Models of competence in solving physics problems

Larkin, Jill H.; MCDERMOTT, J; SIMON, D; SIMON, H

doi:10.1016/s0364-0213(80)80008-5

Cited by 124 publications

(150 citation statements)

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“…Novices had to find alternative structures. La&in, McDermott, Simon and Simon (1980) found that experts use schemas to generate problem solving moves forward from the givens while novices work backward from the goal. Experts having acquired schemas allowing them to recognize problem states and their associated moves, used those schemas to generate moves forward from each problem state encountered.…”

Section: Schema Theorymentioning

confidence: 99%

The effects of technical illustrations on cognitive load

1992

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Section: Schema Theorymentioning

confidence: 99%

The effects of technical illustrations on cognitive load

1992

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“…These differences have been consistently identified across a variety of domains. Areas already documented in the literature include Algebra (Cooper & Sweller, 1987;Low & Over 1990); Geometry (Greeno, 1980); Tarmizi & Sweller, 1988;Lawson & Chinnapan, 1994); Mathematics (Owen & Sweller, 1985); Physics (Chi et al, 1982(Chi et al, , 1989Larkin, McDermott, Simon & Simon, 1980); Computer Programming (Pirolli & Recker, 1994) and Experimental Design (Schraagen, 1993). Apart from the Schraagen research, little work of this nature has been conducted on statistical knowledge but the methodology employed appears equally well-suited to this domain.…”

mentioning

confidence: 99%

Analysing probem solving behaviour of successful and unsuccessful statistics students

Hauff

Fogarty

1996

Instr Sci

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The present study investigated problem-solving behaviour in statistics by documenting differences between successful and unsuccessful students. Two methodological approaches were used. The first, based on studies by Chi, Glaser and Rees (1982), required students to identify key structural features of common problems. The second, based on further work by Chi, Bassok, Lewis, Reimann & Glaser (1989), used verbal protocol procedures to examine the processes employed when 'Good' and 'Poor' statistics students solve an ANOVA problem. It was expected that findings obtained by these earlier researchers in the domain of Physics would also apply in Statistics. Two groups of students in an undergraduate Psychology course were selected for the study. The first group (N = 8) had performed well in a statistics unit, the second group (N---6) had failed that unit. In the first part of the study, no differences were found between groups on the task of identifying key structural features of common problems. In the second part of the study, protocol analyses showed that the 'Good' students engaged in more concept-oriented solution behaviour, displayed more monitoring/judging behaviour, and asked more questions about the problem itself. These findings are similar to those obtained in other abstract knowledge domains such as Physics and Mathematics and indicate quite fundamental differences in the way in which competent and incompetent Statisics students solve Statistics problems.

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“…Like other studies on expertise (e.g., map reading: Thomdyke and Stasz, 1980;electronics: Egan and Schwartz, 1979; physics problem solving: Simon and Simon, 1980;revision: Hayes, Flower, Schrivcr, Stmlman and Carey, 1987), the number of years of experience and professional practice in the respective domain were used as the determining criteria of expertise. Each participant in this study had a minimum of ten years of professional experience, either teaching the content to first year science or health science college students or evaluating instructional materials for diverse m#ining needs.…”

Section: Subjectsmentioning

confidence: 99%

Differences in expert practice: a case from formative evaluation

Saroyan

1993

Instr Sci

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A clear case has been made in the literature regarding the role of the learner in formative evaluation of instructional materials. In contrast, research on the role of the expert has been limited. This paper describes formative evaluation by inslrucfional designers and subject matter experts, highlighting their task interpretation, their focus on text features, and their strategies. Content analysis of protocols based on think-aloud data suggest that instructional designers take on the role of a generalist, use a comparative method of review, and appear to be directed by the heuristics of the Instructional Systems Design Model. In contrast, subject matter experts approach the task as a specialist, use a sequential method of review, and seem to be directed by the domain knowledge. These differences lead to the identification of different problems and the generation of different revision recommendations. The implications of findings are discussed.

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Models of competence in solving physics problems

Cited by 124 publications

References 0 publications

The effects of technical illustrations on cognitive load

The effects of technical illustrations on cognitive load

Analysing probem solving behaviour of successful and unsuccessful statistics students

Differences in expert practice: a case from formative evaluation

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