" on a topic and to submit to testing when they feel they have accomplished it. This is what PHD students do and we provide even them with some help.
The way the discoverer of new knowledge expresses what they have found is rarely an efficient way to understand their discovery. Later researchers will create simpler explanations, of more practical value. It is not feasible to expect very student to undertake this work.
In addition Kirschner, Sweller, and Clark (2006) do not discuss the different aims of learning. Someone undertaking a PHD in order to be able to do fundamental research may be justified in spending years investigating their own theory in a very narrow area of a discipline. However, for someone learning to be a practitioner in industry, this is not a good way to get trained up.
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