In mixed methods approaches, statistical models are used to identify "nested" cases for intensive, small-n investigation for a range of purposes, including notably the examination of causal mechanisms. This article shows that under a commonsense interpretation of causal effects, large-n models allow no reliable conclusions about effect…

Background: Observation Studies, Unmeasured Confounding, and Sensitivity Analysis: An important part of educational research is identifying important, potentially causal, factors that influence children's learning from observational studies. However, it is well-known that discovering such factors from observational studies can be biased due to…

There are usually limited user evaluation of resources on a recommender system, which caused an extremely sparse user rating matrix, and this greatly reduce the accuracy of personalized recommendation, especially for new users or new items. This paper presents a recommendation method based on rating prediction using causal association rules.…

The present study aims at delving into English as foreign language teachers' attributions by investigating the role of teacher attributions in teacher burnout and teacher self-regulation. This is accomplished by building a causal structural model through which the associations among these constructs are estimated. The results demonstrate that…

Discounting is a phenomenon in causal reasoning in which the presence of one cause casts doubt on another. We provide a survey of the descriptive and formal models that attempt to explain the discounting process and summarize what current models do not account for and where room for improvement exists. We propose a levels-of-analysis framework…

A fundamental issue for theories of human induction is to specify constraints on potential inferences. For inferences based on shared category membership, an analogy, and/or a relational schema, it appears that the basic goal of induction is to make accurate and goal-relevant inferences that are sensitive to uncertainty. People can use source…

Little is known about the influence of language background in problem-based learning (PBL) tutorial groups on group processes and students' academic achievement. This study investigated the relationship between language background, secondary school score, tutorial group processes, and students' academic achievement in PBL. A validated tutorial…

Causal reasoning represents one of the most basic and important cognitive processes that underpin all higher-order activities, such as conceptual understanding and problem solving. Hume called causality the "cement of the universe" [Hume (1739/2000). Causal reasoning is required for making predictions, drawing implications and…

This article considers how people judge the identity of objects (e.g., how people decide that a description of an object at one time, t-sub-0, belongs to the same object as a description of it at another time, t-sub-1). The authors propose a causal continuer model for these judgments, based on an earlier theory by Nozick (1981). According to this…

A normative framework for modeling causal and counterfactual reasoning has been proposed by Spirtes, Glymour, and Scheines (1993; cf. Pearl, 2000). The framework takes as fundamental that reasoning from observation and intervention differ. Intervention includes actual manipulation as well as counterfactual manipulation of a model via thought. To…