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  1. Metacognitive Control and Optimal Learning.Lisa K. Son & Rajiv Sethi - 2006 - Cognitive Science 30 (4):759-774.
    The notion of optimality is often invoked informally in the literature on metacognitive control. We provide a precise formulation of the optimization problem and show that optimal time allocation strategies depend critically on certain characteristics of the learning environment, such as the extent of time pressure, and the nature of the uptake function. When the learning curve is concave, optimality requires that items at lower levels of initial competence be allocated greater time. On the other hand, with logistic learning curves, (...)
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  • An Individual's Rate of Forgetting Is Stable Over Time but Differs Across Materials.Florian Sense, Friederike Behrens, Rob R. Meijer & Hedderik Rijn - 2016 - Topics in Cognitive Science 8 (1):305-321.
    One of the goals of computerized tutoring systems is to optimize the learning of facts. Over a hundred years of declarative memory research have identified two robust effects that can improve such systems: the spacing and the testing effect. By making optimal use of both and adjusting the system to the individual learner using cognitive models based on declarative memory theories, such systems consistently outperform traditional methods. This adjustment process is driven by a continuously updated estimate of the rate of (...)
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  • An Individual's Rate of Forgetting Is Stable Over Time but Differs Across Materials.Florian Sense, Friederike Behrens, Rob R. Meijer & Hedderik van Rijn - 2016 - Topics in Cognitive Science 8 (1):305-321.
    One of the goals of computerized tutoring systems is to optimize the learning of facts. Over a hundred years of declarative memory research have identified two robust effects that can improve such systems: the spacing and the testing effect. By making optimal use of both and adjusting the system to the individual learner using cognitive models based on declarative memory theories, such systems consistently outperform traditional methods (Van Rijn, Van Maanen, & Van Woudenberg, 2009). This adjustment process is driven by (...)
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  • The dynamics of learning and allocation of study time to a region of proximal learning.Janet Metcalfe & Nate Kornell - 2003 - Journal of Experimental Psychology: General 132 (4):530.
  • The cognitive antecedents and motivational consequences of the feeling of being in the zone.Patrick Kennedy, David B. Miele & Janet Metcalfe - 2014 - Consciousness and Cognition 30:48-61.
  • Effects of interleaved and blocked study on delayed test of category learning generalization.Paulo F. Carvalho & Robert L. Goldstone - 2014 - Frontiers in Psychology 5.
  • Spanning seven orders of magnitude: a challenge for cognitive modeling.John R. Anderson - 2002 - Cognitive Science 26 (1):85-112.
    Much of cognitive psychology focuses on effects measured in tens of milliseconds while significant educational outcomes take tens of hours to achieve. The task of bridging this gap is analyzed in terms of Newell's (1990) bands of cognition—the Biological, Cognitive, Rational, and Social Bands. The 10 millisecond effects reside in his Biological Band while the significant learning outcomes reside in his Social Band. The paper assesses three theses: The Decomposition Thesis claims that learning occurring at the Social Band can be (...)
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  • Skill Acquisition and the LISP Tutor.John R. Anderson, Frederick G. Conrad & Albert T. Corbett - 1989 - Cognitive Science 13 (4):467-505.
    An analysis of student learning with the LISP tutor indicates that while LISP is complex, learning it is simple. The key to factoring out the complexity of LISP is to monitor the learning of the 500 productions in the LISP tutor which describe the programming skill. The learning of these productions follows the power‐law learning curve typical of skill acquisition. There is transfer from other programming experience to the extent that this programming experience involves the same productions. Subjects appear to (...)
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