Special Issue on the Generalized Intelligent Framework for Tutoring (GIFT): Creating a Stable and Flexible Platform for Innovations in AIED Research

Publication Information


  • Robert A. Sottilare,
  • Ryan S.J.D Baker, Columbia University
  • Arthur C. Graesser, University of Memphis
  • James Lester, North Carolina State University


  • 139-151


  • Adaptive instruction, Affect, Afect sensitivity, Authoring, Generalized intelligent framework for tutoring (GIFT), Instructional management, Psychomotor tasks, Teams, Taskwork, Teamwork, Testbed


  • The Generalized Intelligent Framework for Tutoring (GIFT) is a research prototype with three general goals associated with its functions and components: 1) lower the skills and time required to author Intelligent Tutoring Systems (ITSs) in a variety of task domains; 2) provide effective adaptive instruction tailored to the needs of each individual learner or team of learners; and 3) provide tools and methods to evaluate the effectiveness of ITSs and support research to continuously improve instructional best practices. This special issue focuses primarily on the third goal, GIFT as a research testbed. A discussion thread covers each article within this special issue and discusses its actual and potential impact on GIFT as a research tool for AIED. Our primary motivation was to introduce the AIED community to GIFT not just as a research tool, but as an extension of familiar challenges taken on previously by AIED scientists and practitioners. This preface provides a high level overview of the GIFT functions (authoring, instructional delivery and management, and experimentation) and presents its primary design principles. To learn more about GIFT, freely access the software, documentation, and associated technical papers visit www.GIFTtutoring.org.