Track 14. Smart Learning Environments (SLE@ICALT2016)

Track Chairs

Nian-Shing Chen, National Sun Yat-sen University, Taiwan
Ronghuai Huang, Beijing Normal University, China
Wu-Yuin Hwang, National Central University, Taiwan
Kinshuk, Athabasca University, Canada [Coordinator -]
Alke Martens, University of Rostock, Germany

Track Program Committee

  • Ben Chang, National Central University, Taiwan
  • Bernardo Tabuenca, Open University of Netherlands, The Netherlands
  • Bertrand David, LIRIS-CNRS, France
  • Dirk Börner, Open University of Netherlands, The Netherlands
  • Gilbert Paquette, Université du Québec à Montréal, Canada
  • Jia-Jiunn Lo, Chung Hua University , Taiwan
  • Jinghua Zhang, Winston-Salem State University, USA
  • Johannes Konert, Technische Universitat Darmstadt, Germany
  • Josep Blat, Universitat Pompeu Fabra, Spain
  • Ju-ling Shih, National University Of Tainan, Taiwan
  • Jun-Ming Su, National University of Tainan, Taiwan
  • Ka Wai Wong, Hong Kong Institute of Education, Hong Kong
  • Li Ping, Hong Kong Institute of Education, Hong Kong
  • Matej Zajc, University of Ljubljana, Slovenia
  • Monica Divitini, Norwegian University of Science and Technology, Norway
  • Ting-Wen Chang, Beijing Normal University, China
  • Yanjie Song, The Hong Kong Institute of Education, Hong Kong

Track Description and Topics of Interest

Broadly defined, smart learning environments represent a new wave of educational systems, involving an effective and efficient interplay of pedagogy, technology and their fusion towards the betterment of learning processes. Various components of this interplay include but are not limited to:

  • Pedagogy/didactics: instructional design, learning paradigms, teaching paradigms, environmental factors, assessment paradigms, social factors, policy
  • Technology: emerging technologies, innovative uses of mature technologies, interactions, adoption, usability, standards, and emerging/new technological paradigms (open educational resources, learning analytics, cloud computing, smart classrooms, etc.)
  • Fusion of pedagogy/didactics and technology: transformation of curriculum, transformation of teaching behaviour, transformation of learning, transformation of administration, transformation of schooling, best practices of infusion, piloting of new ideas

A learning environment can be considered smart when the learner is supported through the use of adaptive and innovative technologies from childhood all the way through formal education, and continued during work and adult life where non-formal and informal learning approaches become primary means for learning. Smart learning environments are neither pure technology-based systems nor a particular pedagogical approach. They encompass various contexts, in which students (and perhaps teachers) move from one context to another. So, they are perhaps overarching concept for future academia. This perspective has the potential to overcome some of the traditions of institution based instruction towards lifelong learning.

SLE@ICALT2016 will explore various dimensions of smart learning environments, such as what makes a learning environment smart, challenges in the design and implementation of such environments in multiple and heterogeneous contexts, pedagogical and technological underpinnings, and the validation issues.

Important dates about ICALT 2017 submissions can be found here.

The ICALT 2017 Author Guidelines can be found here.

The Track 14 CfP can be downloaded from here:

  • .txt version
  • .doc version