Title: Cognitive Measures for Visual Concept Teaching with
       Intelligent Tutoring Systems

Authors names: Andrey R. Pimentel and Alexandre I. Direne

Affiliation: Depto. de Informatica - UFPR - Centro Politecnico
             CEP: 81531-990 - Curitiba - PR - BRASIL
             andrey@pos.inf.ufpr.br, alexd@inf.ufpr.br


This  work  presents  a  set  of  cognitive  measures  for  describing
radiological image databases. The measures allow an adequate choice of
the next image to be presented to the learner when interacting with an
ITS (Intelligent  Tutoring System)  shell  that teaches  about  visual
concepts.

The goal is to minimise the learning time of radiological concepts and
to  permit  the  implementation  of  a  wider  variety  of  long-term,
pedagogic strategies.

The literature on concept teaching shows very few attempts to  produce
computer-based material,  particularly  on  visual  concept  tutoring.
Authoring environments  have  also been  rare,  showing that  ITS  for
visual concepts are usually not easy to be re-programmed or expanded.

We formalise general-purpose  measures for dealing  with ordering  and
complexity of image sequences based on  the idea of cognitive load  of
images and teaching sessions.

This load derives  from the differences  of capacities between  novice
and expert radiologists, which we summarise from the literature in 
three major dimensions: (1) visual  recognition, (2) diagnostic and 
(3) verbal  expressivity.

A case  study  to exemplify  the  teaching of  brain  tumor  diagnosis
through CT-scans has been carried out with the local University
Hospital.

An implemented  software  tool,  called SEQUENCE,  supports  part  the
authoring process for eliciting the cognitive measures and for setting
ordering parameters.

We are currently using  the cognitive measures in  ITS for a range  of
visual  domains,  as  well  as  discussing  their  applicability  in a
significantly different class of domain, such as computer programming.