SEARCH

SEARCH BY CITATION

REFERENCES

  • Aikens, J. (1983). Prototypical knowledge for expert systems. Artificial Intelligence, 20, 163210.
  • Anderson, J.R. (1983). The architecture of cognition. Cambridge , MA : Harvard University Press.
  • Anderson, J.R. (1987). Skill acquisition: Compilation of weak-method problem solutions. Psychological Review, 94, 192210.
  • Anderson, J.R., Greeno, J.G., Kline, P.J., & Neves, D.M. (1981). Acquisition of problem-solving skill. In J.R. Anderson (Ed.), Cognitive skills and their acquisition (pp. 191230). Hillsdale , NJ : Erlbaum.
  • Carbonell, J.G. (1986). Analogy in problem solving. In R.S. Michalski, J.G. Carbonell & T.M. Mitchell (Eds.), Machine learning: An artificial intelligence approach, (Vol. 2, pp. 371392). Los Altos , CA : Morgan Kaufmann.
  • Chi, M.T.H., Feltovich, P.J., & Glaser, R. (1981). Categorization and representation of psychics knowledge by experts and novices. Cognitive Science, 5, 121152.
  • Chi, M.T.H., Glaser, R., & Rees, E. (1982). Expertise in problem solving. In R.J. Sternberg (Ed.), Advances in the psychology of human intelligence, (Vol. 1, pp. 776). Hillsdale , NJ : Erlbaum.
  • Clancey, W.J. (1983). The epistemology of a rule-based expert system: A framework for explanation. Artificial Intelligence, 20, 215251.
  • de Groot, A. (1966). Perception and memory versus thought: Some old ideas and recent findings. In B. Kleinmuntz (Ed.), Problem solving (pp. 000000). New York : Wiley.
  • DeJong, G., & Mooney, R. (1986). Explanation-based learning: An alternative view. Machine Learning, 1, 145176.
  • Elio, R., & Anderson, J.R. (1984). The effects of information order and learning mode on schema abstraction. Memory & Cognition, 12, 2030.
  • Feigenbaum, E.A., & Simon, H.A. (1962). A theory of the serial position effect. British Journal of Psychology, 53, 307320.
  • Halliday, D., & Resnick, R. (1981). Fundamentals of physics. New York : Wiley.
  • Heller, J.I., & Reif, F. (1984). Prescribing effective human problem-solving processes: Problem descriptions in physics. Cognition and Instruction, 1, 177216.
  • Hinsley, D.A., Hayes, J.R., & Simon, H.A. (1978). From words to equations: Meaning and representation in algebra word problems. In P.A. Carpenter & M.A. Just (Eds.), Cognitive processes in comprehension (pp. 89106). Hillsdale , NJ : Erlbaum.
  • Johnson, P.E., Duran, A.S., Hassebrock, F., Moller, J., Prietula, M., Feltovich, P.J., & Swanson, D.B. (1981). Expertise and error in diagnostic reasoning. Cognitive Science, 5, 235283.
  • Kolodner, J.L. (1983a). Towards an understanding of the role of experience in the evolution from novice to expert. International Journal of Man-Machine Studies, 19, 497518.
  • Kolodner, J.L. (1983b). Maintaining organization in a dynamic long-term memory. Cognitive Science, 7, 243280.
  • Kolodner, J.L. (1984). Retrieval and organizational strategies in conceptual memory: A computer model. Hillsdale , NJ : Erlbaum.
  • Laird, J., Rosenbloom, P., & Newell, A. (1986). Chunking in Soar: The anatomy of a general learning mechanism. Machine Learning, 1, 1146.
  • Langley, P. (1987). A general theory of discrimination learning. In D. Klahr, P., Langley, & R. Neches (Eds.), Production system models of learning and development. (pp. 99162). Cambridge , MA : MIT Press.
  • Larkin, J.H. (1979). Processing information for effective problem solving. Engineering Education, 70, 285288.
  • Larkin, J.H. (1981). Enriching formal knowledge: A model for learning to solve textbook physics problems. In J.R. Anderson (Ed.), Cognitive skills and their acquisition (pp. 311334). Hillsdale , NJ : Erlbaum.
  • Larkin, J.H. (1983). The role of problem representation in physics. In D. Centner & A.L. Stevens (Eds.), Mental models (pp. 7598). Hillsdale , NJ : Erlbaum.
  • Larkin, J.H. (1985). Understanding, problem representations, and skill in physics. In S.F. Chipman, J.W. Segal, & R. Glaser (Eds.), Thinking and learning skills: Research and open questions (Vol. 2, pp. 141159). Hillsdale , NJ : Erlbaum.
  • Larkin, J.H., McDermott, J., Simon, D.P., & Simon, H.A. (1980). Models of competence in solving physics problems. Cognitive Science, 4, 317345.
  • Lebowitz, M. (1983). Generalization from natural language text. Cognitive Science, 7, 140.
  • Lebowitz, M. (1986). Concept learning in a rich input domain: Generalization-based memory. In R.S. Michalski, J.G. Carbonell, & T.M. Mitchell (Eds.), Machine learning: An artificial intelligence approach (Vol. 2, pp. 193214). Los Altos , CA : Morgan Kaufman.
  • McKeithen, K.B., Reitman, J.S., Rueter, H.H., & Hirtle, S.C. (1981). Knowledge organization and skill differences in computer programmers. Cognitive Psychology, 13, 307325.
  • Michalski, R.S. (1983). A theory and methodology of inductive learning. In R.S. Michalski, J.G. Carbonell, & T.M. Mitchell (Eds.), Machine learning: An artificial intelligence approach (Vol. 1, pp. 83130). Palo Alto , CA : Tioga Publishing Company.
  • Neves, D.M. & Anderson, J.R. (1981). Knowledge compilation: Mechanisms for the automatization of cognitive skills. In J.R. Anderson (Eds.), Cognitive skills and their acquisition (pp. 5784). Hillsdale , NJ : Erlbaum.
  • Novak, G.S., Jr. (1977). Representations of knowledge in a program for solving physics problems. Proceedings of the Fifth International Joint Conference on Artificial Intelligence (pp. 286291). Cambridge , MA : MIT Press.
  • Novak, G.S., Jr., & Araya, A. (1980). Research on expert problem solving in physics. First National Conference on Artificial Intelligence (AAAI) (pp. 178180). Stanford , CA : Morgan Kaufmann.
  • Pauker, S.G., Gorry, G.A., Schwartz, W.G., & Kassirer, J.P. (1976). Towards the simulation of clinical cognition. American Journal of Medicine, 60, 981986.
  • Pople, H.E. (1977). The formation of composite hypotheses in diagnostic problem solving: An exercise in synthetic reasoning. Proceedings of the Fifth International Joint Conference on Artificial Intelligence (pp. 10301037). Pittsburgh , PA : Morgan Kaufmann.
  • Pople, H.E., Myers, J.D., & Miller, R.A. (1975). DIALOG: A model of diagnostic logic for internal medicine. Proceedings of the Fourth International Joint Conference on Artificial Intelligence (pp. 848855). Tbilisi , USSR : Morgan Kaufman.
  • Riesbeck, C.K. (1981). Failure-driven reminding for incremental learning. Proceedings of the 7th International Joint Conference on Artificial Intelligence (pp. 115120). Menlo Park , CA : IJCAI.
  • Rumelhart, D.E., & Norman, D.A. (1978). Accretion, tuning and restructuring: Three modes of learning. In J.W. Cotton & R.L. Kltazky (Eds., Semantic factors in cognition. Hillsdale , NJ : Erlbaum.
  • Schank, R.C. (1908). Language and memory. Cognitive Science, 4, 243284.
  • Schank, R.C. (1982). Dynamic Memory: A theory of reminding and learning in computers and people. Cambridge , MA : Cambridge University Press.
  • Schoenfeld, A.H., & Herrmann, D.J. (1982). Problem perception and knowledge structure in expert and novice mathematical problem solver. Journal of Experimental Psychology: Learning, Memory, and Cognition, 8, 484494.
  • Simon, H.A., & Chase, W.G. (1973). Skill in chess. American Scientist, 61, 394403.
  • Simon, D.P., & Simon, H.A. (1978). Individual differences in solving physics problems. In R. Siegler (Ed.), Children's thinking: What develops? (pp. 325348). Hillsdale , NJ : Erlbaum.
  • Voss, J.F., Greene, T.R., Post, T.A., & Penner, B.C. (1983). Problem-solving skill in the social sciences. In G.H. Bower (Ed.), The psychology of learning and motivation (Vol. 17, pp. 000000). New York : Academic.