1. An ICALL writing support system tunable to varying levels
of learner initiative
Karin Harbusch1 & Gerard Kempen2,3
University of Koblenz-Landau, Koblenz, DE
Max Planck Institute for Psycholinguistics, Nijmegen, NL
Department of Psychology, Leiden University, NL

2. Overview
Motivation: Learning to write in L2 through a dialogue with a sentence generator
COMPASSII prototype at work (based on the Performance Grammar (PG) formalism)
Student-initiated feedback production in our L2-writing system COMPASSII
Conclusions and future work

3. Motivation (I): Why ICALL?
Observation:
Langugage lerners like to create and test their own sentences instead of being restricted to work with prepared text materials.
ICALL solution:
Apply Natural Language Processing (NLP) techniques.
Parsing
Generation

4. Parsing-based ICALL-system
Motivation (II):
Parsing-based ICALL-system
After the student has typed a sentence, the parser evaluates it and provides feedback on the grammatical quality.
Origin of parsing problems:
Student and parser perform rather different tasks although they use the very same grammar rules. However, interpreting and applying the rules for production purposes is not the same thing as doing this for comprehension purposes.
Problems with producing fine-tuned feedback:
Ambiguities in the analysis process make it difficult to select appropriate feedback.
The more errors a sentence contains, the less accurate the feedback, due to the many correction options in the parser.

5. Generation-based L2 learning
Motivation (III):
Generation-based L2 learning
In producing a written sentence, writer and generation system perform the same job, based on the same grammar rules.
So, let them do the job together. Let them inform and help each other while building a grammatically correct sentence that expresses the student’s communicative intention.

6. Dialogue with the generator
Motivation (IV):
Dialogue with the generator
Students construct sentences in a dialogue via a graphical drag&drop user interface of a natural language generation system, which intervenes immediately when they try to build an ill-formed structure. Every construction step is commented with informative feedback that the student might study in more depth.
Learner-initiated grammar study based
on fine-tuned informative feedback

7. System at work Learner-initiative (L2 = German, L1 = English)
The student drags words into a workspace where their grammatical properties are displayed in the form of syntactic treelets as defined in our grammar formalism
(Lexicalized Performance Grammar).
Why Performance Grammar?
During the construction process, Performance Grammar affords the flexibility to concentrate on
any part of the linguistic structure,
in any order.
Learner-initiative

8. Lexicon window List of inflected word forms
The student drags words into a workspace where their grammatical properties are displayed in the form of syntactic treelets as defined in our grammar formalism
(Lexicalized Performance Grammar).
List of inflected word forms
the students can select from

9. Workspace window Student manipulates lexical treelets in the workspace
The student drags words into a workspace where their grammatical properties are displayed in the form of syntactic treelets as defined in our grammar formalism
(Lexicalized Performance Grammar).

10. currently showing treelet information belonging to
Feedback window
The student drags words into a workspace where their grammatical properties are displayed in the form of syntactic treelets as defined in our grammar formalism
(Lexicalized Performance Grammar).
Communication window
currently showing treelet information belonging to
selected node in the
workspace

11. Tree building in the workspace
In the workspace, the student can combine treelets by moving the root of one treelet to a foot of another treelet. In the generator, this triggers a unification process that evaluates the quality of the intended structure.
If the latter is licensed by the generator’s syntax, the tree grows and a larger phrase-structure tree is
displayed.
In case of licensing failure, the generator informs the student about the reason(s). This feedback follows directly from the unification requirements.

12. Tree composition via drag&drop

13. during the writing dialogue
Feedback generation
during the writing dialogue
Each student action triggers detailed informative feedback (positive/negative).
All feedback texts are attached to a PG treelet or to a word order rule, which can be inspected in more detail if desired.
MAL-RULES extend the grammar to model frequently observed errors.

14. Conclusions
COMPASSII system is a new sentence generation application.We deploy the paraphrase generator for PG which allows direct graphical manipulation of syntactic structures.
COMPASSII supports students in producing diverse sentence structures on-line allowing them to focus on grammatical structure.

15. Future work (I)
Feedback texts adapted to the grammatical knowledge of the student,
Developing a real German course targeting some domain of constructions, e.g. word order in German clauses, for highschool students who are native speakers of English.
Evaluation studies with such ICALL courses.

16. Teach coordinate elision in German
Future work (II)
Teach coordinate elision in German
Example of clausal coordination from the TIGER treebank:
Monopole sollen geknackt werden
und Märkte sollen getrennt werden
‘Monopolies should be shattered and markets split’ ⌧ ⌧
Monopole sollen geknackt werden
und Märkte sollen getrennt werden ⌧ ⌧
COMPASSII subsystem of ELLEIPO:
generates all possible elisions
corpus frequences determine preferred choice

17. Dank u!
Thank you!

18. For more information on the Performance Grammar formalism
and COMPASSII
see our websites:
Ask us for a live demo
here at CALL 2010!