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Relevant bibliographies by topics / Successive relearning

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Academic literature on the topic 'Successive relearning'

Author: Grafiati

Published: 4 June 2021

Last updated: 3 February 2022

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Journal articles on the topic "Successive relearning"

1

Vaughn, Kalif E., John Dunlosky, and Katherine A. Rawson. "Effects of successive relearning on recall: Does relearning override the effects of initial learning criterion?" Memory & Cognition 44, no. 6 (March 30, 2016): 897–909. http://dx.doi.org/10.3758/s13421-016-0606-y.

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Rawson, Katherine A., Kalif E. Vaughn, Matthew Walsh, and John Dunlosky. "Investigating and explaining the effects of successive relearning on long-term retention." Journal of Experimental Psychology: Applied 24, no. 1 (March 2018): 57–71. http://dx.doi.org/10.1037/xap0000146.

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Maurer, Trent, and Catelyn Shipp. "Challenges of Shaping Student Study Strategies for Success." Teaching & Learning Inquiry 9, no. 1 (March 7, 2021): 241–57. http://dx.doi.org/10.20343/teachlearninqu.9.1.16.

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This paper reports results from a mixed-methods intervention conducted in partnership between a faculty member and an undergraduate to shape student study strategies for success in an introductory course. The instructor provided students with information on the effectiveness of the successive relearning study strategy, conducted an in-class demonstration of the strategy, and explained how students could apply the strategy to their study plan for the first exam. Students were asked about their planned study behaviors for the first exam before the intervention and exam and about their actual study behaviors for the exam after the intervention and exam. Students were asked before the intervention what an instructor could do to convince them to try a new strategy, and again after the intervention whether or not they adopted the new strategy and why. Quantitative results indicated that the intervention had no effect on students’ study behaviors, contrary to the predictions of the prior literature. Qualitative analyses suggested that students were open to learning more effective ways to study and thought that interventions like the one used in this investigation would convince them to try a new strategy. However, students were unable to use successive relearning because of procrastination and time management issues.

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Janes, Jessica L., John Dunlosky, Katherine A. Rawson, and Aaron Jasnow. "Successive relearning improves performance on a high‐stakes exam in a difficult biopsychology course." Applied Cognitive Psychology 34, no. 5 (June 9, 2020): 1118–32. http://dx.doi.org/10.1002/acp.3699.

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Rawson, Katherine A., John Dunlosky, and Sharon M. Sciartelli. "The Power of Successive Relearning: Improving Performance on Course Exams and Long-Term Retention." Educational Psychology Review 25, no. 4 (September 24, 2013): 523–48. http://dx.doi.org/10.1007/s10648-013-9240-4.

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Dunlosky, John, and Katherine A. Rawson. "Practice tests, spaced practice, and successive relearning: Tips for classroom use and for guiding students’ learning." Scholarship of Teaching and Learning in Psychology 1, no. 1 (2015): 72–78. http://dx.doi.org/10.1037/stl0000024.

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Rawson, Katherine A., John Dunlosky, and Jessica L. Janes. "All Good Things Must Come to an End: a Potential Boundary Condition on the Potency of Successive Relearning." Educational Psychology Review 32, no. 3 (April 21, 2020): 851–71. http://dx.doi.org/10.1007/s10648-020-09528-y.

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Kumar, Neeraj, Adarsh Kumar, Bhoomika Sonane, and Pratik K. Mutha. "Interference between competing motor memories developed through learning with different limbs." Journal of Neurophysiology 120, no. 3 (September 1, 2018): 1061–73. http://dx.doi.org/10.1152/jn.00905.2017.

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Learning from motor errors that occur across different limbs is essential for effective tool use, sports training, and rehabilitation. To probe the neural organization of error-driven learning across limbs, we asked whether learning opposing visuomotor mappings with the two arms would interfere. Young right-handers first adapted to opposite visuomotor rotations A and B with different arms and were then reexposed to A 24 h later. We observed that relearning of A was never faster nor were initial errors smaller than prior A learning, which would be expected if there was no interference from B. Rather, errors were greater than or similar to, and learning rate was slower than or comparable to, previous A learning depending on the order in which the arms learned. This indicated robust interference between the motor memories of A and B when they were learned with different arms in close succession. We then proceeded to uncover that the order-dependent asymmetry in performance upon reexposure resulted from asymmetric transfer of learning from the left arm to the right but not vice versa and that the observed interference was retrograde in nature. Such retrograde interference likely occurs because the two arms require the same neural resources for learning, a suggestion consistent with that of our past work showing impaired learning following left inferior parietal damage regardless of the arm used. These results thus point to a common neural basis for formation of new motor memories with different limbs and hold significant implications for how newly formed motor memories interact. NEW & NOTEWORTHY In a series of experiments, we demonstrate robust retrograde interference between competing motor memories developed through error-based learning with different arms. These results provide evidence for shared neural resources for the acquisition of motor memories across different limbs and also suggest that practice with two effectors in close succession may not be a sound approach in either sports or rehabilitation. Such training may not allow newly acquired motor memories to be stabilized.

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Coltman, Susan K., Joshua G. A. Cashaback, and Paul L. Gribble. "Both fast and slow learning processes contribute to savings following sensorimotor adaptation." Journal of Neurophysiology 121, no. 4 (April 1, 2019): 1575–83. http://dx.doi.org/10.1152/jn.00794.2018.

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Recent work suggests that the rate of learning in sensorimotor adaptation is likely not fixed, but rather can change based on previous experience. One example is savings, a commonly observed phenomenon whereby the relearning of a motor skill is faster than the initial learning. Sensorimotor adaptation is thought to be driven by sensory prediction errors, which are the result of a mismatch between predicted and actual sensory consequences. It has been proposed that during motor adaptation the generation of sensory prediction errors engages two processes (fast and slow) that differ in learning and retention rates. We tested the idea that a history of errors would influence both the fast and slow processes during savings. Participants were asked to perform the same force field adaptation task twice in succession. We found that adaptation to the force field a second time led to increases in estimated learning rates for both fast and slow processes. While it has been proposed that savings is explained by an increase in learning rate for the fast process, here we observed that the slow process also contributes to savings. Our work suggests that fast and slow adaptation processes are both responsive to a history of error and both contribute to savings. NEW & NOTEWORTHY We studied the underlying mechanisms of savings during motor adaptation. Using a two-state model to represent fast and slow processes that contribute to motor adaptation, we found that a history of error modulates performance in both processes. While previous research has attributed savings to only changes in the fast process, we demonstrated that an increase in both processes is needed to account for the measured behavioral data.

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Day, Kevin A., Kristan A. Leech, Ryan T. Roemmich, and Amy J. Bastian. "Accelerating locomotor savings in learning: compressing four training days to one." Journal of Neurophysiology 119, no. 6 (June 1, 2018): 2100–2113. http://dx.doi.org/10.1152/jn.00903.2017.

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Acquiring new movements requires the capacity of the nervous system to remember previously experienced motor patterns. The phenomenon of faster relearning after initial learning is termed “savings.” Here we studied how savings of a novel walking pattern develops over several days of practice and how this process can be accelerated. We introduced participants to a split-belt treadmill adaptation paradigm for 30 min for 5 consecutive days. By training day 5, participants were able to produce near-perfect performance when switching between split and tied-belt environments. We found that this was due to their ability to shift specific elements of their stepping pattern to account for the split treadmill speeds from day to day. We also applied a state-space model to further characterize multiday locomotor savings. We then explored methods of achieving comparable savings with less total training time. We studied people training only on day 1, with either one extended split-belt exposure or alternating four times between split-belt and tied-belt conditions rapidly in succession. Both of these single-day training groups were tested again on day 5. Experiencing four abbreviated exposures on day 1 improved the performance on day 5 compared with one extended exposure on day 1. Moreover, this abbreviated group performed similarly to the group that trained for 4 consecutive days before testing on day 5, despite only having one-quarter of the total training time. These results demonstrate that we can leverage training structure to achieve a high degree of performance while minimizing training sessions. NEW & NOTEWORTHY Learning a new movement requires repetition. Here, we demonstrate how to more efficiently train an adapted walking pattern. By compressing split-belt treadmill training delivered over 4 days to four abbreviated bouts of training delivered on the first day of training, we were able to induce equivalent savings over a 5-day span. These results suggest that we can manipulate the delivery of training to most efficiently drive multiday learning of a novel walking pattern.

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Dissertations / Theses on the topic "Successive relearning"

1

Janes, Jessica L. "Successive Relearning Improves Performance on a High-Stakes Exam in a Difficult Biopsychology Course." Kent State University / OhioLINK, 2019. http://rave.ohiolink.edu/etdc/view?acc_num=kent1555593773001858.

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