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.

AIS Conference participants support the adoption and advancement of products that use artificial intelligence and advanced technologies to help people learn. Stakeholders include AIS product and service providers, instructional designers, instructors, trainers, learning and development organizations, teachers and school districts, learning engineers and scientists, researchers, foundations, and government agencies.

Authors 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. 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.

The AIS Conference has been largely supported by members of the AIS Consortium, a business alliance with the mission to promote the development and adoption of effective AIS solutions. If you are an AIS provider, user, researcher, or developer, we encourage you to engage with HCII AIS conference participants to learn more about the AIS Consortium, its mission, and membership opportunities by visiting the AIS Consortium website at: or by contacting Bob Sottilare at

Call for participation leaflet (114KB)

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

  • Michelle Barrett
    Edmentum, Inc., United States
  • Benjamin Bell
    Eduworks Corporation, United States
  • Shelly Blake-Plock
    Yet Analytics, Inc., United States
  • Bruno Emond
    National Research Council Canada, Canada
  • Jim Goodell
    Quality Information Partners, United States
  • Ani Grubišić
    University of Split, Croatia
  • Xiangen Hu
    The University of Memphis, United States
  • Cheryl Johnson
    NAWCTSD, United States
  • John Edison Muñoz Cardona
    University of Waterloo, Canada
  • Maria Mercedes Rodrigo
    Ateneo de Manila University, Philippines
  • Meagan Rothschild
    Age of Learning, United States
  • Alexander Streicher
    Fraunhofer IOSB, Germany
  • KP Thai
    Age of Learning, United States
  • Rachel Van Campenhout
    VitalSource, United States
  • Joost Van Oijen
    Royal Netherlands Aerospace Centre, Netherlands
  • Elizabeth Whitaker
    Georgia Tech Research Institute (Retired), United States
  • Thomas Witte
    Fraunhofer FKIE, Germany