The goal of the Adaptive Instructional Systems (AIS) Conference, affiliated to the HCI International conference, is to understand the theory and enhance the state-of-practice for a set of technologies (tools and methods) called adaptive instructional systems. AISs are defined as artificially-intelligent, computer-based systems that guide learning experiences by tailoring instruction and recommendations based on the goals, needs, preferences, and interests of each individual learner or team in the context of domain learning objectives. The interaction between individual learners or teams of learners with AIS technologies is a central theme of this conference. AISs observe user behaviors to assess progress toward learning objectives and then act on learners and their learning environments (e.g., problem sets or scenario-based simulations) with the goal of optimizing learning, performance, retention and transfer of learning to work environments.

The focus of this conference on instructional tailoring of learning experiences highlights the importance of accurately modeling learners to accelerate their learning, boost the effectiveness of AIS-based experiences, and to precisely reflect their long term competence in a variety of domains of instruction. Conference participants examine modeling, interaction design and standards to facilitate research and development of effective and efficient learning using AISs. Authors in the AIS conference share their expertise in machine-based instruction including aspects of adaptation, augmentation, and interaction design. They share their visions and findings about AIS technologies (e.g. intelligent tutoring systems, intelligent mentors, and personal assistants for learning) and propose standards to improve the portability, extensibility, and interoperability of AIS technologies with each other and other instructional technologies. Finally, AIS Conference participants seek to identify standards for authoring, delivery, interaction design, real-time management, and evaluation of AIS technologies supporting domain classifications: cognitive, affective, psychomotor, and group instruction.

If you are an AIS user, researcher or developer of AIS products and services, you may also wish to have a look at:
IEEE Adaptive Instructional System (AIS) Technical Advisory Group (TAG)

Call for participation leaflet (104KB)

The related topics include, but are not limited to:

  • Instructional Theories Applied to Adaptive Instruction
  • Methods of Adaptation for Individual Learners and Teams
  • Assessment of Learner and Team States for Adaptive Instructional Decisions
  • Role of Artificial Intelligence in Adaptive Instruction
  • Authoring Adaptive Instructional Systems for Cognitive, Affective, Psychomotor, and Group Tasks
  • Interaction Design for Adaptive Instructional Systems
  • Conceptual Models and Interoperability Standards for Adaptive Instructional Systems
  • Augmentation Technologies (Tools and Methods) for Adaptive Instruction
  • Evaluating the Effectiveness of Adaptive Instructional Systems
  • Program Chair

    Robert Sottilare

    Soar Technology, Inc., USA

  • Program Chair

    Jessica Schwarz

    Fraunhofer FKIE, Germany

  • Board Members

  • Roger Azevedo
    University of Central Florida, United States
  • Brenda Bannan
    George Mason University, United States
  • Avron Barr
    IEEE Educational Activities Board, United States
  • Michelle Barrett
    Edmentum, United States
  • Benjamin Bell
    Eduworks Corporation, United States
  • Shelly Blake-Plock
    Yet Analytics, United States
  • Barbara Buck
    Boeing, United States
  • Jody Cockroft
    The University of Memphis, United States
  • Jeanine Defalco
    US Army Futures Command, United States
  • Jim Goodell
    Quality Information Partners, United States
  • Ani Grubisic
    University of Split, Croatia
  • Andrew Hampton
    University of Memphis, United States
  • Xiangen Hu
    The University of Memphis, United States
  • Benny Johnson
    VitalSource Technologies, United States
  • Cheryl Johnson
    Naval Air Warfare Center Training Systems Division, United States
  • MA. Mercedes T. Rodrigo
    Ateneo de Manila University, Philippines
  • Vasile Rus
    The University of Memphis, United States
  • Jordan Richard Schoenherr
    Carleton University, Canada
  • KP Thai
    Age of Learning, Inc., United States
  • Richard Tong
    Squirrel AI & IEEE LTSC, United States
  • Rachel Van Campenhout
    Acrobatiq, United States
  • Joost Van Oijen
    NLR, Netherlands
  • Elizabeth Veinott
    Michigan Technological University, United States
  • Elizabeth Whitaker
    Georgia Tech Research Institute, United States
  • Thomas E.F. Witte
    Fraunhofer FKIE, Germany