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Lowering the Technical Skill Requirements for Building Intelligent Tutors: A Review of Authoring Tools

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[Technical Report, Book Chapter]

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In this chapter, we focus on intelligent tutoring systems ITSs, an instance of educational technology that is often criticized for not reaching its full potential Nye, 2013. Researchers have debated why, given such strong empirical evidence in their favor Anderson, Corbett, Koedinger and Pelletier, 1995 DMello and Graesser, 2012 Van Lehn et al., 2005 Woolf, 2009, intelligent tutors are not in every classroom, on every device, providing educators with fine-grained assessment information about their students. Although many factors contribute to a lack of adoption Nye, 2014, one widely agreed upon reason behind slow adoption and poor scalability of ITSs is that the engineering demands are simply too great. This is no surprise given that the effectiveness of ITSs is often attributable to the use of rich knowledge representations and cognitively plausible models of domain knowledge Mark and Greer, 1995 Valerie J. Shute and Psotka, 1996 VanLehn, 2006 Woolf, 2009, which are inherently burdensome to build. To put it another way the features that tend to make ITSs effective are also the hardest to build. The heavy reliance on cognitive scientists and artificial intelligence AI software engineers seems to be a bottleneck.


Subject Categories:

  • Humanities and History
  • Cybernetics

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[A, Approved For Public Release]