How variability shapes learning and generalization

Raviv, Limor; Lupyan, Gary; Green, Shawn C

doi:10.1016/j.tics.2022.03.007

Cited by 105 publications

(136 citation statements)

References 158 publications

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“…Contrarily, if group members contribute different perspectives, their joint representations will have to accommodate this variability yielding more abstract joint representations (similarly to when individuals are presented with more varied training episodes, cf. Raviv et al, 2022). From this follows the prediction that groups collaborating on complex problems will benefit from cognitive diversity (Aggarwal & Woolley, 2010;Aggarwal, Woolley, Chabris, & Malone, 2015;Hong & Page, 2004;Woolley, Chabris, Pentland, Hashmi, & Malone, 2010).…”

Section: Diversity and Complexitymentioning

confidence: 91%

“…Most theories of abstraction and problem solving take the individual as an implicit starting point: as individuals notice structural analogies across tokens or situations, they generalize these as belonging to the same abstract type (Barsalou, 2003;Brown, 1989;Medin & Smith, 1984;Piaget, 1970;Pylyshyn, 1973). Across a number of domains and modalities, from motor learning to categorization and language, it has thus been observed how increased variance in learning episodes seem to facilitate generalization (Raviv, Lupyan, & Green, 2022). Common to these approaches, however, is that our special capacities for generalization and ruleformation are broadly conceived as a property of individual human brains and cognition (Gentner & Medina, 1998;Gibson, 2002;Rips, 1989).…”

Section: Social Interaction and Abstractionmentioning

confidence: 99%

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The social route to abstraction: interaction and diversity enhance performance and transfer in a rule-based categorization task

Tylén¹,

Fusaroli²,

Smith³

et al. 2020

Preprint

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Capacities for abstract thinking, category-formation and problem solving are central to human cognition. Processes of abstraction allow the transfer of experiences and knowledge between contexts helping us make informed decisions in new or changing contexts. While we are often inclined to relate such reasoning capacities to individual minds and brains, they may in fact be contingent on human-specific modes of collaboration, dialogue, and shared attention. In an experimental study, we test the hypothesis that social interaction enhances cognitive processes of abstraction, which in turn improves problem solving performance. Through three sessions of increasing complexity, individuals and groups were presented with a problem-solving task requiring them to categorize a set of visual stimuli. To assess the character of participants’ problem representations, we investigated the extent to which participants generalized observations from known to new stimuli during training sessions. Furthermore, after each training session they were presented with a transfer task involving stimuli that differed in appearance, but shared relations among features with the training set. We found that groups were more likely to correctly generalize their observations during the training sessions and performed superior to individuals in the transfer phase, especially in the high complexity session, suggesting that groups formed more abstract problem representations. Crucially, variation in performance among groups was predicted by semantic diversity in members’ dialogical contributions suggesting a link between social interaction, cognitive diversity, and abstraction.

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Section: Diversity and Complexitymentioning

confidence: 91%

Section: Social Interaction and Abstractionmentioning

confidence: 99%

The social route to abstraction: interaction and diversity enhance performance and transfer in a rule-based categorization task

Tylén¹,

Fusaroli²,

Smith³

et al. 2020

Preprint

View full text Add to dashboard Cite

show abstract

“…According to the lexical legacy perspective, our knowledge of words is shaped by our summed experiences of encountering them across varied contexts throughout our lives (Nation, 2017). Contextual diversity refers to the number of different contexts in which a given word occurs, which can impact how that word is learned and subsequently processed (Jones et al, 2017;Raviv et al, 2022). The present experiment examines effects of contextual diversity on the early stages of novel word learning by adults in their native language.…”

Section: Introductionmentioning

confidence: 99%

“…Effects of variability are pervasive across different learning domains. A recent review that integrated evidence from across a range of different fields (Raviv et al, 2022) concluded that variability affects learning in different ways at different stages of learning. They presented evidence that in the earliest stages of learning any increase in variability typically makes initial acquisition more challenging.…”

Section: Introductionmentioning

confidence: 99%

Diversity of narrative context disrupts the early stage of learning the meanings of novel words

Hulme¹,

Begum²,

Nation³

et al. 2022

Preprint

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High quality lexical representations develop through repeated exposures to words in different contexts. This preregistered experiment investigated how diversity of narrative context affects the earliest stages of word learning via reading. Adults (N = 100) learned invented meanings for eight pseudowords, which each occurred in five written paragraphs either within a single coherent narrative context or five different narrative contexts. The words’ semantic features were controlled across conditions to avoid influences from polysemy (lexical ambiguity). Post-tests included graded measures of word-form recall (spelling accuracy) and recognition (multiple-choice), and word-meaning recall (number of semantic features). Diversity of narrative context did not affect word-form learning, but more semantic features were correctly recalled for words trained in a single context. These findings indicate that learning the meanings of novel words is initially boosted by anchoring them to a single coherent narrative discourse.

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“…However, what is often overlooked is that variability can be a great asset for learning as it facilitates generalization (i.e., applying learned behavior to new stimuli): variability may foster the extraction of core features across stimuli through abstraction, concept learning, and rule derivation. In many learning domains, variability acts as a catalyst for generalization [7]. In fact, theoretical studies suggest that the degree of variability during learning determines whether the system specializes on specific stimuli by memorizing them or instead learns generalizable rules [8].…”

Section: Introductionmentioning

confidence: 99%

Variability in training unlocks generalization in visual perceptual learning through invariant representations

Manenti

Dizaji

Schwiedrzik

2022

Preprint

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Stimulus and location specificity are long considered hallmarks of visual perceptual learning. This renders visual perceptual learning distinct from other forms of learning, where generalization can be more easily attained, and unsuitable for practical applications, where generalization is key. Based on hypotheses derived from the structure of the visual system, we test here whether stimulus variability can unlock generalization in perceptual learning. We train subjects in orientation discrimination, while we vary the amount of variability in a task-irrelevant feature, spatial frequency. We find that independently of task difficulty, this manipulation enables generalization of learning to new stimuli and locations, while not negatively affecting the overall amount of learning on the task. We then use deep neural networks which recapitulate our findings in humans to investigate how variability unlocks generalization. We find that networks develop invariance to the task-irrelevant feature when trained with variable inputs. The degree of learned invariance strongly predicts generalization. A reliance on invariant representations can explain variability-induced generalization in visual perceptual learning, suggests new targets for understanding the neural basis of perceptual learning in high-order visual cortex, and presents an easy to implement modification of common training paradigms that may benefit practical applications.

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How variability shapes learning and generalization

Cited by 105 publications

References 158 publications

The social route to abstraction: interaction and diversity enhance performance and transfer in a rule-based categorization task

The social route to abstraction: interaction and diversity enhance performance and transfer in a rule-based categorization task

Diversity of narrative context disrupts the early stage of learning the meanings of novel words

Variability in training unlocks generalization in visual perceptual learning through invariant representations

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