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Cognitive Psychology, Cognitive Development, History Instruction, Piagetian Theory, Cognitive Processes, Evidence, Empathy, History, Epistemology, Prior Learning, Transfer of Training, Learning Theories, and Mastery Learning

History teaching and learning make intellectual demands on both teachers and students, requiring them to travel back in time and engage with complex issues and distant lifestyles. History education research advocates the use of approaches that portray History as an intellectually engaging subject but the application of cognitive research to History has not received much attention in recent times. This article focuses on the role of cognitive psychology in the teaching and learning of History and argues for a linkage between Piaget's concept of intellectual development and History pedagogy. The article suggests that even though the application of substantive and procedural concepts are necessary for attaining historical understanding, thoughtful consideration of the cognitive processes of knowledge construction is essential for progression in thinking and understanding.

Statistical Analysis, Hierarchical Linear Modeling, Cognitive Psychology, Neurosciences, Bayesian Statistics, Causal Models, Experiments, and Hypothesis Testing

Statistical mediation allows researchers to investigate potential causal effects of experimental manipulations through intervening variables. It is a powerful tool for assessing the presence and strength of postulated causal mechanisms. Although mediation is used in certain areas of psychology, it is rarely applied in cognitive psychology and neuroscience. One reason for the scarcity of applications is that these areas of psychology commonly employ within-subjects designs, and mediation models for within-subjects data are considerably more complicated than for between-subjects data. Here, we draw attention to the importance and ubiquity of mediational hypotheses in within-subjects designs, and we present a general and flexible software package for conducting Bayesian within-subjects mediation analyses in the R programming environment. We use experimental data from cognitive psychology to illustrate the benefits of within-subject mediation for theory testing and comparison.

Visualization, Data Analysis, Evaluative Thinking, Statistical Inference, Decision Making, Cognitive Psychology, Research Methodology, Cognitive Processes, Design, and Research Design

Understanding human judgement and decision making during visual inspection of data is of both practical and theoretical interest. While visualizing data is a commonly employed mechanism to support complex cognitive processes such as inference, judgement, and decision making, the process of supporting and scaffolding cognition through effective design is less well understood. Applying insights from cognitive psychology and visualization science, this paper critically discusses the role of human factors -- visual attention, perception, judgement, and decision making -- toward informing methodological choices when visualizing data. The value of visualizing data is discussed in two key domains: (1) visualizing data as a means of communication; and (2) visualizing data as research methodology. The first applies cognitive science principles and research evidence to inform data visualization design for communication. The second applies data- and cognitive-science to deepen our understanding of data, of its uncertainty, and of analysis when making inferences. The evidence for human capacity limitations -- attention and cognition -- are discussed in the context of data visualizations to support inference-making in both domains, and are followed by recommendations. Finally, how learning analytics can further research on understanding the role data visualizations can play in supporting complex cognition is proposed.