Learning from equations or words

A series of four experiments was designed to study the cognitive load consequences of learning from equations, as compared to words. Cognitive load theory suggests that some instructional procedures require learners to engage in cognitive activities solely because of the manner in which information is presented rather than because of intrinsic characteristics of the material. As a consequence, a heavy extraneous cognitive load that interferes with learning may be imposed. It is suggested that in studying equations with unfamiliar notations, a heavy extraneous cognitive load is generated because mental integration of notations and meanings is required. The results of Experiment 1 supported this suggestion. Experiment 2 found that when an equation format involves simple equations and familiar notations, it is more effective than an equivalent verbal format which requires substantial reading. Experiment 3 showed that when the use of notations becomes automated after extended practice and thus reduces the extraneous cognitive load required to mentally integrate notations and meanings, an equation format can be more effective than a verbal format. Experiment 4 indicated that supplementing a concise equation format with extensive verbal information does not assist learning, because processing the extensive verbal information induces a heavy cognitive load which creates redundancy effects. It was concluded that the efficacy of equations or words may depend, in part, on their cognitive load consequences.

[1]  Michelene T. H. Chi,et al.  Expertise in Problem Solving. , 1981 .

[2]  G. A. Miller THE PSYCHOLOGICAL REVIEW THE MAGICAL NUMBER SEVEN, PLUS OR MINUS TWO: SOME LIMITS ON OUR CAPACITY FOR PROCESSING INFORMATION 1 , 1956 .

[3]  Jill H. Larkin,et al.  Novice rules for assessing importance in scientific texts , 1988 .

[4]  L M Reder,et al.  Effects of spacing and embellishment on memory for the main points of a text , 1982, Memory & cognition.

[5]  F. Paas,et al.  Instructional control of cognitive load in the training of complex cognitive tasks , 1994 .

[6]  H A Simon,et al.  How Big Is a Chunk? , 1974, Science.

[7]  P. Chandler,et al.  Cognitive load as a factor in the structuring of technical material. , 1990 .

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

[9]  H. Simon,et al.  Why are some problems hard? Evidence from Tower of Hanoi , 1985, Cognitive Psychology.

[10]  Walter Schneider,et al.  Controlled and automatic human information processing: II. Perceptual learning, automatic attending and a general theory. , 1977 .

[11]  Michelene T. H. Chi,et al.  Self-Explanations: How Students Study and Use Examples in Learning To Solve Problems. Technical Report No. 9. , 1987 .

[12]  Kathleen M. Fisher The Students-and-Professors Problem Revisited. , 1988 .

[13]  J. Sweller,et al.  Structuring Effective Worked Examples , 1990 .

[14]  A. D. D. Groot Thought and Choice in Chess , 1978 .

[15]  J. Hiebert,et al.  Conceptual and Procedural Knowledge in Mathematics: An Introductory Analysis , 1986 .

[16]  James Hiebert,et al.  A Cognitive Approach to Meaningful Mathematics Instruction: Testing a Local Theory Using Decimal Numbers. , 1988 .

[17]  H. Simon,et al.  Learning Mathematics From Examples and by Doing , 1987 .

[18]  Jill H. Larkin,et al.  Novice Strategies for Processing Scientific Texts. , 1986 .

[19]  Herbert A. Simon,et al.  Models of Competence in Solving Physics Problems , 1980, Cogn. Sci..

[20]  J. Sweller,et al.  Development of expertise in mathematical problem solving. , 1983 .

[21]  John Sweller,et al.  Some cognitive processes and their consequences for the organisation and presentation of information , 1993 .

[22]  J. Bargh Automatic and conscious processing of social information. , 1984 .

[23]  J. Sweller,et al.  What do students learn while solving mathematics problems , 1985 .

[24]  P. Chandler,et al.  Cognitive Load Theory and the Format of Instruction , 1991 .

[25]  M. Burton,et al.  A Linguistic Basis for Student Difficulties with Algebra. , 1988 .

[26]  J. Sweller,et al.  Cognitive load effects in a primary-school geometry task , 1993 .

[27]  Jill H. Larkin,et al.  Equations in Scientific Proofs: Effects on Comprehension , 1991 .

[28]  Walter Schneider,et al.  Controlled and Automatic Human Information Processing: 1. Detection, Search, and Attention. , 1977 .

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

[30]  Renae Low,et al.  Hierarchical Ordering of Schematic Knowledge Relating to Area-of-Rectangle Problems. , 1992 .

[31]  P. Chandler,et al.  Why Some Material Is Difficult to Learn , 1994 .

[32]  John Sweller,et al.  Cognitive technology: Some procedures for facilitating learning and problem solving in mathematics and science. , 1989 .

[33]  John Sweller,et al.  Demands Imposed on Primary-School Students by Geometric Models , 1994 .

[34]  H. Simon,et al.  A simulation of memory for chess positions. , 1973 .

[35]  Herbert A. Simon,et al.  Why a Diagram is (Sometimes) Worth Ten Thousand Words , 1987 .

[36]  R. A. Tarmizi,et al.  Guidance during Mathematical Problem Solving. , 1988 .

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

[38]  Jeroen J. G. van Merriënboer,et al.  Strategies for computer-based programming instruction: Program completion vs. program generation. , 1992 .

[39]  John R. Anderson,et al.  A Comparison of Texts and their Summaries: Memorial Consequences. , 1980 .

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

[41]  Renae Low,et al.  Text editing of algebraic word problems , 1990 .

[42]  Fred G. W. C. Paas,et al.  The Efficiency of Instructional Conditions: An Approach to Combine Mental Effort and Performance Measures , 1992 .

[43]  J. Sweller,et al.  The Use of Worked Examples as a Substitute for Problem Solving in Learning Algebra , 1985 .

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