2017 IEEE 17th International Conference on Advanced Learning Technologies (ICALT)

A new wave of technologies is disrupting innovation in the education sector now more than ever before. Phenomena and technologies such as learning analytics, cloud computing, maker spaces, 3-D printing, wearable technologies, cognitive profiling and augmented reality are just a few examples that have seen early adopters bringing new hope and optimism to the debate about the usefulness and relevance of new technologies and learning support. At the same time, new standards are also emerging with the intention of bringing these innovations to a level where they are widely accepted and sustainable. Such rapid growth of the field is not without mixed blessings, as it changes the ways that people access, design, deploy and support learning, posing challenges for educational organisations, researchers, practitioners and policy makers, especially with regard to the development of advanced technologies that accommodate the needs of a new generation of learners and a changing social environment. The choice of appropriate technologies and their application in emerging learning contexts are huge challenges for 21st century learning technologists.

ICALT is an annual international conference on Advanced Learning Technologies and Technology-enhanced Learning organized by the IEEE Computer Society and the IEEE Technical Committee on Learning Technology. After its kick-off as IWALT in Palmerston North, New Zealand (2000), ICALT has been held in Madison, USA (2001), Kazan, Russia (2002), Athens, Greece (2003), Joensuu, Finland (2004), Kaohsiung, Taiwan (2005), Kerkade, The Netherlands (2006), Niigata, Japan (2007), Santander, Spain (2008), Riga, Latvia (2009), Sousse, Tunisia (2010), Athens, Georgia, USA (2011), Rome, Italy (2012), Beijing, China (2013), Athens, Greece (2014), Hualien, Taiwan (2015) and Austin, Texas, USA (2016).

We invite submission of papers reporting original academic or industrial research in the area of Advanced Learning Technologies and Technology-enhanced Learning. All papers will be double-blindly peer-reviewed.