AGENT-DYSL: A Novel IntelligentReading System for Dyslexic Learners

AGENT-DYSL: A Novel Intelligent Reading System for Dyslexic Learners Andreas Schmidt FZI Research Center for Information Technologies Germany [email_address]

Motivation, problem area
Dyslexia is the most common form of reading disorder
estimations are at ~10%
Reading difficulties often lead to low achievements in education overall
74% of poor readers at 3rd grade are still poor readers at 9th grade
impact on vocabulary development and knowledge construction
negative effect on self-esteem and motivation
Dyslexia, however, does not mean that affected students cannot learn reading well at all
they only need more time and more assistance

Research Objectives
Key objective of the EU FP6 project AGENT-DYSL is an intelligent adaptive reading system
complementing teacher activities
allowing for an accomodative educational setting, i.e., students remain in „ordinary“ classes
Key partners & competencies
AtosOrigin, Spain: administrative coordination and integration
ICCS, Greece: technical coordination, recognition of facial expressions
Dyslexia Action, UK; Danish Education Ministry; FOME, Spain experts on dyslexia
FZI, Germany: ontology-based representation of adaptation knowledge
ULBS, Romania: user profiling
ILSP, Greece: speech recognition
Eurodynamics, Greece

General Approach
Monitor the performance of a dyslexic user and his current emotional and physical state
using speech recognition to detect errors
using image recognition to detect emotional state/attention
Automated construction of a user-profile
Predict possible future errors of the learner based on this profile
Provide personalized assistance to the learner, according to his profile.

Technical Approach
The characteristics of the learner and their current situation in a semantically rich user model
speech processing: detect anomalies in the reading performance like hesitance, but also reading errors.
image processing: capture attention patterns and emotional state
input from teachers who encode their knowledge of the individual learner (e.g., type of errors)
Descriptive encoding of expert pedagogical knowledge for adaptation
Derivation of adaptation actions applied to the user interface like
predictive highlighting of difficult words in various forms
adaptation of the reading speed
presentation of additional help and pronunciation clues

AGENT-DYSL Architecture

AGENT-DYSL Ontology

Key Innovation
a deep knowledge about the user and the current context or situation
context-aware pedagogical knowledge about how to respond to a particular situation
appropriate adaptation possibilities in the reading software user interface
teachers and experts gaining new insights into the effectiveness of certain pedagogical strategies.

Vision: Closed Loop Approach

Conclusion and Outlook
AGENT-DYSL started in September 2006
Requirements Analysis and first adaptation strategies
System architecture and concept finalized
First GUI-Prototype ready
Second prototype next year will be evaluated in Greece and Denmark
More information at http://www.agent-dysl.eu
Andreas Schmidt Department Manager FZI Research Center for Information Technologies, Karlsruhe, GERMANY andreas.schmidt@fzi.de, http://andreas.schmidt.name

AGENT-DYSL: A Novel IntelligentReading System for Dyslexic Learners

by Andreas Schmidt on Oct 24, 2007

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