Quiz
1.
What is the purpose of the SLALOM model?
(a) Generate errors
(b) Provide user feedback
(c) Captures user proficiency in grammatical structures
(d) The actual grammar parser
2.
Name three levels of knowledge in the user model?
(a) Acquired, ZPD, Unacquired
(b) Previous, Current, Future
(c) Irregular, Standard, Knowledgeable
(d) Beginner, Proficient, Expert
Quiz
3.
Name the two modules in the ICICLE System.
(a) Tutoring Session Module and User Interface Module
(b) Error Identification Module and Response Generation
Module
(c) User Module and System Module
(d) Gradual Learning Module and Frequency of Practicing
Module
4.
What is the purpose of the ICICLE system?
(a) Improving English literacy and ASL skills for all
students
(b) Improving English literacy skills for hearing students
(c) Improving ASL skills for deaf students
(d) Improving English literacy skills in deaf students
An Intelligent Tutoring
System for Deaf Learners of
Written English
Lisa N. Michaud, Kathleen F. McCoy,
Christopher A. Pennington
Presented by Allan Spale – EECS 578
Introduction
• Improve English literacy skills of deaf
students who primarily use ASL
– ASL (American Sign Language)…a foreign
language
– Deaf literacy in English impacts a student
in every facet of education
– Teach students English using a strategy
called “English as a Second Language”
Signing and Education
• Lipreading: a method for pre-lingually
deaf children to acquire English
– Usually not successful, only 40% of
English phonemes are visible
• Deaf children must learn English in
school while learning to read and write
– “…average deaf high school graduate has
only a fourth grade reading ability.”
Methods of Communication
with Deaf Students in School
• Spoken English
– Requires students to use “lipreading” for
acquiring language communication
– Not effective, most students do not have
access to usable linguistic input
Methods of Communication
with Deaf Students in School
• Manually Coded English (MCE)
– Codes used to visualize the structure of
words and sentences of English
– A morpheme in English has a sign
– Signed languages are still more efficient
than MCE in communicating
– People who speak and sign simultaneously
omit many morphemes in their signing
Deaf Students:
Bi-Lingual and Bi-Cultural
• English is taught as a second language
– “[C]hildren in bilingual programs have
better comprehension of spoken English
than do those in immersion [programs].”
• System philosophy
– Include similarities and differences with
English and ASL
– Eventually provide instructional feedback in
ASL to supplement English explanations
ICICLE System Overview
• ICICLE is an acronym for Interactive
Computer Identification and Correction
of Language Errors
• Two modules
– Error identification
– Response generation
ICICLE System Overview
• Tutorial Instruction
– User submits written material
– System responds with list of errors
• Only reports relevant errors that can be tutored
– System guides the user through a review
for improving aspects of the user’s writing
– User can make changes and request
another analysis
ICICLE System
Design Goals
• Computer systems are suitable for learning
using post-performance review
– Doing intensive tasks restricts learning during their
execution
• “[S]atisfy the deaf learner’s need for
understandable English input”
– Most written material read by deaf students comes
from academic texts
– Use English grammatical structures that the user
is trying to utilize in writing
ICICLE System
Design Goals
• Provide feedback without a human
teacher
– Students do not have to “feel bad” being
corrected by a teacher
– Might encourage students to write more
ICICLE System Diagram
Current Implementation
• Error Recognition is the focus
• Follows a “user input, system response
model”
– System acquires user text
– User requests analysis
– System highlights errors in sentences
– User click on a highlighted sentence
returns static error explanation
– User can resubmit text for another analysis
Grammar Coverage
• Grammar used is English-based with
error productions
– Error productions allow errors to be flagged
– Uses COMLEX Syntax 2.2 lexicon
– Handles many parts of speech and their
alternate forms
– Has grammar recognition limitations
– New grammar system from C. P. Rose
relaxes some grammar requirements
(reducing error rules)
User Interface
• Designed using Tcl/Tk
• Layout structure
– Text entry area
– Analysis controls
– Highlighting of errors
– “Fix-it” window
User Interface Example
Toward Modeling the User
• Necessary to model user’s knowledge
– User history of system use
– User knowledge of English grammar
• Solves some problems
– Choosing appropriate grammar parses
– Provide relevant feedback to the user
Three Levels of Knowledge
• Acquired
– User can correctly use these English
grammar structures and rules
• Zone of Proximal Development (ZPD)
– User is in the process of acquiring these
English grammar structures and rules
• Unacquired
– User cannot correctly use these English
grammar structures and rules
SLALOM Model
• SLALOM is an acronym for “Steps of
Language Acquisition in a Layered
Organization Model”
• Used to separate English into “a set of
feature hierarchies”
– Each hierarchy contains an ordered list of
items in their acquisition order
– Acquisition sequence is used based on
previous language studies
The SLALOM Model
• First use involves evaluation of writing
– SLALOM tags in the feature hierarchies will
be labeled as acquired, ZPD, and
unacquired
• Subsequent uses will update the tags
– Typically, one would expect ZPD items to
become acquired over time
SLALOM Diagram
Problems Using
the SLALOM Model
and Their Solutions
• Initial evaluation does not use SLALOM
tags
– Separate evaluation pass with evaluation
not directly related to SLALOM
• Concern with difficulties for establishing
and maintaining the user model
– Large number of user writings
– SLALOM captures syntactic content from
user writings
Problems Using
the SLALOM Model
and Their Solutions
• Inaccurate feedback from user errors
– Include statistical confidence measures
into system
• My solution
– Implement a neural network system into
parsing methods and writing analysis
Reasoning on
Partial Evidence
• ICICLE will not have complete
information from SLALOM when
evaluating user competency
• General learner profile will supplement
the specific learner
• “Unique” situations will rely on a general
profile, while system decisions rely on
specific learner
Developing the User Model
• SLALOM feature relationships will be
established based on
– Research from second language
acquisition
– Human evaluations of writing samples from
a studied learner population
Generating a Response
• Error Identification system component
analyzes text and produces error list
• Text and error list sent to the Response
Generator
• Response Generator system
component supplies tutorial feedback
Anatomy of a Response
• Content
– Factual knowledge of the response to help
the student to improve some part of his/her
writing style
– Influenced by
•
•
•
•
Error annotations
Error source
“[I]nformation about the languages involved“
“[I]nformation from the acquisition model”
Anatomy of a Response
• Method
– Manner of content organization and
creation for the user
– Depends on…
* The kind of information available in the
language model
* Kind of information available about various
English constructs involved in the error
* Receptivity of the student to various kinds of
information in the correction
* Indicates material directly quoted from the paper
Anatomy of a Response
• Form
– Utilizing appropriate background
knowledge
– “[Structures] information to ensure that the
appropriate rhetorical resources are used
in realizing the chosen method”
• History
– “[M]aking the response contextually aware
by [referring to] earlier tutorial information
and [current user knowledge]”
Anatomy of a Response
• Manner
– “[S]tyle of the actual language employed in
realization of the response as actual
English text”
– Depends on…
• Language acquisition level of the user
• Current language constructs the user is
attempting to acquire
Multimodal Response
• Present some tutorial information in a
format closer the user’s “native
language”
– Improve the user’s knowledge acquisition
– Reduce user’s stress level in using the
system
• Provision of a “signing agent”
Issues with a Signing Agent
• Signing agent compensates for a
missing perception channel
• Times for using the signing agent
• Should not be added to the system
without studying how to integrate it
appropriately into the system
Conclusion
• Problem of literacy of deaf students
– Provide a computerized tutorial tool
for learning English grammar
• Gives feedback on user’s grammatical
errors relevant to the user’s knowledge
domain
• Tracks the students acquisition of
grammatical rules and constructs
Conclusion
• The future language tutorial system
components
– “[U]nique user language model”
– “[F]lexible and robust tutorial planning”
– “[M]ultimodal capabilities via the inclusion
of an animated signing agent”
Questions and Comments