Affordable Cognitive Modeling Authoring Tools using HCI Methods: Carnegie Mellon University Portion

Abstract

We were able to show that our tools can be used to build many different rule-based cognitive models, such as a Warrior Simulator at Fort Benning (Livak & Heffernan, 2004), a Logic Tutor for internal use at CMU, and a Genetics tutor. In preliminary controlled experiments involving basic Cognitive Tutor development tasks, we found efficiency gains due to CTAT of 1.4 to 2 times faster (Aleven, McLaren, Sewall & Koedinger, 2006). We also demonstrated across 4 different behavioral modeling projects that our tools created example-tracing tutors that drastically reduced modeling costs (Koedinger, Al even, Heffernan, McLaren, & Hockenberry, 2004, Heffernan, Turner, Lourenco, Macasek, Nuzzo-Jones, Koedinger, 2006). Not only did we reduce the time dramatically (averaging a reduction of over a factor 5), we also reduced the experience level modelers needed. Finally, we pushed the state of the art in data mining and machine learning support to help rule-writers (McLaren et al 2005; Harrer et al, 2005; McLaren et al, 2004b; McLaren et al, 2004a; Jarvis, Nuzzo-Jones, & Heffernan, 2004; Matsuda, Cohen, and Koedinger, 2005a; 2005b; 2005c).

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Document Details

Document Type
Technical Report
Publication Date
Nov 30, 2005
Accession Number
ADA447039

Entities

People

  • Kenneth R. Koedinger
  • Neil T. Heffernan
  • Vincent Aleven

Organizations

  • Carnegie Mellon University

Tags

Communities of Interest

  • Autonomy

DTIC Thesaurus Topics

  • Abstracts
  • Cognitive Systems Engineering
  • Data Mining
  • Department Of Defense
  • Education
  • Efficiency
  • Human-Computer Interaction
  • Information Operations
  • Learning
  • Machine Learning
  • Military Research
  • Psychology
  • Simulations
  • Simulators
  • Students
  • Universities

Fields of Study

  • Computer science

Readers

  • Artificial Intelligence
  • Computational Fluid Dynamics (CFD)
  • Information Retrieval

Technology Areas

  • AI & ML
  • AI & ML - Machine Learning Algorithms
  • Biotechnology