(CALL FOR PAPERS) 7th Annual GIFT Users Symposium - GIFTSym7
CALL FOR PAPERS (https://easychair.org/cfp/GIFTSym7)
GIFTSym7 is the seventh 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 US Army Natick Soldier Research, Development & Engineering Center’s Simulation and Training Technology Center (NSRDEC STTC).
GIFTSym7 invites GIFT designers, developers and practitioners to submit technical papers about their ideas, experiences, and lessons-learned in using GIFT to author and evaluate Adaptive Instructional Systems (AIS). In an effort to sustain the growth of the community, we will continue with last year’s addition and have a track to share ideas for standardization across AISs.
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 AISs. This will form the basis for a separate session on the applicability of standards for AIS development.
Abstracts are required to be extended abstracts (minimum 800 words) covering the focus of your paper, results/conclusions and recommendations.
- Abstract Submission Deadline - 08 March 2019
- Acceptance Notification - 20 March 2019
- Paper Submission Deadline - 30 April 2019
- Presentation Submission Deadline - 09 May 2019
- GIFTSym7 - 16-17 May 2019, Orlando, Florida
- AI and Machine Learning for ITSs
- Collective and Team-Based Methods
- Measurement and Assessment
- Authoring Tools
- Domain Modeling
- Individual Learner Modeling
- Instructional Management
- ITS Architecture and Ontology
- After Action Review (AAR)
- Competency Modeling
- Standards for Adaptive Instructional Systems (AISs)
LINK TO SUBMISSION SITE:
All questions about submissions should be emailed to Dr. Benjamin Goldberg at email@example.com