Using Collaborative Filtering in an Intelligent Tutoring System for Legal Argumentation Niels...

Using Collaborative Filtering in an Intelligent Tutoring System for Legal Argumentation

Niels Pinkwart, Vincent Aleven, Kevin Ashley, and Collin Lynch

Carnegie Mellon UniversityUniversity of Pittsburgh

Niels PinkwartAH 2006


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An ITS for legal argumentation Problem: legal argumentation is an ill-

defined domain ITS approach: Engage students in analyzing

& reflecting about examples of expert Socratic reasoning

Application of collaborative filtering and social navigation principles: “Standard” activities: markup, “tagging”

resources, recommending objects created by peers

Novel function: indirect, results employed as tools to generate better feedback in ITS



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US Supreme Court Oral Arguments

Important part of decision process Attorneys propose a decision rule

(“test”) to determine how to decide a case

Justices challenge these tests, often by posing hypothetical scenarios



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An Example Case Example: Lynch v. Donnelly 465 U.S. 668

(1984) Facts: The city of Pawtucket annually erected

a Christmas display located in the city's shopping district. The display included such objects as a Santa Claus house, a Christmas tree, a banner reading "Seasons Greetings," and a nativity scene.

Question: Did this violate the constitutional separation of Church and State?

MR. DE LUCA: With the possible exception of the cross, the nativity scene is one of the most powerful religious symbols in this country, and most certainly one of the most powerful Christian religious symbols in this country. (…) Pawtucket's purchase, the maintenance, and the erection of the fundamental Christian symbol involves government in religion to a profound and substantial degree. (…)

JUSTICE: Now, if the city did not own the crèche itself, so that everything that was contributed to the display, including the crèche, were privately owned, it wouldn't violate the First Amendment, the fact that it was right next door to the City Hall, would it?

MR. DE LUCA: I think that in understanding that the city owns all of the symbols and all of the artifacts that are contained in this display, and assuming that the crèche were purchased and paid for privately without any other explanation that it is private, then I think it would still violate the establishment clause for the First Amendment, because there is no indication to anyone looking at that that the display or the crèche is not part of the broader display which is put up and sponsored by the city. (…)

JUSTICE: Would you regard the prayer that I spoke of to your friend in the House or the Senate or in any state legislature as purely symbolic, or is it a matter of substance?

Example: Tests and Hypotheticals

Test

Hypo

TestModif.

Hypo

A Tool For Graphical Argument Visualization



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An Example Diagram(Result of Pilot Study)



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Intelligent Support How help students

analyze the argument transcript? navigate the interlinked information spaces?

Automated diagram analysis allow for: Graph structure inspection

general argumentation principles, e.g. “there should be at least one test”

Checks of links between graph and transcript case specific “important passages”

Not subject of this talk ( ITS 2006)



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Content Analysis?



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Content WeaknessesIdea:

Make use of peer students working on the same task

Have students rate peer solutions as part of their working with the system



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Content Weaknesses Exploit that the system

knows what part of the graph refers to certain important parts of text…

Student A

Student B

Student C



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Content Weaknesses … and use these

relations for generating the dialogs.

Student A

Student B

Student C



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Principle for quality rating q: weighted average of base rating and evaluation rating (0=poor, 1=excellent)

Base rating Based on how student rates other solutions Serves as initial score heuristic, immediately

available Assumption: having good solution correlates to

recognizing good solutions

n

kii

k

ii qq

nb

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)1(1

Content Weaknesses

Recommended items Non-recommended items



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Evaluation rating Based on recommendations a student’s

answer receives (or not), and by whom Develops over time Takes peer opinions into account Assumption: measures actual quality

j

ii

p

ii

q

qe

1

1

Content Weaknesses

Actual recommenders

All possible recommenders



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Feedback: Self Explanation Prompts Use detected

weaknesses as tailored self explanation prompts

Offer opportunities for reflection about specific parts of Socratic reasoning examples

Present if quality rating below specific threshold (e.g. 0.3)

Does the System provide Feedback when appropriate?



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Conclusion and OutlookUse collaborative filtering methods to generate a quality

heuristic for important parts of argument diagrams

Filter for quality Aim is not to

show only “best” or “most matching” argument descriptions

get to very precise rating Instead: use implicitly to generate adaptive feedback

in the ITS

Pilot studies with single users successful, studies with small groups to come

Larger lab studies to evaluate the ITS: Fall 2006



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Please visit our project website:

http://www.cs.cmu.edu/~hypoform

Email:

[email protected]

Using Collaborative Filtering in an Intelligent Tutoring System for Legal Argumentation Niels...

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