Caitlin Tenison
Carnegie Mellon University
18 Papers
13 Citations
Caitlin Tenison is an academic researcher from Carnegie Mellon University. The author has contributed to research in topics: Cognition & Computer science. The author has an hindex of 10, co-authored 16 publications. Previous affiliations of Caitlin Tenison include Stanford University.
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Papers
Neural predictors of individual differences in response to math tutoring in primary-grade school children
Kaustubh Supekar,Anna G. Swigart,Caitlin Tenison,Dietsje Jolles,Miriam Rosenberg-Lee,Lynn S. Fuchs,Vinod Menon +6 more
TL;DR: Evidence is provided that individual differences in morphometry and connectivity of brain regions associated with learning and memory, and not regions typically involved in arithmetic processing, are strong predictors of responsiveness to math tutoring in children and that quantitative measures of brain structure and intrinsic brain organization can provide a more sensitive marker of skill acquisition than behavioral measures.
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Cognitive tutoring induces widespread neuroplasticity and remediates brain function in children with mathematical learning disabilities.
Teresa Iuculano,Miriam Rosenberg-Lee,Jennifer Richardson,Caitlin Tenison,Lynn S. Fuchs,Kaustubh Supekar,Vinod Menon +6 more
TL;DR: It is demonstrated that eight weeks of 1:1 cognitive tutoring not only remediates poor performance in children with MLD, but also induces widespread changes in brain activity that are significantly discriminable from neurotypical peers before, but not after, tutoring.
Weak task-related modulation and stimulus representations during arithmetic problem solving in children with developmental dyscalculia.
TL;DR: The results show that children with DD not only under-activate key brain regions implicated in mathematical cognition, but they also fail to generate distinct neural responses and representations for different arithmetic problems.
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Modeling the distinct phases of skill acquisition.
Caitlin Tenison,John R. Anderson +1 more
TL;DR: Hidden Markov modeling is used to identify transitions in the learning process and finds that as participants practice solving math problems they transition through 3 distinct learning states, which find parallels with the 3 phases of skill acquisition proposed by Fitts and Posner (1967): a cognitive, an associative, and an autonomous phase.
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Phases of learning: How skill acquisition impacts cognitive processing.
TL;DR: This fMRI study examines the changes in participants' information processing as they repeatedly solve the same mathematical problem and shows that the majority of practice-related speedup is produced by discrete changes in cognitive processing.
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