Page 512 - Deep Learning
P. 512

References                       495

            ———. (1990c). The mechanism of restructuring in geometry. Proceedings of the Twelfth
               Annual Conference of the Cognitive Science Society, Cambridge, Massachusetts,
               July 25–28 (pp. 237–244). Hillsdale, NJ: Erlbaum.
            ———.  (1991)  System  hacking  meets  learning  theory:  Reflections  on  the  goals  and
               standards of research in Artificial Intelligence and education. Journal of Artificial
               Intelligence in Education, vol. 2, pp. 5–18.
            ———. (1992a). Information-processing models of insight and related phenomena. In
               M. T. Keane & K. J. Gilhooly (Eds.), Advances in the psychology of thinking (vol. 1,
               pp. 1–44). New York: Harvester/Wheatsheaf.
            ———. (1992b). The cognitive skill of theory articulation: A neglected aspect of science
               education? Science and Education, vol. 1, pp. 181–192.
            ———. (1992c). Simulating the understanding of arithmetic: Answer to Schoenfeld.
               Journal for Research in Mathematics Education, vol. 23, pp. 474–482.
            ———. (1992d). Constraint-based student modeling. Journal of Artificial Intelligence
               and Education, vol. 3, pp. 429–447.
            ———. (1992e). The learning curve for writing books: Evidence from Professor Asimov.
               Psychological Science, vol. 3, pp. 380–382.
            ———. (1992f). Beyond rules and propositions: Reflections on Bereiter’s concept of
               problem-centered knowledge. Interchange, vol. 23, pp. 367–378.
            ———.  (1992g).  Artificial  instruction:  A  method  for  relating  learning  theory  to
               instructional design. In M. Jones & P. H. Winne (Eds.), Foundations and frontiers
               in instructional computing systems (pp. 55–83). Berlin, Germany: Springer-Verlag.
            ———. (1992h). Towards intelligent tutoring systems that teach knowledge rather than
               skills: Five research questions. In E. Scanlon & T. O’Shea (Eds.), New directions in
               educational technology (pp. 71–96). New York: Springer-Verlag.
            ———. (1993a). The interaction between knowledge and practice in the acquisition of
               cognitive skills. In A. Meyrowitz & S. Chipman (Eds.), Foundations of knowledge
               acquisition:  Cognitive  models  of  complex  learning  (pp.  147–208).  Norwell,
               MA: Kluwer.
            ———. (1993b). Abstract schemas. Educational Psychologist, vol. 28, pp. 51–66.
            ———. (1993c). The impact of cognitive theory on the practice of courseware authoring.
               Journal of Computer Assisted Learning, vol. 9, pp. 194–221.
            ———.  (1994).  Declarative  and  procedural  knowledge.  In  T.  Husen  &  T.  Neville-
               Postlethwaite (Eds.), The international encyclopedia of education (2nd ed., vol. 3,
               pp. 1432–1434). London, UK: Pergamon Press.
            ———. (1995a). Epistemic obstacles and the marriage of fantasy to rigor: A response to
               Suchting. Science and Education, vol. 4, pp. 379–389.
            ———. (1995b). Learning to do and learning to understand: A lesson and a challenge
               for cognitive modeling. In P. Reimann & H. Spada (Eds.), Learning in humans
               and machines: Towards an interdisciplinary learning science (pp. 37–62). Oxford,
               UK: Elsevier.
            ———.  (1996a).  Learning  from  performance  errors.  Psychological  Review,  vol.  103,
               pp. 241–262.
            ———. (1996b). Learning from error and the design of task environments. International
               Journal of Educational Research, vol. 25, pp. 419–449.
   507   508   509   510   511   512   513   514   515   516   517