JTE v24n1 - Transfer of Learning: Connecting Concepts During Problem Solving - 0 views
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There are several factors that affect learning transfer. These include whether students understand or simply memorize knowledge, the amount of time spent on learning the task, the amount of deliberate practice that is done beyond learning the task, the motivation of the student, how the problem is represented, the transfer conditions, and the metacognition of the solver (Dweck, 1989; Ericsson, Krampe, & Tesch-Romer, 1993; Johnson et al., 2011; Palinscar & Brown, 1984; Singley & Anderson, 1989).
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A student’s comprehension of a problem and his or her ultimate ability to transfer concepts learned previously to the current problem is inextricably linked to his or her ability to properly represent the problem.
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ognitive research shows that the organization of learning and how new learning relates to what a student already knows are the strongest predictors of how well a student will transfer knowledge (National Research Council, 2000). Schunn and Silk (2011) articulated, however, that in science and engineering students often “lack relevant conceptual frameworks or have frameworks that are not developed enough to support new learning adequately” (p. 9). The absence of such frameworks makes it difficult for students to connect and apply other knowledge where relevant.
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The problem solving process begins as soon as the problem solver generates enough information about the problem space to gain an understanding of the problem.
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Representation in the problem-solving process refers to how the solver mentally represents the problem. The solver’s representation of the problem is directly related to his or her existing knowledge structure of the content of the problem.
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Students have to increase their reflective practice to aid their metacognition and transfer of STEM concepts.
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Different individuals have different conceptual knowledge and will make different associations to their knowledge. Exposure to the constraints and affordances of a particular context in which a problem exists will invariably influence the way in which the student represents a problem in a similar context.
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Sanders (2009) admitted that it is difficult to prepare a teacher that is competent in all three bodies of knowledge, given the volume of content knowledge necessary to be an effective science, mathematics or technology educator.
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This pedagogical approach is not without its challenges, as students may still compartmentalize their knowledge. Also, it is often difficult logistically and in terms of instructional timing for teachers across STEM discipline to collaborate effectively (Crismond, 2011; Kimbell & Stables, 2008).
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Good and poor problem solvers differ in their recall of information from previously encountered problems and by extension their ability to transfer concepts to the target problem. This difference exists because poor problem solvers tend to remember surface similarities between problems, while good problem solvers remember underlying conceptual structures that make two problems similar although they have different surface features (Sutton, 2003).
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Until student assessment methods are modified to reflect less dependency on standardized tests, engineering and technology educators will garner greater collaboration from math and science teachers when the latter can see that engineering and design-based curriculums does improve students’ ability to solve standardized test problems.