Learning geometry problem solving by studying worked-examples: effects of learner guidance and expertise

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Copyright: Bokosmaty, Sahar
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Abstract
Research has demonstrated that instruction that relies heavily on worked examples is more effective for novices as opposed to instruction consisting of problem-solving. However, excessive guidance for expert learners may reduce their performance. This study investigated optimal degrees of guidance using geometry worked examples. Three conditions were used. In the Theorem & Step Guidance condition, students were told the steps to find each angle, the measure of the angle, and the theorem used to justify the answer. In the Step Guidance condition, learners were told the sequence of steps needed to reach the answer, but not told the theorem required to make a step. The problem solving condition required learners to solve problems with no guidance. It was hypothesized that by using Step Guidance, a new concept could be more readily incorporated into existing knowledge held in long-term memory compared to a Problem Solving approach or a Theorem & Step Guidance approach. Problem Solving would impose the heavy cognitive load associated with problem solving search while providing information concerning well-known theorems would be redundant. In other words, as long recognised by cognitive load theory, most students need to learn to recognise problem states and the moves associated with those states and this information is provided by Step Guidance without additional, redundant information. A series of geometry instruction experiments supported these hypotheses. The results of these experiments revealed that for students who already understand the relevant theorems, learning to solve problems primarily consists of learning to recognise problem states and their associated moves. Information concerning theorems only should be provided if students have yet to learn and automatise theorem schemas.
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Author(s)
Bokosmaty, Sahar
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Sweller, John
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Publication Year
2012
Resource Type
Thesis
Degree Type
PhD Doctorate
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