[On behalf of myself & Ben Nye, special track co-chairs for Intelligent
Learning Technologies @ FLAIRS-30, please consider submitting your work and
distribute this call widely! -Stephen Fancsali]
CfP: Intelligent Learning Technologies Special Track at FLAIRS-30
Special Track URL: https://sites.google.com/site/flairsilt/
FLAIRS-30 URL: http://flairs-30.info
The Special Track on Intelligent Learning Technologies (ILTs) will be held
as part of the 30th International Conference of the Florida Artificial
Intelligence Research Society (FLAIRS-30), which will take place from 22-24
May, 2017 at The Hilton Marco Island Beach Resort and Spa in Marco Island,
Florida, USA. The special track aims to provide a forum for ILT researchers
to share their current projects and recent studies that identify,
investigate, and (begin to) resolve issues that relate to ILTs. A special
track consists of a group of papers in a sub-discipline of artificial
intelligence. Special tracks are an integral part of each FLAIRS
conference: their papers are required to meet the same standards and are
published in the conference proceedings, and the tracks run in parallel
with the general conference. Special tracks provide researchers in focused
areas the opportunity to meet and present their work, and they offer a
forum for interaction among the broader community of artificial
intelligence researchers.
What are Intelligent Learning Technologies?
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Intelligent learning technologies include a diverse array of computer-based
systems and tools designed to foster meaningful student learning. These
technologies are intelligent to the extent they implement artificial
intelligence principles and techniques to create teachable structure from
content, analyze and model inputs from the learner, and generate
personalized and adaptive feedback and guidance. Intelligent tutoring
systems (ITSs) represent a classic example. ITSs, broadly defined, possess
an “outer loop” that intelligently selects the next relevant task, or
content object, for learners to complete based on prior performance, and an
“inner loop” that provides iterative and intelligent feedback as learners
work toward completing their tasks. However, intelligent learning
technologies encompass more than just intelligent tutors. Increasingly,
educational games, automated writing evaluation, virtual pedagogical
agents, simulations, virtual worlds, open-ended problem solving, generative
concept maps, AI-assisted authoring systems, learning content aggregation
programs, and e-textbooks rely on some form of artificial intelligence to
enrich the learning experience.
The ILT research community is multidisciplinary; it draws upon artificial
intelligence, computer science, educational psychology, the learning
sciences, human systems, linguistics, and more. The Intelligent Tutoring
Systems, Educational Data Mining, Learning Analytics, Computer-Supported
Collaborative Learning, and Affective Computing communities are all of high
relevance.
What is the GOAL of the track?
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The purpose of this track is to bring together an international group of
scientists to present innovative empirical research, technical innovations,
and well-grounded theory related to artificial intelligence in learning
technologies. This track will inform attendees about recent developments in
the design, implementation, and evaluation of such systems.
This track is a continuation of the 2015 and 2016 FLAIRS ILT tracks, which
naturally emerged from the longstanding Intelligent Tutoring Systems
special track. The aim of the Intelligent Learning Technologies track is to
be more representative and inclusive of the diverse work being conducted
with intelligent systems that support student learning.
Topics of Interest
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The Intelligent Learning Technologies special track welcomes original,
well-written reports on empirical evaluations of learning technologies,
innovative designs and implementations, and theoretical principles that
advance the field. The preference for all submissions is to include both
substantive references to the existing literature and empirical data. We
seek submissions that address a variety of intelligent learning technology
issues including, but not limited to:
- Adaptive scaffolding in open-ended learning environments
- Assistive technologies for learners with special needs
- Automated writing evaluation
- Educational data mining and learning analytics
- Interaction-based learner modeling from novice or expert populations
- Effective design principles for intelligent learning technologies
- Game-based, narrative-based, and immersive learning environments
- Intelligent tutoring systems
- Natural language processing to support intelligent interaction and
feedback
- Novel designs, interfaces, and scaffolds
- Overcoming challenges within the field (e.g., gaming the system,
ill-defined domains)
- Teachable agents, learning companions, and other pedagogical agents
- Tests of existing intelligent learning technologies
- Efficient sampling methods for experiments in learning environments.
- Analysis and analytics of Massive Open Online Courses (MOOC)
Important Dates
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Paper Submission Deadline: 21 November, 2016
Acceptance Notification: 23 January, 2017
Camera-Ready Papers Due: 27 February, 2017
FLAIRS-29 Conference: 22-24 May, 2017
