Artificial grammar learning

His explanation was that learners could identify the common characteristics between learned sequences and accordingly encode them to a memory set.

He claimed that if participants could encode the grammar rules as productive memory sets, then they should be able to verbalize their strategy in detail.

As in the original paradigm developed by Miller, participants were asked to memorize a list of letter strings which were created from an artificial grammar rule model.

In a typical AGL experiment, participants are required to memorize strings of letters previously generated by a specific grammar.

In the case of a standard AGL implicit learning task,[3] subjects are not told that the strings are based on a specific grammar.

During a test phase, the subjects are instructed to categorize new letter strings as "ruleful" or "unruleful".

Implicit learning is considered to be successful when the percentage of correctly sorted strings is significantly higher than chance level.

If this significant difference is found, it indicates the existence of a learning process that is more involved than memorizing the presented letter strings.

A sentence like "the dog cat the ball" is implicitly recognized as grammatically incorrect due to the lack of utterances that contain those words paired in that specific order.

Traditional approaches to AGL claim that the stored knowledge obtained during the learning phase is abstract.

[6][11] In any case, it is assumed that the information stored in memory is retrieved in the test phase and is used to aid decisions about letter strings.

[18] A series of experiments with amnesiac patients support the idea that AGL involves both abstract concepts and concrete exemplars.

Amnesiacs were able to classify stimuli as "grammatical" vs. "randomly constructed" just as well as participants in the control group.

Since the amnesiacs were unable to store specific "chunks" in memory, they completed the task using an abstract set of rules.

Knowledge encoded during training may include many aspects of the presented stimuli (whole strings, relations among elements, etc.).

The contribution of the various components to performance depends on both the specific instruction in the acquisition phase and the requirements of the retrieval task.

[13] Therefore, the instructions on every phase are important in order to determine whether or not each stage will require automatic processing.

[26] Results from over 200 experiments on this effect indicate that there is a positive relationship between mean "goodness" rating and frequency of stimulus exposure.

Following each exposure participants were asked to rate the degree to which each stimulus suggested "good" vs. "bad" effect on a 7-point scale.

[28] For example, when the model encounters "the-dog-chased" and "the-cat-chased" it classifies "dog" and "cat" as being members of the same class since they both precede "chase".

Contemporary studies with AGL have attempted to identify which structures are involved in the acquisition of grammar and implicit learning.

[30] De Vries, Barth, Maiworm, Knecht, Zwitserlood & Flöel[31] found that electrical stimulation of Broca's area enhances implicit learning of an artificial grammar.

Direct current stimulation may facilitate acquisition of grammatical knowledge, a finding of potential interest for rehabilitation of aphasia.