51 research outputs found

    Music Analysis, Cultural Morality, and Sociology in the Writings of August Halm

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    Music, neurology, and psychology in the nineteenth century

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    This chapter examines connections between research in music, neurology, and psychology during the late-nineteenth century. Researchers in all three disciplines investigated how music is processed by the brain. Psychologists and comparative musicologists, such as Carl Stumpf, thought in terms of multiple levels of sensory processing and mental representation. Early thinking about music processing can be linked to the start of Gestalt psychology. Neurologists such as August Knoblauch also discussed multiple levels of music processing, basing speculation on ideas about language processing. Knoblauch and others attempted to localize music function in the brain. Other neurologists, such as John Hughlings Jackson, discussed a dissociation between music as an emotional system and language as an intellectual system. Richard Wallaschek seems to have been the only one from the late-nineteenth century to synthesize ideas from musicology, psychology, and neurology. He used ideas from psychology to explain music processing and audience reactions and also used case studies from neurology to support arguments about the nature of music. Understanding the history of this research sheds light on the development of all three disciplines—musicology, neurology, and psychology.https://digitalcommons.chapman.edu/music_books/1000/thumbnail.jp

    Educational Data Mining Approaches for Digital Libraries

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    This collaborative research project between the Exploratorium and Utah State\u27s Department of Instructional Technology and Learning Sciences investigates online evaluation approaches and the application of educational data mining to educational digital libraries and services. Much work over the past decades has focused on developing algorithms and methods for discovering patterns in large datasets, known as Knowledge Discovery from Data (KDD). Webmetrics, the application of KDD to web usage mining, is growing rapidly in areas such as e-commerce. Educational Data Mining (EDM) is just beginning to emerge as a tool to analyze the massive, longitudinal user data that are captured in online learning environments and educational digital libraries. This project uses EDM to examine data from the Exploratorium\u27s Learning Resources Collection and the Instructional Architect at Utah State University. The results are combined with more traditional evaluation data (e.g., surveys, interviews) as part of a comprehensive strategy to understand science teachers\u27 behaviors, motivations, and learning experiences with digital library resources. The project informs improvements in the design of the user experience, as well as tailored teacher professional development, contributing to a growing body of research on teacher learning by using cyber-enabled approaches. This poster shares the results from the first year\u27s work

    Tinctoris and signa congruentiae: a new perspective

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    The notational treatises of Johannes Tinctoris are among the most important texts on late fifteenth-century musical practice. His monumental treatise on the art of counterpoint, De arte contrapuncti, affords modern scholars a great insight into the intricacies of counterpoint practice on the cusp of the era of music theory printing. In the examples for this text, Tinctoris regularly uses additional markers to raise the visual profile of specific moments of a musical demonstration. These signs often closely resemble signa congruentiae, though their function in these theoretical contexts is somewhat different from the deployment of such symbols in practical music sources. This article re-examines the historical justification for the term signa congruentiae, offering a new perspective on Tinctoris’s usage of such signs to explicate the rich text–example relationship underpinning his theoretical arguments and drawing attention to some novel uses of these signs to consolidate text-example relationships

    Construction of efficient tree networks: The pipeline problem

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