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Culture, musicality, and musical expertise

Susan Hallam

in A Cultural Psychology of Music Education

This chapter focuses on the processes concerned with learning and the development of musical expertise which are common to all human beings but which develop differentially depending on the ... More

This chapter focuses on the processes concerned with learning and the development of musical expertise which are common to all human beings but which develop differentially depending on the environment (cultural and ecological) within which individuals are located. It considers what we know about human learning, the way that the brain develops in response to the particular musical environments to which the individual is exposed, and how these changes are expressed as musical expertise develops. The evidence regarding the importance of long-term engagement with music for expertise to develop is considered and how beliefs about personal efficacy can influence commitment to active music-making. The chapter concludes with a consideration of the different cultural perceptions of ‘musicality’ and changing perceptions of it in Western culture.Less

Rules of Order: Process Models of Human Learning

Josef Nerb, Frank E. Ritter, and Pat Langley

in In Order to Learn: How the sequence of topics influences learning

Science is concerned not only with data, but also with models or theories that explain those data. Because human cognition is dynamic and involves change over time, accounts of cognition often take ... More

Science is concerned not only with data, but also with models or theories that explain those data. Because human cognition is dynamic and involves change over time, accounts of cognition often take the form of process models, which are sometimes called cognitive models. This chapter reviews the form such models have taken and their relation to order effects in learning. It begins by discussing the connection between artificial intelligence (AI) systems, including those from machine learning and computational models of human behavior, including some illustrations of the latter. It presents a computational model of order effects on a cognitive task, cast within a particular but simplified theoretical framework. It then explores more broadly the possible sources of order effects within such models and then briefly considers an alternative approach that models human behavior at a more abstract level. The chapter closes with some open problems in the area of modeling order effects and a charge to new modelers.Less

Human–Automated Judgment Learning: Enhancing Interaction with Automated Judgment Systems

Ellen J. Bass and Amy R. Pritchett

in Adaptive Perspectives on Human–Technology Interaction: Methods and Models for Cognitive Engineering and Human-Computer Interaction

This chapter presents a methodology for investigating human interaction with automated judges capable of informing training and design: human-automated judgment learning (HAJL). After introducing ... More

This chapter presents a methodology for investigating human interaction with automated judges capable of informing training and design: human-automated judgment learning (HAJL). After introducing HAJL, it describes the experimental task and experimental design used as a test case for investigating HAJL's utility. Then, idiographic results representative of the insights that HAJL can bring and a nomothetic analysis of the experimental manipulations are reported. It ends with conclusions surrounding HAJL's utility. The results showed the HAJL's ability not only to capture individual judgment achievement, interaction with an automated judge, and understanding of an automated judge but also to identify the mechanisms underlying these performance measures, including cognitive control, knowledge, conflict, compromise, adaptation, and actual and assumed similarity. In addition, it highlights the number of factors that go into designing effective human-automated judge interaction, which require detailed methods for measurement and analysis.Less

The Challenge of Novelty

Kim Sterelny

in The Evolved Apprentice: How Evolution Made Humans Unique

This chapter argues for two crucial ideas. First, over deep history and at different times and places, humans have experienced very different physical, biological, economic and social environments. ... More

This chapter argues for two crucial ideas. First, over deep history and at different times and places, humans have experienced very different physical, biological, economic and social environments. Even as foragers, our ancestors experienced different worlds, but over the last 10,000 years change has become more frequent and intense. As a consequence, human adaptive response to the many environments with which we have coped cannot solely or primarily be based on innate, genetically programmed capacities. Social learning is the engine of human adaptability. Second, while defenders of the social intelligence hypothesis are right to emphasise the cognitive challenges posed by human social environments, they have typically over-rated the importance of deception and manipulation, and under-rated the cognitive challenge of coordination. Humans evolved as technically skilled, ecologically informed, cooperative foragers, and that was a cognitively demanding lifeway, especially given the dynamism of human environments.Less

Through the looking glass: a dynamic lens model approach to multiple cue probability learning

Maarten Speekenbrink and David R. Shanks

in The Probabilistic Mind:: Prospects for Bayesian cognitive science

This chapter considers a probabilistic perspective on a classic problem of human contingency learning: finding the relationships between a category or outcome, for which there are several ... More

This chapter considers a probabilistic perspective on a classic problem of human contingency learning: finding the relationships between a category or outcome, for which there are several probabilistic cues. It provides an analysis within the framework of Brunswik's (1955) lens model. It focuses on the dynamics of learning, e.g. the rate of learning and how the learner may respond to changing contingencies — which are, presumably, the norm, in many real-world contexts.Less

John Dewey: His Life and Work

Larry A. Hickman

in John Dewey Between Pragmatism and Constructivism

This chapter presents an overview of John Dewey's life and work. John Dewey was born in Burlington, Vermont, the third of four sons of Archibald Sprague Dewey and Lucina ... More

This chapter presents an overview of John Dewey's life and work. John Dewey was born in Burlington, Vermont, the third of four sons of Archibald Sprague Dewey and Lucina Artemesia Rich Dewey. In 1949, on the occasion of his ninetieth birthday, Dewey was hailed by the New York Times as “America's Philosopher”. He died at his apartment on New York City on June 1, 1952. During his long and productive life, Dewey wrote widely about psychology, philosophy, art, and social issues. The chapter focuses on three general topics that are recurring themes in Dewey's work. The themes are: (1) his concept of the purpose and process of human learning; (2) his understanding of truth as a process, instead of something absolute and unchanging; and (3) his faith in democracy as the only means of social organization that can foster individual fulfillment, and its implications for education and the arts.Less

Learning and Learning to Learn

in Inside Man: The Discipline of Modeling Human Ways of Being

This chapter, which examines the modeling of human learning, proposes a particular model of learning and shows that it can accommodate basic insights and intuitions about learning. It considers some ... More

This chapter, which examines the modeling of human learning, proposes a particular model of learning and shows that it can accommodate basic insights and intuitions about learning. It considers some basic choices in modeling deterministic behaviorism, inductivism, and fallibilism. The chapter also discusses the capability of the proposed model to salvage both the “betting odds” interpretation of personal degrees of belief and the fallibilist approach that undergirds inference from the known to the unknown.Less