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  1.  42
    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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  2.  1
    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.
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  3.  4
    Reflections of idiographic long-term memory characteristics in resting-state neuroimaging data.Peiyun Zhou, Florian Sense, Hedderik van Rijn & Andrea Stocco - 2021 - Cognition 212 (C):104660.
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    Cognition‐Enhanced Machine Learning for Better Predictions with Limited Data.Florian Sense, Ryan Wood, Michael G. Collins, Joshua Fiechter, Aihua Wood, Michael Krusmark, Tiffany Jastrzembski & Christopher W. Myers - 2022 - Topics in Cognitive Science 14 (4):739-755.
    The fields of machine learning (ML) and cognitive science have developed complementary approaches to computationally modeling human behavior. ML's primary concern is maximizing prediction accuracy; cognitive science's primary concern is explaining the underlying mechanisms. Cross-talk between these disciplines is limited, likely because the tasks and goals usually differ. The domain of e-learning and knowledge acquisition constitutes a fruitful intersection for the two fields’ methodologies to be integrated because accurately tracking learning and forgetting over time and predicting future performance based on (...)
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    Capturing Dynamic Performance in a Cognitive Model: Estimating ACT‐R Memory Parameters With the Linear Ballistic Accumulator.Maarten Velde, Florian Sense, Jelmer P. Borst, Leendert Maanen & Hedderik Rijn - 2022 - Topics in Cognitive Science 14 (4):889-903.
    The parameters governing our behavior are in constant flux, and capturing these dynamics in cognitive models remains a challenge. We demonstrate how a mapping between ACT‐R's model of declarative memory and the linear ballistic accumulator enables efficient estimation of memory parameters from data. The resulting estimates provide a cognitively meaningful explanation for observed differences in behavior over time and between individuals.
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    Capturing Dynamic Performance in a Cognitive Model: Estimating ACT‐R Memory Parameters With the Linear Ballistic Accumulator.Maarten van der Velde, Florian Sense, Jelmer P. Borst, Leendert van Maanen & Hedderik van Rijn - 2022 - Topics in Cognitive Science 14 (4):889-903.
    The parameters governing our behavior are in constant flux. Accurately capturing these dynamics in cognitive models poses a challenge to modelers. Here, we demonstrate a mapping of ACT-R's declarative memory onto the linear ballistic accumulator (LBA), a mathematical model describing a competition between evidence accumulation processes. We show that this mapping provides a method for inferring individual ACT-R parameters without requiring the modeler to build and fit an entire ACT-R model. Existing parameter estimation methods for the LBA can be used, (...)
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    Cognition‐Enhanced Machine Learning for Better Predictions with Limited Data.Florian Sense, Ryan Wood, Michael G. Collins, Joshua Fiechter, Aihua Wood, Michael Krusmark, Tiffany Jastrzembski & Christopher W. Myers - 2022 - Topics in Cognitive Science 14 (4):739-755.
    The fields of machine learning (ML) and cognitive science have developed complementary approaches to computationally modeling human behavior. ML's primary concern is maximizing prediction accuracy; cognitive science's primary concern is explaining the underlying mechanisms. Cross-talk between these disciplines is limited, likely because the tasks and goals usually differ. The domain of e-learning and knowledge acquisition constitutes a fruitful intersection for the two fields’ methodologies to be integrated because accurately tracking learning and forgetting over time and predicting future performance based on (...)
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