In this paper, we discuss the importance of the quality against the quantity of automatically extracted examples for word sense disambiguation (WSD). We first show that we can build a competitive WSD system with a memory-based classifier and a feature set reduced to easily and efficiently computable features. We then show that adding automatically annotated examples improves the performance of ...

Children with SLI exhibit overall deficits in novel word learning compared to their age-matched peers. However, the manifestation of the word learning difficulty in SLI was not consistent across tasks and the factors affecting the learning performance were not yet determined. Our aim is to examine the extent of word learning difficulties in Mandarin-speaking preschool children with SLI, and to ...

Learning by imitation is a powerful process for acquiring new knowledge, but there has been little research exploring imitation’s potential in the problem solving domain. Classical problem solving techniques tend to center around reinforcement learning, which requires significant trial-and-error learning to reach successful goals and problem solutions. Heuristics, hints, and reasoning by analog...

Learning by imitation is a powerful process for acquiring new knowledge, but there has been little research exploring imitation’s potential service to the problem-solving domain. Classical problem-solving techniques tend to center around reinforcement learning, which requires significant trial-and-error learning to reach successful goals and problem solutions. Heuristics, hints, and reasoning b...

Title Page Not included in page count. Title: Using model-tracing to conduct performance assessment of students' inquiry skills within a microworld. Background / Context: Description of prior research and its intellectual context. The National frameworks for science emphasize inquiry skills (NRC, 1996), however, in typical classroom practice, science learning often focuses on rote learning in p...

The dual-channel assumption of the cognitive theory multimedia learning suggests that importing a large amount information through single (visual or audio) channel overloads channel, causing partial loss information, while it simultaneously multiple channels relieves burden on them and leads to registration larger information. In light such knowledge, this study investigates possibility reinfor...

This paper proposes a method for the unsupervised learning of lexicons from pairs of a spoken utterance and an object as its meaning without any a priori linguistic knowledge other than a phoneme acoustic model. In order to obtain a lexicon, a statistical model of the joint probability of a spoken utterance and an object is learned based on the minimum description length principle. This model c...