Three potential sources of comprehensible input for second language acquisition are examined: Modified Input, Interactionally Modified Input and Modified Output. To this end, an attempt is made to closely investigate how each type of linguistic environment facilitates learner comprehension, and subsequently, acquisition. Different theoretical claims as well as a number of empirical studies are ...

This study attempts to test aspects of the input hypothesis (Krashen, 1980, 1983, 1985) and Long's modification of it (Long, 1980, 1983a, 1985). Specifically, it experimentally tests the hypothesis that both input and interactional modifications facilitate second language acquisition, using Japanese as the target language. Three experimental groups were differentiated in terms of input and inte...

The main rivals to the input or comprehension hypothesis are the skill-building and comprehensible output hypotheses. Studies claiming to show that the skill-building hypothesis is correct consist of studies of the impact of grammar instruction and error correction. These studies show only that instruction and correction have a modest impact on tests in which subjects are focused on form. Compr...

We present a model of creating a hierarchical set of rules that encode generalizations and exceptions derived from induction learning. The rules use the input features directly and are therefore comprehensible to the users. Learning is performed by a feedforward neural network and the rules are extracted from the trained network. A pattern classification task is used to demonstrate the efficacy...

A significant limitation of neural networks is that the representations they learn are usually incomprehensible to humans. We present a novel algorithm, TREPAN, for extracting comprehensible , symbolic representations from trained neural networks. Our algorithm uses queries to induce a decision tree that approximates the concept represented by a given network. Our experiments demonstrate that T...