In the last decade, the design practice has been widely crossing disciplines and their inputs, acting as a mediator among Fine Arts, Humanities, Economics, Technology and Engineering sciences. Not only the cross-fertilization among methodologies and research tools has empowered design practice’s ability to modeling cultural contexts but also Web 2.0, social media and big data has dramatically changed the design perspective and reach and, in particular its fuzzy front end stage represented by trend research. Traditionally, trend research aims to orienting the design practice starting from the identification of relevant signals in various areas of search that inform the further design phases. It is a hybrid research activity, which moves from quantitative analysis and forecasting on product’s aesthetic and perceptive characteristics—such as color and shape—and on markets figures—in regard of consumer’s consumption habits, companies’ market positioning and growth, and sale data—to a field qualitative analysis on socio-cultural contexts. Referring to this latter qualitative dimension, trend research borrows tools from humanistic disciplines to scanning and deep diving socio-political systems—that defines the evolution of values and behaviors of the collective imaginary—and core cultural industries [1]—such as art, literature, design, arts&crafts, movie industry, music industry—that express the evolution of symbolic, visual and experiential contents for a certain socio-cultural group. So, trend research is meant to examine the Zeitgeist, ‘the spirit of the time’, and revealing predominant cultural trends in a certain age [2]. Nowadays, the potentialities offered by social media sensing and data science allows to implement this practice, its scope and its outputs’ relevancy augmenting both quantitative and qualitative dimension of research’s breadth and depth. Within this framework, the present paper will present a blended learning experience focused on a trend research activity based on the use of Nextatlas, a digital data-driven trend research platform, developed with the Metadesign Studio classes offered in the Product Design, Fashion Design and Interior Design undergraduate programs of the Design School at Politecnico di Milano. Reflecting on the planning and the implementation of this blended learning activity the paper will offer insights on how to innovate both the metadesign teaching methodology and learning process.

Innovating trend research practice through a data driven-approach: a blended experience within the design field

M. Celi;C. Colombi
2017

Abstract

In the last decade, the design practice has been widely crossing disciplines and their inputs, acting as a mediator among Fine Arts, Humanities, Economics, Technology and Engineering sciences. Not only the cross-fertilization among methodologies and research tools has empowered design practice’s ability to modeling cultural contexts but also Web 2.0, social media and big data has dramatically changed the design perspective and reach and, in particular its fuzzy front end stage represented by trend research. Traditionally, trend research aims to orienting the design practice starting from the identification of relevant signals in various areas of search that inform the further design phases. It is a hybrid research activity, which moves from quantitative analysis and forecasting on product’s aesthetic and perceptive characteristics—such as color and shape—and on markets figures—in regard of consumer’s consumption habits, companies’ market positioning and growth, and sale data—to a field qualitative analysis on socio-cultural contexts. Referring to this latter qualitative dimension, trend research borrows tools from humanistic disciplines to scanning and deep diving socio-political systems—that defines the evolution of values and behaviors of the collective imaginary—and core cultural industries [1]—such as art, literature, design, arts&crafts, movie industry, music industry—that express the evolution of symbolic, visual and experiential contents for a certain socio-cultural group. So, trend research is meant to examine the Zeitgeist, ‘the spirit of the time’, and revealing predominant cultural trends in a certain age [2]. Nowadays, the potentialities offered by social media sensing and data science allows to implement this practice, its scope and its outputs’ relevancy augmenting both quantitative and qualitative dimension of research’s breadth and depth. Within this framework, the present paper will present a blended learning experience focused on a trend research activity based on the use of Nextatlas, a digital data-driven trend research platform, developed with the Metadesign Studio classes offered in the Product Design, Fashion Design and Interior Design undergraduate programs of the Design School at Politecnico di Milano. Reflecting on the planning and the implementation of this blended learning activity the paper will offer insights on how to innovate both the metadesign teaching methodology and learning process.
ICERI 2017 Proceedings
978-84-697-6957-7
Metadesign, Design Trend research, Data-driven technology, Social Media, Concept development.
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Utilizza questo identificativo per citare o creare un link a questo documento: http://hdl.handle.net/11311/1044268
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