Authoring Tools for Designing Intelligent Tutoring Systems: a Systematic Review of the Literature

Publication Information


  • Diego Dermeval, Federal University of Alagoas
  • Ranilson Paiva, Federal University of Alagoas
  • Julita Vassileva, University of Saskatchewan
  • Ig Ibert Bittencourt, Federal University of Alagoas
  • Daniel Borges, Federal University of Alagoas


  • 336-384


  • Intelligent tutoring systems, Authoring tools, Systematic literature review, Intelligent tutoring systems design


  • Authoring tools have been broadly used to design Intelligent Tutoring Systems (ITS). However, ITS community still lacks a current understanding of how authoring tools are used by non-programmer authors to design ITS. Hence, the objective of this work is to review how authoring tools have been supporting ITS design for non-programmer authors. In order to meet our goal, we conduct a Systematic Literature Review (SLR) to identify the primary studies on the use of ITS authoring tools, following a pre-defined review protocol. Among the 4622 papers retrieved from seven digital libraries published from 2009 to June 2016, 33 papers are finally included after applying our exclusion and inclusion criteria. We then identify the main ITS components authored, the ITS types designed, the features used to facilitate the authoring process, the technologies used to develop authoring tools and the time at which authoring occurs. We also look for evidence of the benefits of ITS authoring tools. In summary, the main findings of this work are: (1) there is empirical evidence of the benefits (i.e., mainly in terms of effectiveness, efficiency, quality of authored artifacts, and usability) of using ITS authoring tools for non-programmer authors, specially to aid authoring of learning content and to support authoring of model-tracing/cognitive and example-tracing tutors; 2) domain and pedagogical models have been much more targeted by authoring tools; (3) several ITS types have been authored, with an emphasis on model-tracing/cognitive and example-tracing tutors; (4) besides providing features for authoring all four ITS components, current authoring tools are also presenting general features (e.g., view learners’ statistics and reuse tutor design) to create broader authoring tools; (5) a great diversity of technologies, which include AI techniques, software solutions and distributed technologies, are used to develop ITS authoring tools; and (6) authoring tools have been mainly targeting ITS design before students’ instruction, but works are also addressing authoring during and/or post-instruction relying both on human and artificial intelligence. We conclude this work by showing several promising research opportunities that are quite important and interesting but underexplored in current research and practice.