Track Program Chairs


Nian-Shing Chen [Coordinator]

National Yunlin University of Science and Technology, Taiwan

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)


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


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

Tosti Hsu-Cheng Chiang National Taiwan Normal University, Taiwan

Wu-Yuin Hwang National Central University, Taiwan

Bertrand David Ecole Centrale de Lyon

Bernardo Tabuenca Universidad Polit?cnica de Madrid

Ming-Chi Liu Feng Chia University, Taiwan

Jia-Jiunn Lo Chung-Hua University, Taiwan

Jinghua Zhang Winston-Salem State University

Gilbert Paquette LICEF - TELUQ

Gheorghita Ghinea Brunel University

Ben Chang National Central University, Taiwan

Jun-Ming Su National University of Tainan

Matej Zajc University of Ljubljana

Ting-Wen Chang Beijing Normal University

Yu-Sheng (Addison) Su National Central University

Steve Yang National Central University, Taiwan

Jui-Rong Hung Boise State University, USA

MikhailFominykh Norwegian University of Science and Technology

Jorge Barbosa UNISINOS (Brazil)

Isabela Gasparini UDESC (Brazil)

Cristian Cechinel UFPel (Brazil)

Bernardo Pereira Nunes PUC-RIO (Brazil)

Anarosa Brandão USP (Brazil)

Diego Dermeval UFAL (Brazil)

Leonardo Marques UFAL (Brazil)

Sandro Rigo UNISINOS (Brazil)

Eleandro Maschio UTFPR (Brazil)

André Raabe UNIVALI (Brazil)

Leandro Wives UFRGS (Brazil)

Débora Barbosa FEEVALE (Brazil)

Eliseo Reategui UFRGS (Brazil)

Fabiano Dorça UFU (Brazil)

Leônidas Brandão USP (Brazil)

Farshad Badie, Aalborg University, Denmark

Josep Blat, Universitat Pompeu Fabra, Spain

Guangbing Yang, University of Eastern Finland, Finland