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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
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Vannaprathip, Narumol; Haddawy, Peter; Schultheis, Holger; Suebnukarn, Siriwan – International Journal of Artificial Intelligence in Education, 2022
Virtual reality simulation has had a significant impact on training of psychomotor surgical skills, yet there is still a lack of work on its use to teach surgical decision making. This is particularly noteworthy given the recognized importance of decision making in achieving positive surgical outcomes. With the objective of filling this gap, we…
Descriptors: Intelligent Tutoring Systems, Decision Making, Surgery, Teaching Methods
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Stewart, G. B.; Mengersen, K.; Meader, N. – Research Synthesis Methods, 2014
Bayesian networks (BNs) are tools for representing expert knowledge or evidence. They are especially useful for synthesising evidence or belief concerning a complex intervention, assessing the sensitivity of outcomes to different situations or contextual frameworks and framing decision problems that involve alternative types of intervention.…
Descriptors: Bayesian Statistics, Networks, Cognitive Mapping, Data Collection
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Bramley, Neil R.; Lagnado, David A.; Speekenbrink, Maarten – Journal of Experimental Psychology: Learning, Memory, and Cognition, 2015
Interacting with a system is key to uncovering its causal structure. A computational framework for interventional causal learning has been developed over the last decade, but how real causal learners might achieve or approximate the computations entailed by this framework is still poorly understood. Here we describe an interactive computer task in…
Descriptors: Intervention, Memory, Cognitive Processes, Models
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Solomon, Benjamin G.; Forsberg, Ole J. – School Psychology Quarterly, 2017
Bayesian techniques have become increasingly present in the social sciences, fueled by advances in computer speed and the development of user-friendly software. In this paper, we forward the use of Bayesian Asymmetric Regression (BAR) to monitor intervention responsiveness when using Curriculum-Based Measurement (CBM) to assess oral reading…
Descriptors: Bayesian Statistics, Regression (Statistics), Least Squares Statistics, Evaluation Methods
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Frosch, Caren A.; McCormack, Teresa; Lagnado, David A.; Burns, Patrick – Cognitive Science, 2012
The application of the formal framework of causal Bayesian Networks to children's causal learning provides the motivation to examine the link between judgments about the causal structure of a system, and the ability to make inferences about interventions on components of the system. Three experiments examined whether children are able to make…
Descriptors: Bayesian Statistics, Intervention, Inferences, Attribution Theory
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Hagmayer, York; Sloman, Steven A. – Journal of Experimental Psychology: General, 2009
Causal considerations must be relevant for those making decisions. Whether to bring an umbrella or leave it at home depends on the causal consequences of these options. However, most current decision theories do not address causal reasoning. Here, the authors propose a causal model theory of choice based on causal Bayes nets. The critical ideas…
Descriptors: Causal Models, Inferences, Decision Making, Intervention