A study of children’s musical preference: A data mining approach

Musical preference has long been a research interest in the field of music education, and studies consistently confirm the importance of musical preference in one’s musical learning experiences. However, only a limited number of studies have been focussed on the field of early childhood education (e.g., Hargreaves, North, & Tarrant, 2006; Roulston, 2006). Further, among these limited early childhood studies, few of them discuss children’s musical preference in both the East and the West. There is very limited literature (e.g., Faulkner et al., 2010; Szymanska, 2012) which explores the data by using a data mining approach. This study aims to bridge the research gaps by examining children’s musical preference in Hong Kong and in South Australia by applying a data mining technique – Self Organising Maps (SOM), which is a clustering method that groups similar data objects together. The application of SOM is new in the field of early childhood education and also in the study of children’s musical preference. This paper specifically aims to expand a previous study (Yim & Ebbeck, 2009) by conducting deeper investigations into the existing datasets, for the purpose of uncovering insights that have not been identified through data mining approach

Evaluation of school-based arts education programmes in Australian schools

This report presents evaluations of four Australian school-based arts programmes: Arts@Direk (SA), Boys’ Business (NT), Indigenous Music Education Programme (NT), and SCRAYP – Youth Arts with an Edge (Vic). Arts@Direk and SCRAYP provided a focus on drama, while Boys’ Business and Indigenous Music Education Programme (IMEP) concentrated on music. There was a range of ages from Year 4 to Year 10 and a diverse range of backgrounds amongst the participating students. The study investigated the impact of each arts programme on students’ academic progress, engagement with learning and school attendance. It also considered which attributes of arts programmes were of particular benefit to the students

Pattern languages in HCI: A critical review

This article presents a critical review of patterns and pattern languages in human-computer interaction (HCI). In recent years, patterns and pattern languages have received considerable attention in HCI for their potential as a means for developing and communicating information and knowledge to support good design. This review examines the background to patterns and pattern languages in HCI, and seeks to locate pattern languages in relation to other approaches to interaction design. The review explores four key issues: What is a pattern? What is a pattern language? How are patterns and pattern languages used? and How are values reflected in the pattern-based approach to design? Following on from the review, a future research agenda is proposed for patterns and pattern languages in HCI

Distances in the field : mapping similarity and familiarity in the production, curation and consumption of Australian art music

This thesis provides a timely intervention in the investigation of cultural fields by employing traditional and new data analytics to expand our understanding of fields as multi-dimensional sites of production, curation and consumption. Through a case study of contemporary Australian art music, the research explores the multiple ways in which the concept of ‘distance’ contributes to how we conceive of and engage with fields of artistic practice. While the concept of distance has often been an implicit or axiomatic concern for cultural sociology, this thesis foregrounds how it can be used to analyse fields from multiple perspectives, at multiple scales of enquiry and using diverse methodologies. In doing so, it distinguishes between notions of distance in the related concepts of similarity and familiarity. In the former, the relative proximities of cultural producers can be mapped to discern and contrast the organising principles which underlie different perspectives of a field. In the latter, the degree of an individual’s familiarity with an item or genre can be included in theorisations of cultural preferences and their social dimensions. This is disrupted in a field such as Australian art music, however, as its emphasis on experimentation and innovation presents barriers to developing familiarity. Distance can be considered a defining characteristic of this field, and motivates its selection as a critical case study from which to investigate how audiences form attachments to distant musical sounds. The investigation of distance from multiple perspectives, using different scales of analysis and across a series of focal points in the lifecycle of artist practice, provides an analysis of Australian art music in terms of the tensions which emerge from these intersecting representations of the field. The singular spatial representation of ‘objective relations’ in a field, and a concern with power and domination – as found in the approach of Bourdieu – is replaced by a multiplicity of sets of relations and a concern with their organising principles and juxtapositions. The thesis argues that the actor constellations which distances produce are intimately linked to our capacity to engage with fields as discrete and knowable domains of cultural practice. Beyond our capacity to know a cultural field, it also argues for the importance of reconsidering how we form attachments to distant musical tastes. As an avant-garde genre which embraces foreign and confounding sounds, audiences require the capacity to draw on a range of consumption strategies and techniques to successfully engage with and value the unfamiliar

Chapter 1 : Learning Online

The OTiS (Online Teaching in Scotland) programme, run by the now defunct Scotcit programme, ran an International e-Workshop on Developing Online Tutoring Skills which was held between 8–12 May 2000. It was organised by Heriot–Watt University, Edinburgh and The Robert Gordon University, Aberdeen, UK. Out of this workshop came the seminal Online Tutoring E-Book, a generic primer on e-learning pedagogy and methodology, full of practical implementation guidelines. Although the Scotcit programme ended some years ago, the E-Book has been copied to the SONET site as a series of PDF files, which are now available via the ALT Open Access Repository. The editor, Carol Higgison, is currently working in e-learning at the University of Bradford (see her staff profile) and is the Chair of the Association for Learning Technology (ALT)

Making sense of assets: Community asset mapping and related approaches for cultivating capacities

This working paper critically reviews some main aspects from asset based approaches highlights key strengths and weaknesses for future research/development. Drawing on a large body of reports and relevant literature we draw on different theoretical traditions and critiques, as well as practices and processes embedded within a broad range of approaches including, widely acknowledged frameworks such Asset Based Community Development (ABCD), Appreciative Inquiry (AI), Sustainable Livelihood Approaches (SLA) and Community Capitals Framework (CCF). Although these are presented as distinct approaches, there is a sense of evolution through them and many of them overlap (in terms of both theories and methodologies). We also include emerging frameworks, including geographical, socio-spatial, visual and creative approaches, stemming from a number of projects within AHRC’s Connected Communities programme and additional collaborations

Making music through real-time voice timbre analysis: machine learning and timbral control

PhDPeople can achieve rich musical expression through vocal sound { see for example human beatboxing, which achieves a wide timbral variety through a range of extended techniques. Yet the vocal modality is under-exploited as a controller for music systems. If we can analyse a vocal performance suitably in real time, then this information could be used to create voice-based interfaces with the potential for intuitive and ful lling levels of expressive control. Conversely, many modern techniques for music synthesis do not imply any particular interface. Should a given parameter be controlled via a MIDI keyboard, or a slider/fader, or a rotary dial? Automatic vocal analysis could provide a fruitful basis for expressive interfaces to such electronic musical instruments. The principal questions in applying vocal-based control are how to extract musically meaningful information from the voice signal in real time, and how to convert that information suitably into control data. In this thesis we address these questions, with a focus on timbral control, and in particular we develop approaches that can be used with a wide variety of musical instruments by applying machine learning techniques to automatically derive the mappings between expressive audio input and control output. The vocal audio signal is construed to include a broad range of expression, in particular encompassing the extended techniques used in human beatboxing. The central contribution of this work is the application of supervised and unsupervised machine learning techniques to automatically map vocal timbre to synthesiser timbre and controls. Component contributions include a delayed decision-making strategy for low-latency sound classi cation, a regression-tree method to learn associations between regions of two unlabelled datasets, a fast estimator of multidimensional di erential entropy and a qualitative method for evaluating musical interfaces based on discourse analysis

Measuring Expressive Music Performances: a Performance Science Model using Symbolic Approximation

Music Performance Science (MPS), sometimes termed systematic musicology in Northern Europe, is concerned with designing, testing and applying quantitative measurements to music performances. It has applications in art musics, jazz and other genres. It is least concerned with aesthetic judgements or with ontological considerations of artworks that stand alone from their instantiations in performances. Musicians deliver expressive performances by manipulating multiple, simultaneous variables including, but not limited to: tempo, acceleration and deceleration, dynamics, rates of change of dynamic levels, intonation and articulation. There are significant complexities when handling multivariate music datasets of significant scale. A critical issue in analyzing any types of large datasets is the likelihood of detecting meaningless relationships the more dimensions are included. One possible choice is to create algorithms that address both volume and complexity. Another, and the approach chosen here, is to apply techniques that reduce both the dimensionality and numerosity of the music datasets while assuring the statistical significance of results. This dissertation describes a flexible computational model, based on symbolic approximation of timeseries, that can extract time-related characteristics of music performances to generate performance fingerprints (dissimilarities from an ‘average performance’) to be used for comparative purposes. The model is applied to recordings of Arnold Schoenberg’s Phantasy for Violin with Piano Accompaniment, Opus 47 (1949), having initially been validated on Chopin Mazurkas.1 The results are subsequently used to test hypotheses about evolution in performance styles of the Phantasy since its composition. It is hoped that further research will examine other works and types of music in order to improve this model and make it useful to other music researchers. In addition to its benefits for performance analysis, it is suggested that the model has clear applications at least in music fraud detection, Music Information Retrieval (MIR) and in pedagogical applications for music education

Analysis of Summa by Arvo Pärt

Includes bibliographical references.This study presents a musical analysis using a process of pitch mapping. Pitch rows are presented graphically to demonstrate the visual design of the music. Description of the process is preceded by a discussion of some of the historical, and philosophical factors that are relevant to the development of Pärt’s tintinnabuli music. The musical and political history of Estonia and some of its other composers are presented as an important resource for understanding Pärt’s music. The use of proportions and formulas in the music is presented as being connected to a long line of similar practice in the fields of music, mathematics, physics and astronomy that has been used in the pursuit of an understanding of the Universe. Although informed by an extensive depth of spirituality, research and construction, the music remains an intensely personal expression of the composer. In this combination of structure and intuition it is able to resonate with people across many different cultures, and across many visible and invisible boundaries. Through the establishment of tonal stability in tintinnabuli music, extra-musical codes and symbols can be placed within its structure. This is achieved through a compositional process that includes both highly organized proportional formulas and creative intuition. The process of pitch mapping as a method of musical analysis demonstrates how this can be done. Pitch mapping is presented as a creative process of musical analysis. Visual images and animated visual images are used to add to an understanding of the music

Conflicts, integration, hybridization of subcultures: An ecological approach to the case of queercore

This paper investigates the case study of queercore, providing a socio-historical analysis of its subcultural production, in the terms of what Michel Foucault has called archaeology of knowledge (1969). In particular, we will focus on: the self-definition of the movement; the conflicts between the two merged worlds of punk and queer culture; the \u201cinternal-subcultural\u201d conflicts between both queercore and punk, and between queercore and gay\lesbian music culture; the political aspects of differentiation. In the conclusion, we will offer an innovative theoretical proposal about the interpretation of subcultures in ecological and semiotic terms, combining the contribution of the American sociologist Andrew Abbot and of the Russian semiologist Jurij Michajlovi\u10d Lotma