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Record W2765156980

Children's Causal Learning from Fiction: Assessing the Proximity Between Real and Fictional Worlds - eScholarship

2012· article· en· W2765156980 on OpenAlexaboutno aff
Caren M. Walker, Patricia A. Ganea, Alison Gopnik

Bibliographic record

VenueProceedings of the Annual Meeting of the Cognitive Science Society · 2012
Typearticle
Languageen
FieldPsychology
TopicEducational Strategies and Epistemologies
Canadian institutionsnot available
Fundersnot available
KeywordsPremiseFantasyContext (archaeology)PsychologyFictional universeEpistemologyCognitive scienceArtPhilosophyLiteratureHistoryNarrative
DOInot available

Abstract

fetched live from OpenAlex

Children’s Causal Learning from Fiction: Assessing the Proximity Between Real and Fictional Worlds Caren M. Walker 1 , Patricia A. Ganea 2 , & Alison Gopnik 1 (caren.walker@berkeley.edu, patricia.ganea@utoronto.ca, gopnik@berkeley.edu) Psychology Department, University of California, Berkeley, 3210 Tolman Hall, Berkeley, CA 94720 Human Development & Applied Psychology, University of Toronto, 56 Spadina Rd., Toronto, Canada M5R 2TI Abstract this perceived similarity by presenting information in a fictional world that seamlessly interweaves fantasy and reality (Woolley & Cox, 2007). Even in explicitly pedagogical scenarios, teachers often embed their intended curriculum within a fantasy context. This decision is based on the assumption that fictional worlds are more engaging to the young child, and may therefore encourage increased sustained attention and learning of novel material (Harris, 2000; Renninger & Wozniak, 1985). Previous research supports the proposal that fantasy contexts serve to improve children’s performance on certain types of cognitive tasks, such as deductive and syllogistic reasoning and theory of mind (e.g., Dias & Harris, 1988; Dias, Roazzi, & Harris, 2005; Hawkins, Pea, Glick & Scribner, 1984; Richards & Sanderson, 1999; Lillard & Sobel, 1999; Sobel & Lillard, 2001). For example, according to Dias et al. (2005), placing an unfamiliar premise in a fantastical context – particularly when the premise directly contradicts a currently-held theory – allows children to override their natural empirical orientation, or bias to reason in line with their past experiences. It is unknown, however, how learning and generalization of novel causal information (which does not require the suspension of existing knowledge) is affected by the fantastical contexts of the fictional stories in which this information is embedded. The ability to effectively process fictional information is dependent upon a variety of representational skills, including at least two major factors that are unique to learning from fictional material. The first includes the development of a mature concept about the boundary between the fictional and real world, as well as an understanding of what information is more appropriately quarantined to the fictional space. Second, it is necessary for children to develop an understanding of when it is appropriate to transfer information from the fictional to the real world, and what contextual cues should be considered in this decision. The current research explores the early development of each of these factors, and in particular, examines whether children’s sensitivity to contextual cues in fictional worlds changes over the course of development. Fictional information presents a unique challenge to the developing child. Children must learn when it is appropriate to transfer information from the fictional space to the real world and what contextual cues should be considered in this decision. The current research explores children’s causal inferences between fictional representations and reality by examining their developing sensitivity to the proximity of the fictional world to the real world, and the effect of this judgment on their subsequent generalization of novel causal properties. By 3-years of age, children are able to evaluate the data that they receive from fictional stories in order to inform their generalization of novel story content to the real world. Additionally, as children develop, they become better able to discriminate between close (realistic) and far (fantastical) fictional worlds when assessing which stories are likely to provide relevant causal knowledge. Keywords: causal inference; fiction; cognitive development; prior knowledge; representation The ‘Reader’s Dilemma’ Children’s growing knowledge about the world comes from a variety of sources, including their exposure to fictional material. In fact, much of the unfamiliar information that children encounter appears in the context of stories and fantastical representations of the world. Children, like adults, therefore often encounter the “reader’s dilemma”: the need to compartmentalize fictional information to insulate real world knowledge from false facts, and the simultaneous need to incorporate this information due to its potential application to a host of real world topics (Gerrig & Prentice, 1999; Potts, St. John, & Kirson, 1989). There is substantial evidence in developmental psychology that indicates that the ability to distinguish reality from fiction develops significantly during the preschool years (e.g., DeLoache, Pierroutakos, Uttal, Rosengren, & Gottlieb, 1998; Flavell, Flavell, & Green, 1989; Woolley & Cox, 2007; Woolley & Wellman, 1990; Woolley & Van Reet, 2006). However, very little research has explored children’s ability to learn causal information about the real world from their exposure to fictional material. Fictional information presents a unique challenge to the developing child. Research has shown that the transfer of knowledge is generally facilitated by similarity between the context in which the information is learned, and the context in which it is to be applied (Catranbone & Holyoak, 1989; Spencer & Weisberg, 1986). However, many of the learning contexts that are created for young children act to reduce Children’s Beliefs about Fictional Worlds There is a growing literature in developmental psychology regarding when and how children distinguish between fantasy and reality. Methods for testing this distinction vary

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.003
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.064
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0020.002
Scholarly communication0.0000.001
Open science0.0010.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.040
GPT teacher head0.336
Teacher spread0.296 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

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Citations0
Published2012
Admission routes1
Has abstractyes

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