Instance Theory and Universal Grammar in Second Language

research

Team members : Steve, Jones, Ines, Trixie

Teacher : Aya Okamato

Instance theory Concepts and categorization

One important area in which instance theory has been developed is that of concepts and categorization (Medin and Schaffer, 1978; Smith and Medin, 1981; Nosofsky, 1986; Nosofsky et al., 1992; Estes, 1994).

Classical idea

An item belongs to a given category if and only if it has the defining characteristics of that category.

Prototype theory (Posner and Keele, 1970; Rosch, 1978; Smith and Medin, 1981)

Each category has a most representative case, abstracted from the various examples of it, and judgments about category membership are made primary by comparison with this prototype.

Logan’s automatization theory

Learners initially rely on a generally procedure, or algorithm, but then gradually accumulate a store of case in which they have used the skill.

Problems in applying instance theory to natural language

One type of problem lies in the interpretation of the approach’s important concepts.

Features Instances and learning tasks

The need for organization of the instances

Two fundamental aspects of language point to an intricate organization of linguistic knowledge:

- Systematicity

- The Efficiency with linguistic knowledge is used

UG approach

General considerations Proposes Principle and Parameters

theory of Chomsky(1981;1986;1995)as a way to learn.

In order to learn instances, we need to organize instances.

Organization of instances

We organize the instances in relation to the language theory.

System of language=system of organization.

Instances and learning tasks

UG is a good solution to learn instances.

No need for large amounts of constraints, only learn what is specific of the language.

Features

Language theory provided the features

Each of these features are encoded

How do we possess these features?

- According to Principles and Parameters theory.

Instances and algorithms

When you develop an algorithms, you gather instances.

This shift from rule to instance can happen in 2 ways:

1. Production, comprehension, judgment - that’s the right instance for the situation.

2. L2 learners have the advantage of a set of L1 skills to help with learning.

Nature of the representations

The relationship between L1 and L2.

- Affection between L1 and L2

- Learner’s competence

Similarity and performance

- The similarity between a target instance and a stored instance.

- Odd performance errors.

Grammar judgments

Grammar judgments depend on two situations, which is the violation.

- Situation 1: If the sentence violates UG.

- Situation 2: If no such violation occurs.

Production

How the learners would produce their instances?

- Learners’ algorithm and instance theory in UG.

- Algorithm, a way that the learner tries to use their knowledge of English to produce a sentence or an utterance.

Processing

How the learners process?

- The use of implicational relations.

- Resembling the existing interlanguage.

Some possible applications to language learning

Learning from noisy data

An advantage of this approach is that it directly accounts for the existence of good subjectless sentences (Truscott and Wexler,1989;Valian,1990).

Undoing errors in the learning process

-The Uniqueness Principle

-The Subset Principle

Common observation regarding both L1 and L2 acquisition.

The Uniqueness Principle

The principle has also been applied to L2 parameter setting (Rutherford,1989;Trahey and White,1993).

The Subset Principle

The Principle constrains the order in which learners consider the possible values of a parameter (Berwick,1985; Manzini and Wexler,1987).

Transfer and Fossilization

-It is probably uncontroversial (Transfer).

-In contexts that encourage a reliance on algorithms and discourage the natural (Fossilization).

The nondiscrete character of language and learning

Nondiscreteness is not limited to the learning process. It seems to hold for L1 as well(Valian,1991).

Abstraction in the UG-instance theory approach

The issue of storage and processing capacity:

- Massive parallel processing

- Pools, the storage sorts of the brain.

Systematicity within acquired knowledge

The learners’ knowledge of forming sentences systematically.

- Some of the acquired knowledge can’t be readily attributed to UG.

Historical change

Languages evolves, from time to time.

- SOV (earlier matrix clauses)

- SVO (the present day)

Conclusion

Language is a big knowledge!

- Abstractions

- Pools

- Instances

Thank you ^_^