CBIE-2016 - Keynotes
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Kinshuk

Biography

Dr. Kinshuk is the Dean of the College of Information at the University of North Texas. Prior to that, he held the NSERC/CNRL/Xerox/McGraw Hill Research Chair for Adaptivity and Personalization in Informatics, funded by the Federal government of Canada, Provincial government of Alberta, and by national and international industries. He was also Full Professor in the School of Computing and Information Systems and Associate Dean of Faculty of Science and Technology, at Athabasca University, Canada. He earned his PhD from De Montfort University, United Kingdom. His work has been dedicated to advancing research on the innovative paradigms, architectures and implementations of online and distance learning systems for individualized and adaptive learning in increasingly global environments. His research interests include adaptive and personalized learning; learning analytics; learning technologies; mobile, ubiquitous and location aware learning systems; cognitive profiling; and, interactive technologies. Dr Kinshuk is founding chair of IEEE Technical Committee on Learning Technologies, and founding editor of the Journal of Educational Technology & Society (SSCI indexed, within top 5 in Google Scholar metrics ranking for Educational Technology) and Springer's Smart Learning Environments journal.

CV: http://kinshuk.athabascau.ca

Talk 1

Title: Improving learning through smart learning analytics - downDownload

Abstract

Student learning is complex. All phases of student experiences produce data - in the classrooms, in the labs, on the net, within social networks, when with friends and when interacting with loved ones. With access to these big, continuous, and disparate data-sets, learning experiences can be characterized based on quality of the content, personalized assessments, learners’ comprehension, topic associations made by learners, learners’ feelings/emotive states, learners' insights, learners' assumptions in discussions, effectiveness of peer networks, instructional capacity, learner challenges, learners’ confidence, learners' recognition of new skills, and learners' refinement of gained competencies. Such characterizations not only enable the capture of information on where, why, how, and when learning happens, but also empower refinement of instructional measures employed by the institution in a continuous manner. This talk will focus on making learning smart by using analytics approaches to discover, analyze and make sense of these characteristics and adapt instruction accordingly.

Talk 2

Title: Learner Engagement/Retention Through Technology - - downDownload

Abstract

Online learning has emerged as a mainstream phenomenon in education sector and every academic institution has embraced it in some form and shape. While online learning approaches have opened up new pathways for learning, success of students requires consideration of various nuances that make it different from traditional face to face interactions. Three specific aspects are predominant in online learning that hinder the success of learning: feeling of isolation, both in spatial and temporal sense, since students are separated both in time and location at the moment they have possibility for learning; availability of learning opportunities when and where desired, using devices on hand; and, relevance of learning experience, taking into account of individual student's characteristics, preferences, capabilities, and context. This talk will explore those differences and will discuss solutions for effective learning using various best practice examples. In particular, learner empowerment in the learning process will be explored in the context of constructivist learning that has been proven to be effective in typical online learning scenarios. While the role of teacher is paramount in the learning process, online learning provides some excellent opportunities as well as challenges for teachers to encourage development of 21st century skills, leading not only to the transformation of students into better citizens in long term, but also improvement in learner engagement and retention in short term.


Rosa Maria Vicari

Biography

Holds a PhD in Electrical and Computer Engineering from the University of Coimbra (1990). Coordinates a UNESCO Chair in ICT and is a professor of the Institute of Informatics at the Federal University of Rio Grande do Sul. She has experience in Computer Science, acting on the following topics: Intelligent tutoring, multi-agent systems, intelligent tutoring systems, information technology in education.

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Peter Brusilovsky

Biography

Peter Brusilovsky received his BS (1983) and PhD (1987) degrees from Moscow “Lomonosov” State University. He received postdoctoral training at University of Sussex, University of Trier, and Carnegie Mellon University. He also holds a Doctor Honoris Causa degree from the Slovak University of Technology in Bratislava (2009). Currently, he is a Professor of Information Science and Intelligent Systems at the University of Pittsburgh, where he directs Personalized Adaptive Web Systems (PAWS) lab. Peter Brusilovsky has been working in the field of adaptive educational systems, user modeling, and intelligent user interfaces for more than 20 years. He published numerous papers and edited several books on adaptive hypermedia, adaptive educational systems, user modeling, and the adaptive Web. Peter is the Editor-in-Chief of IEEE Transactions on Learning Technologies and a board member of several journals including User Modeling and User Adapted Interaction, ACM Transactions on the Web, and Web Intelligence and Agent Systems. He is a Senior Member of IEEE.

Talk 1

Title: Addictive Links: Engaging Students through Adaptive Navigation Support and Open Social Student Modeling - downDownload

Abstract:

Empirical studies of adaptive navigation support in the educational context have demonstrated that it can help students to acquire knowledge faster, improve learning outcomes, reduce navigational overhead, and encourage non-sequential navigation. Over the last 10 years we have explored a lesser known effect of adaptive navigation support - its ability to significantly increase student motivation to work with non-mandatory educational content. In the presence of adaptive link annotation students tend to access several times more learning content; they stay with it longer, return to it more often and explore wider variety of learning resources. This talk will present an overview of our exploration of the "addictive links" effect in many course-long studies, which we run in several domains (C, SQL and Java programming), for several types of learning content (quizzes, problems, interactive examples). The first part of the talk will review our exploration of a more traditional knowledge-based personalization approaches and the second part will focus on more recent studies of social navigation support that we also call as Open Social Student Modeling.

 


Sergio Crespo

Biography

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