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Ong, Jia Hoong; Liu, Fang – Journal of Autism and Developmental Disorders, 2023
According to Bayesian/predictive coding models of autism, autistic individuals may have difficulties learning probabilistic cue-outcome associations, but empirical evidence has been mixed. The target cues used in previous studies were often straightforward and might not reflect real-life learning of such associations which requires learners to…
Descriptors: Autism Spectrum Disorders, Probability, Cues, Associative Learning
Miranda N. Long; Darko Odic – Child Development, 2025
Children rely on their Approximate Number System to intuitively perceive number. Such adaptations often exhibit sensitivity to real-world statistics. This study investigates a potential manifestation of the ANS's sensitivity to real-world statistics: a negative power-law distribution of objects in natural scenes should be reflected in children's…
Descriptors: Number Concepts, Numeracy, Intuition, Mathematics Education
Levy, Roy – Measurement: Interdisciplinary Research and Perspectives, 2022
Obtaining values for latent variables in factor analysis models, also referred to as factor scores, has long been of interest to researchers. However, many treatments of factor analysis do not focus on inference about the latent variables, and even fewer do so from a Bayesian perspective. Researchers may therefore be ill-acquainted with Bayesian…
Descriptors: Factor Analysis, Bayesian Statistics, Inferences, Decision Making
Deon T. Benton; David Kamper; Rebecca M. Beaton; David M. Sobel – Developmental Science, 2024
Causal reasoning is a fundamental cognitive ability that enables individuals to learn about the complex interactions in the world around them. However, the mechanisms that underpin causal reasoning are not well understood. For example, it remains unresolved whether children's causal inferences are best explained by Bayesian inference or…
Descriptors: Preschool Children, Thinking Skills, Associative Learning, Abstract Reasoning
Hayes, Brett K.; Liew, Shi Xian; Desai, Saoirse Connor; Navarro, Danielle J.; Wen, Yuhang – Journal of Experimental Psychology: Learning, Memory, and Cognition, 2023
The samples of evidence we use to make inferences in everyday and formal settings are often subject to selection biases. Two property induction experiments examined group and individual sensitivity to one type of selection bias: sampling frames - causal constraints that only allow certain types of instances to be sampled. Group data from both…
Descriptors: Logical Thinking, Inferences, Bias, Individual Differences
Minju Kim; Adena Schachner – Developmental Science, 2025
Listening to music activates representations of movement and social agents. Why? We test whether causal reasoning plays a role, and find that from childhood, people can intuitively reason about how musical sounds were generated, inferring the events and agents that caused the sounds. In Experiment 1 (N = 120, pre-registered), 6-year-old children…
Descriptors: Causal Models, Abstract Reasoning, Thinking Skills, Music
Li, Tenglong; Frank, Ken – Sociological Methods & Research, 2022
The internal validity of observational study is often subject to debate. In this study, we define the counterfactuals as the unobserved sample and intend to quantify its relationship with the null hypothesis statistical testing (NHST). We propose the probability of a robust inference for internal validity, that is, the PIV, as a robustness index…
Descriptors: Probability, Inferences, Validity, Correlation
W. Jake Thompson – Grantee Submission, 2023
In educational and psychological research, we are often interested in discrete latent states of individuals responding to an assessment (e.g., proficiency or non-proficiency on educational standards, the presence or absence of a psychological disorder). Diagnostic classification models (DCMs; also called cognitive diagnostic models [CDMs]) are a…
Descriptors: Bayesian Statistics, Measurement, Psychometrics, Educational Research
Austerweil, Joseph L.; Sanborn, Sophia; Griffiths, Thomas L. – Cognitive Science, 2019
Generalization is a fundamental problem solved by every cognitive system in essentially every domain. Although it is known that how people generalize varies in complex ways depending on the context or domain, it is an open question how people "learn" the appropriate way to generalize for a new context. To understand this capability, we…
Descriptors: Generalization, Logical Thinking, Inferences, Bayesian Statistics
Starns, Jeffrey J.; Cohen, Andrew L.; Vargas, John M.; Lougee-Rodriguez, William F. – Journal of Statistics and Data Science Education, 2021
We developed and tested strategies for using spatial representations to help students understand core probability concepts, including the multiplication rule for computing a joint probability from a marginal and conditional probability, interpreting an odds value as the ratio of two probabilities, and Bayesian inference. The general goal of these…
Descriptors: Active Learning, Probability, Statistics Education, Concept Formation
Baek, Eunkyeng; Beretvas, S. Natasha; Van den Noortgate, Wim; Ferron, John M. – Journal of Experimental Education, 2020
Recently, researchers have used multilevel models for estimating intervention effects in single-case experiments that include replications across participants (e.g., multiple baseline designs) or for combining results across multiple single-case studies. Researchers estimating these multilevel models have primarily relied on restricted maximum…
Descriptors: Bayesian Statistics, Intervention, Case Studies, Monte Carlo Methods
Rodríguez-Ferreiro, Javier; Vadillo, Miguel A.; Barberia, Itxaso – Teaching of Psychology, 2023
Background: We have previously presented two educational interventions aimed to diminish causal illusions and promote critical thinking. In both cases, these interventions reduced causal illusions developed in response to active contingency learning tasks, in which participants were able to decide whether to introduce the potential cause in each…
Descriptors: Sampling, Inferences, Psychology, Undergraduate Students
Hinterecker, Thomas; Knauff, Markus; Johnson-Laird, P. N. – Journal of Experimental Psychology: Learning, Memory, and Cognition, 2019
Individuals draw conclusions about possibilities from assertions that make no explicit reference to them. The model theory postulates that assertions such as disjunctions refer to possibilities. Hence, a disjunction of the sort, "A or B or both," where "A" and "B" are sensible clauses, yields mental models of an…
Descriptors: Logical Thinking, Abstract Reasoning, Inferences, Probability
Jack Dempsey; Kiel Christianson; Julie A. Van Dyke – Reading and Writing: An Interdisciplinary Journal, 2025
Typical print formatting provides no information regarding the linguistic features of a text, although texts vary considerably with respect to grammatical complexity and readability. Complex texts may be particularly challenging for individuals with weak language knowledge, such as English language learners. This paper investigates the usefulness…
Descriptors: Reading Comprehension, Mandarin Chinese, Korean, Native Language
Piepho, Hans-Peter; Madden, Laurence V. – Research Synthesis Methods, 2022
Network meta-analysis is a popular method to synthesize the information obtained in a systematic review of studies (e.g., randomized clinical trials) involving subsets of multiple treatments of interest. The dominant method of analysis employs within-study information on treatment contrasts and integrates this over a network of studies. One…
Descriptors: Medical Research, Meta Analysis, Networks, Drug Therapy