Recent semantic space models learn vector representations for word meanings by observing statistical redundancies across a text corpus. A word's meaning is represented as a point in a high-dimensional semantic space, and semantic similarity between words is quantified by a function of their spatial proximity (typically the cosine of the angle…

Several recent studies have explored the applicability of the preferential attachment principle to account for vocabulary growth. According to this principle, network growth can be described by a process in which existing nodes recruit new nodes with a probability that is an increasing function of their connectivity within the existing network.…

Language is rife with ambiguity. Do children and adults meet this challenge in similar ways? Recent work suggests that while adults resolve syntactic ambiguities by integrating a variety of cues, children are less sensitive to top-down evidence. We test whether this top-down insensitivity is specific to syntax or a general feature of children's…

This dissertation uses the processing of anaphoric relations to probe how linguistic information is encoded in and retrieved from memory during real-time sentence comprehension. More specifically, the dissertation attempts to resolve a tension between the demands of a linguistic processor implemented in a general-purpose cognitive architecture and…

Using current mind/brain research, this paper explores the "hidden curriculum" in the contexts of teaching, learning and supervision. It explains ways in which current research on the nature of learning can fit into today's typical, "clinical" teaching techniques. The importance of respecting individual modes of learning is stressed; further to…