Open AccessDeveloping a Taxonomy of Informal Learning Space
Author(s) -
David Chin,
Cheng Hsu,
Oscar K.T. Yau
Publication year - 2021
Publication title -
international journal of education
Language(s) - English
Resource type - Journals
ISSN - 1948-5476
DOI - 10.5296/ije.v13i4.19016
Subject(s) - taxonomy (biology) , comparability , card sorting , computer science , generalization , knowledge management , underpinning , space (punctuation) , management science , mathematics education , psychology , engineering , mathematics , task (project management) , mathematical analysis , botany , civil engineering , systems engineering , combinatorics , biology , operating system
The move from traditional teaching-centred approach to student-centred approach has resulted in more student collaboration outside classroom, contributing to the growing importance of information learning space (ILS). Review of recent literature suggests the ILS research agenda is at an initial stage of development, without convergence in research methods and lacks theoretical underpinning. Research studies were conducted on a piece meal basis, lacking comparability and generalization. Using a mixed-method approach, this study contributes to ILS knowledge by introducing a qualitative methodology based on concept mapping and sorting for idea generation; to develop a taxonomy of four user-generated ILS types from a portfolio of 38 ILS sites on campus. This is followed by quantitative validation using seven ILS sites to evaluate satisfaction and usage behaviour. Drawing from middle range theory and the ILS taxonomy, practical design principles are proposed based on functionalities and features for the four ILS types. The learnings can be shared with designers, policy makers and different institutions to facilitate knowledge transfer, which contributes to generalization of learnings and theory building.