Teaching Adaptively for Music - Smart Opportunities Emerging from the Representation of Score Notation
Luca Ludovico, Universit degli Studi di Milano ; Giuseppina Mangione, University of Salerno
Journal of e-Learning and Knowledge Society Volume 10, Number 3, ISSN 1826-6223 e-ISSN 1826-6223 Publisher: Italian e-Learning Association
Many developmental approaches have been proposed in literature and are currently in use in order to define music education curricula for young students. In this context, our research aims at describing a computer-based framework for the adaptive teaching of music. A music learning environment can be considered as smart when adaptive technologies are employed in order to improve student performance. Research about effective teaching practice pointed out that adaptive instruction can provide school settings able to foster inclusion and differentiation. Adaptive instruction can be conceptually defined as a set of alternative didactic strategies – either formal or non-formal – within a curricular program which are able to meet the student needs In our proposal, adaptivity is involved from two different points of view: in fact, adaptivity implies the possibility for the teacher to choose an instruction method fit for the single student, as well as the possibility for students to have a learning environment modelled on their personal plans, , preferences and previous knowledge. This approach can be adopted thanks to a computer-based framework including: i) a multi-layer format to encode music, and ii) an advanced application oriented to music educational content design and fruition. As regards the former aspect, we will briefly introduce an international standard known as IEEE 1599, specifically designed for the comprehensive description of music. The latter aspect will be covered by a software prototype – namely an advanced media player supporting IEEE 1599 documents – freely available via Web.
Ludovico, L. & Mangione, G. (2014). Teaching Adaptively for Music - Smart Opportunities Emerging from the Representation of Score Notation. Journal of e-Learning and Knowledge Society, 10(3),. Italian e-Learning Association.
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