Track Program Chairs

2008

Nian-Shing Chen [Coordinator]

National Yunlin University of Science and Technology, Chinese Taiwan
dr.huang-200

Ronghuai Huang

Beijing Normal University, China
University of North Texas portrait of Dr. Kinshuk, dean of the College of Information, Photographed on Friday, Sept. 2, 2016 in Denton, Texas. (Gary Payne/UNT Photo)

Kinshuk

University of North Texas, USA
Track 11-AISLE-TPC Co-chair-Alke Marten

Alke Martens

University of Rostock, Germany
Track 11-AISLE-TPC Co-chair-Patricia A. Jaques Maillard

Patricia Mailard

UNISINOS, Brazil

Track Description and Topics of Interest:

Broadly defined, the Artificial Intelligence and 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. AISLE@ICALT2019 will explore various dimensions of the application of artificial intelligence and the emerging 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.

Track Program Committee

Anarosa Alves Franco Brandão, USP, Brazil
Farshad Badie, Aalborg University, Denmark
Débora Barbosa, FEEVALE, Brazil
Jorge Barbosa, UNISINOS, Brazil
Josep Blat, Universitat Pompeu Fabra, Spain
Leônidas Brandão, USP, Brazil
Cristian Cechinel, UFPel, Brazil
Ben Chang, National Central University, Taiwan
Bertrand David, Ecole Centrale de Lyon, France
Diego Dermeval, UFAL, Brazil
Fabiano Dorça, UFU, Brazil
Mikhail Fominykh, Norwegian University of Science and Technology, Norway
Isabela Gasparini, UDESC, Brazil
Gheorghita Ghinea, Brunel University, UK
Jui-Rong Hung, Boise State University, USA
Wu-Yuin Hwang, National Central University, Taiwan
Ming-Chi Liu, Feng Chia University, Taiwan
Jia-Jiunn Lo, Chung-Hua University, Taiwan
Leonardo Marques, UFAL, Brazil
Eleandro Maschio, UTFPR, Brazil
Gilbert Paquette, LICEF - TELUQ, Canada
Bernardo Pereira Nunes, PUC-RIO, Brazil
André Raabe, UNIVALI, Brazil
Eliseo Reategui, UFRGS, Brazil
Sandro Rigo, UNISINOS, Brazil
Jun-Ming Su, National University of Tainan, Taiwan
Yu-Sheng (Addison) Su, National Central University, Taiwan
Bernardo Tabuenca, Universidad Politécnica de Madrid, Spain
Leandro Krug Wives, UFRGS, Brazil
Guangbing Yang, University of Eastern Finland, Finland
Stephen J.H. Yang, National Central University, Taiwan
Matej Zajc, University of Ljubljana, Slovenia
Jinghua Zhang, Winston-Salem State University, USA