GIFT

GIFTSym6 is the sixth annual Generalized Intelligent Framework for Tutoring (GIFT) Users Symposium. GIFT is an open source, empirically-based, service-oriented framework of tools, methods and standards to make it easier to author computer-based tutoring systems (CBTS), deliver and manage instruction, and assess the effect of adaptive instruction, CBTS, components and methodologies. GIFT is being developed under the Adaptive Tutoring Research Science & Technology project at the Learning in Intelligent Tutoring Environments (LITE) Laboratory, part of the U.S. Army Research Laboratory - Human Research and Engineering Directorate (ARL-HRED).

GIFTSym6 invites GIFT designers, developers and practitioners to submit technical papers about their ideas, experiences, and lessons-learned in using GIFT to author and evaluate Intelligent Tutoring Systems to deliver and manage adaptive instruction. This year, we have added a track to share ideas for standardization across adaptive instructional systems (AISs).

Submission Guidelines
All papers must be original and not simultaneously submitted to another journal or conference. The following paper categories are welcome:

Full papers (5-10 pages using template) describing design, application, and/or science-based potential enhancements to GIFT. This will form the basis for four half-day sessions at GIFTSym.
Short papers (3-4 pages using template) describing standards opportunities for adaptive instructional systems (AISs). This will form the basis for one half-day session at GIFTSym.
Submission Schedule

Abstracts are required to be extended abstracts (minimum 800 words) covering the focus of your paper, results/conclusions and recommendations.

Abstract Submission Deadline - 15 March 2018
Acceptance Notification - 22 March 2018
Paper Submission Deadline - 19 April 2018
Presentation Submission Deadline - 3 May 2018
GIFTSym6 - 8-11 May 2018, Orlando, Florida

List of Topics
AI and Machine Learning for ITSs
Assessment Methods
Authoring Tools
Domain Modeling
Individual Learner Modeling
Instructional Management
ITS Architecture and Ontology
Team Modeling
Standards for Adaptive Instructional Systems (AISs)