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. Users interact with AIS technologies that guide instructional experiences by tailoring feedback and recommendations based on real-time models of individual learners or teams in the context of domain learning objectives. The focus of this conference on instructional tailoring 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.

The conference examines modeling, interaction design and standards to facilitate research and development of effective and efficient learning using AISs. Participants in the AIS conference explore 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.

Another goal is 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.

Call for participation leaflet (106KB)

Indicative topics/keywords of the broad spectrum of issues to be addressed:

  • 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 Learning Technologies Standards Committee, United States
  • Michelle Barrett
    ACT, United States
  • Benjamin Bell
    Eduworks Corporation, United States
  • Gautam Biswas
    Vanderbilt University, United States
  • Shelly Blake-Plock
    Yet Analytics, Inc., United States
  • Michael Boyce
    United States Military Academy, United States
  • Keith Brawner
    Army Futures Command, United States
  • Bert Bredeweg
    Amsterdam University of Applied Sciences (AUAS), Netherlands
  • Barbara Buck
    Boeing, United States
  • Jody Cockroft
    The University of Memphis, United States
  • Brandt Dargue
    The Boeing Company, United States
  • Jeanine DeFalco
    US Army Futures Command, United States
  • Lucio DePaolis
    Università del Salento, Italy
  • Eric Domeshek
    Stottler-Henke, Inc., United States
  • Dragan Gasevic
    Monash University, Australia
  • Benjamin Goldberg
    CCDC-SC, STTC, United States
  • Art Graesser
    The University of Memphis, United States
  • Ani Grubisic
    University of Split, Faculty of Science, Croatia
  • Andrew Hampton
    University of Memphis, United States
  • Ioannis Hatzilygeroudis
    University of Patras, Greece
  • Ross Hoehn
    Soar Technology, United States
  • Xiangen Hu
    University of Memphis, United States
  • Jerzy Jarmasz
    Defence Research and Development Canada, Canada
  • Anne Knowles
    L3Harris Technologies, United States
  • Qiguang Lin
    Guangzhou Zhiban AI Technology, Co. Ltd., P.R. China
  • Robby Robson
    Eduworks, Inc. & IEEE Board of Governors, United States
  • Peder Sj√∂lund
    Skydome, Sweden
  • KP Thai
    Squirrel AI Learning, United States
  • Richard Tong
    Yixue Education Inc., United States
  • Armon Toubman
    NLR, Netherlands
  • Thomas E.F. Witte
    Fraunhofer FKIE, Germany