How Cognitive Science Can Promote Conceptual Understanding in Physics Classrooms

Cognitive science research focuses on how the mind works, including topics such as thinking, problem solving, learning and transfer. Much of this research remains unknown in science education circles, yet is relevant for the design of instructional strategies in the sciences. We outline some difficulties in learning science, along with a discussion of some relevant cognitive science research. We then present a cognitive science-based intervention in physics education aimed at promoting conceptual understanding within a problem solving context. In addition, we present assessments of problem solving and conceptual understanding to better examine the differences between knowledge learned from this approach compared to traditional instruction. Finally, we present some pilot data on an initial implementation of the approach

[1]  R. Siegler Microgenetic Studies of Self-Explanation , 2002 .

[2]  K. Holyoak,et al.  Schema induction and analogical transfer , 1983, Cognitive Psychology.

[3]  J. Hiebert Conceptual and procedural knowledge : the case of mathematics , 1987 .

[4]  A. Ortony,et al.  Similarity and Analogical Reasoning , 1991 .

[5]  J. Mestre,et al.  The relation between problem categorization and problem solving among experts and novices , 1989, Memory & cognition.

[6]  Eric Mazur,et al.  Peer Instruction: A User's Manual , 1996 .

[7]  Geoff N Masters,et al.  Displacement, velocity, and frames of reference: Phenomenographic studies of students’ understanding and some implications for teaching and assessment , 1992 .

[8]  L. Squire,et al.  Preserved learning and retention of pattern-analyzing skill in amnesia: dissociation of knowing how and knowing that. , 1980, Science.

[9]  John Sweller,et al.  Cognitive Load During Problem Solving: Effects on Learning , 1988, Cogn. Sci..

[10]  Robert J. Dufresne,et al.  Using qualitative problem‐solving strategies to highlight the role of conceptual knowledge in solving problems , 1996 .

[11]  B. Ross Remindings and their effects in learning a cognitive skill , 1984, Cognitive Psychology.

[12]  John D. Bransford,et al.  New approaches to instruction: because wisdom can't be told , 1989 .

[13]  Dorothea P. Simon,et al.  Individual Differences in Solving Physics Problems (1978) , 1978 .

[14]  David P Maloney,et al.  Surveying students’ conceptual knowledge of electricity and magnetism , 2001 .

[15]  Robert J. Dufresne,et al.  Constraining Novices to Perform Expertlike Problem Analyses: Effects on Schema Acquisition , 1992 .

[16]  Paul J. Feltovich,et al.  Categorization and Representation of Physics Problems by Experts and Novices , 1981, Cogn. Sci..

[17]  Brian H. Ross,et al.  Effects of principle explanation and superficial similarity on analogical mapping in problem solving. , 1997 .

[18]  B. Rittle-Johnson,et al.  Does comparing solution methods facilitate conceptual and procedural knowledge? An experimental study on learning to solve equations. , 2007 .

[19]  J. Sweller,et al.  Effects of schema acquisition and rule automation on mathematical problem-solving transfer. , 1987 .

[20]  Edward A. Silver,et al.  Recall of Mathematical Problem Information: Solving Related Problems. , 1981 .

[21]  F. Paas Training strategies for attaining transfer of problem-solving skill in statistics: A cognitive-load approach. , 1992 .

[22]  Richard Mayer,et al.  Multimedia Learning , 2001, Visible Learning Guide to Student Achievement.

[23]  Dedre Gentner,et al.  Structure-Mapping: A Theoretical Framework for Analogy , 1983, Cogn. Sci..

[24]  F. Craik,et al.  Interaction between encoding and retrieval operations in cued recall. , 1977 .

[25]  Herbert A. Simon,et al.  Five seconds or sixty? Presentation time in expert memory , 2000, Cogn. Sci..

[26]  R. Glaser Advances in Instructional Psychology , 1978 .

[27]  B. Ross This is like that: The use of earlier problems and the separation of similarity effects. , 1987 .

[28]  B. Rittle-Johnson,et al.  Developing Conceptual Understanding and Procedural Skill in Mathematics: An Iterative Process. , 2001 .

[29]  B. Ross,et al.  Content Effects in Problem Categorization and Problem Solving , 1996 .

[30]  D. Hestenes,et al.  Force concept inventory , 1992 .

[31]  John R. Anderson,et al.  Abstract Planning and Perceptual Chunks: Elements of Expertise in Geometry , 1990, Cogn. Sci..

[32]  B. Ross Distinguishing Types of Superficial Similarities: Different Effects on the Access and Use of Earlier Problems , 1989 .

[33]  F. Craik,et al.  Levels of Pro-cessing: A Framework for Memory Research , 1975 .

[34]  F. Paas,et al.  Variability of Worked Examples and Transfer of Geometrical Problem-Solving Skills: A Cognitive-Load Approach , 1994 .

[35]  B. Adelson Problem solving and the development of abstract categories in programming languages , 1981, Memory & cognition.

[36]  Robert J. Dufresne,et al.  Promoting skilled problem‐solving behavior among beginning physics students , 1993 .

[37]  M. Just,et al.  Cognitive processes in comprehension , 1977 .

[38]  John R. Anderson Language, Memory, and Thought , 1976 .

[39]  B. Ross,et al.  Generalizing from the use of earlier examples in problem solving , 1990 .

[40]  H. Simon,et al.  Perception in chess , 1973 .

[41]  Lillian C. McDermott Guest Comment: How we teach and how students learn—A mismatch? , 1993 .

[42]  D. Herrmann,et al.  Problem perception and knowledge structure in expert and novice mathematical problem solvers. , 1982 .

[43]  John D. Bransford,et al.  Levels of processing versus transfer appropriate processing , 1977 .