Children's long‐term retention is directly constrained by their working memory capacity limitations

2021 ◽  
Author(s):  
Alicia Forsberg ◽  
Dominic Guitard ◽  
Eryn J. Adams ◽  
Duangporn Pattanakul ◽  
Nelson Cowan
Keyword(s):  
Working Memory ◽  
Working Memory Capacity ◽  
Memory Capacity ◽  
Capacity Limitations ◽  
Term Retention ◽  
Long Term Retention

Working Memory: Models and Applications

2020 ◽  
Author(s):  
Stoo Sepp ◽  
Steven J. Howard ◽  
Sharon Tindall-Ford ◽  
Shirley Agostinho ◽  
Fred Paas
Keyword(s):  
Working Memory ◽  
Individual Differences ◽  
Short Term Memory ◽  
Working Memory Capacity ◽  
Memory Capacity ◽  
Long Term Memory ◽  
Auditory Information ◽  
Short Term ◽  
Term Memory

In 1956, Miller first reported on a capacity limitation in the amount of information the human brain can process, which was thought to be seven plus or minus two items. The system of memory used to process information for immediate use was coined “working memory” by Miller, Galanter, and Pribram in 1960. In 1968, Atkinson and Shiffrin proposed their multistore model of memory, which theorized that the memory system was separated into short-term memory, long-term memory, and the sensory register, the latter of which temporarily holds and forwards information from sensory inputs to short term-memory for processing. Baddeley and Hitch built upon the concept of multiple stores, leading to the development of the multicomponent model of working memory in 1974, which described two stores devoted to the processing of visuospatial and auditory information, both coordinated by a central executive system. Later, Cowan’s theorizing focused on attentional factors in the effortful and effortless activation and maintenance of information in working memory. In 1988, Cowan published his model—the scope and control of attention model. In contrast, since the early 2000s Engle has investigated working memory capacity through the lens of his individual differences model, which does not seek to quantify capacity in the same way as Miller or Cowan. Instead, this model describes working memory capacity as the interplay between primary memory (working memory), the control of attention, and secondary memory (long-term memory). This affords the opportunity to focus on individual differences in working memory capacity and extend theorizing beyond storage to the manipulation of complex information. These models and advancements have made significant contributions to understandings of learning and cognition, informing educational research and practice in particular. Emerging areas of inquiry include investigating use of gestures to support working memory processing, leveraging working memory measures as a means to target instructional strategies for individual learners, and working memory training. Given that working memory is still debated, and not yet fully understood, researchers continue to investigate its nature, its role in learning and development, and its implications for educational curricula, pedagogy, and practice.

scholarly journals Does limited working memory capacity underlie age differences in associative long-term memory?

2019 ◽  
Vol 34 (2) ◽  
pp. 268-281 ◽  
Author(s):  
Lea M. Bartsch ◽  
Vanessa M. Loaiza ◽  
Klaus Oberauer
Keyword(s):  
Working Memory ◽  
Age Differences ◽  
Working Memory Capacity ◽  
Memory Capacity ◽  
Long Term Memory ◽  
Term Memory

scholarly journals Chunking as a rational strategy for lossy data compression in visual working memory

2017 ◽  
Author(s):  
Matthew R. Nassar ◽  
Julie C. Helmers ◽  
Michael J. Frank
Keyword(s):  
Working Memory ◽  
Visual Working Memory ◽  
Performance Optimization ◽  
Human Performance ◽  
Storage Capacity ◽  
Working Memory Capacity ◽  
Quantitative Description ◽  
Memory Task ◽  
Memory Capacity ◽  
Capacity Limitations

AbstractThe nature of capacity limits for visual working memory has been the subject of an intense debate that has relied on models that assume items are encoded independently. Here we propose that instead, similar features are jointly encoded through a “chunking” process to optimize performance on visual working memory tasks. We show that such chunking can: 1) facilitate performance improvements for abstract capacity-limited systems, 2) be optimized through reinforcement, 3) be implemented by center-surround dynamics, and 4) increase effective storage capacity at the expense of recall precision. Human performance on a variant of a canonical working memory task demonstrated performance advantages, precision detriments, inter-item dependencies, and trial-to-trial behavioral adjustments diagnostic of performance optimization through center-surround chunking. Models incorporating center-surround chunking provided a better quantitative description of human performance in our study as well as in a meta-analytic dataset, and apparent differences in working memory capacity across individuals were attributable to individual differences in the implementation of chunking. Our results reveal a normative rationale for center-surround connectivity in working memory circuitry, call for re-evaluation of memory performance differences that have previously been attributed to differences in capacity, and support a more nuanced view of visual working memory capacity limitations: strategic tradeoff between storage capacity and memory precision through chunking contribute to flexible capacity limitations that include both discrete and continuous aspects.

Incorporating semantics and individual differences in models of working memory

2003 ◽  
Vol 26 (6) ◽  
pp. 742-742
Author(s):  
Janice M. Keenan ◽  
Jukka Hyönä ◽  
Johanna K. Kaakinen
Keyword(s):  
Working Memory ◽  
Individual Differences ◽  
Language Processing ◽  
Working Memory Capacity ◽  
Memory Capacity ◽  
Long Term Memory ◽  
Term Memory ◽  
General Capacity ◽  
Capacity Estimates

Ruchkin et al.'s view of working memory as activated long-term memory is more compatible with language processing than models such as Baddeley's, but it raises questions about individual differences in working memory and the validity of domain-general capacity estimates. Does it make sense to refer to someone as having low working memory capacity if capacity depends on particular knowledge structures tapped by the task?

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