The objective of this research is to build automated models that emulate VerbNet, a semantic resource for English verbs. VerbNet has been built and expanded by linguists, forming a hierarchical clustering of verbs with common semantic and syntactic expressions, and is useful in semantic tasks. A major drawback is the difficulty of extending a…

Automatic answer assessment systems typically apply semantic similarity methods where student responses are compared with some reference answers in order to access their correctness. But student responses in dialogue based tutoring systems are often grammatically and semantically incomplete and additional information (e.g., dialogue history) is…

We evaluate here the performance of four models of cross-situational word learning: two global models, which extract and retain multiple referential alternatives from each word occurrence; and two local models, which extract just a single referent from each occurrence. One of these local models, dubbed "Pursuit," uses an associative…

How does AI&EdAIED today compare to 25 years ago? This paper addresses this evolution by identifying six trends. The trends are ongoing and will influence learning technologies going forward. First, the physicality of interactions and the physical space of the learner became genuine components of digital education. The frontier between the…

The effects of word predictability and shared semantic similarity between a target word and other words that could have taken its place in a sentence on language comprehension are investigated using data from a reading time study, a sentence completion study, and linear mixed-effects regression modeling. We find that processing is facilitated if…

With the advent of the Web, the notion of "information retrieval" has acquired a completely new connotation and currently encompasses several disciplines ranging from traditional forms of text and data retrieval in unstructured and structured repositories to retrieval of static and dynamic information from the contents of the surface and deep Web.…

Woollams, Lambon Ralph, Plaut, and Patterson (see record 2007-05396-004) reported detailed data on reading in 51 cases of semantic dementia. They simulated some aspects of these data using a connectionist parallel distributed processing (PDP) triangle model of reading. We argue here that a different model of reading, the dual route cascaded (DRC)…

This paper evaluates two classes of hypotheses about how people prosodically segment utterances: (1) meaning-based proposals, with a focus on Watson and Gibson's (2004) proposal, according to which speakers tend to produce boundaries before and after long constituents; and (2) balancing proposals, according to which speakers tend to produce…

Reports an error in "Context and spoken word recognition in a novel lexicon" by Kathleen Pirog Revill, Michael K. Tanenhaus and Richard N. Aslin ("Journal of Experimental Psychology: Learning, Memory, and Cognition," 2008[Sep], Vol 34[5], 1207-1223). Figure 9 was inadvertently duplicated as Figure 10. Figure 9 in the original article was correct.…

Using 3 experiments, I examined false memory for encoding context by presenting Deese-Roediger-McDermott themes (Deese, 1959; Roediger & McDermott, 1995) in usual-looking fonts and by testing related, but unstudied, lure items in a font that was shown during encoding. In 2 of the experiments, testing lure items in the font used to study their…

Three eye movement studies with novel lexicons investigated the role of semantic context in spoken word recognition, contrasting 3 models: restrictive access, access-selection, and continuous integration. Actions directed at novel shapes caused changes in motion (e.g., looming, spinning) or state (e.g., color, texture). Across the experiments,…

The authors identify 2 major types of statistical data from which semantic representations can be learned. These are denoted as "experiential data" and "distributional data". Experiential data are derived by way of experience with the physical world and comprise the sensory-motor data obtained through sense receptors. Distributional data, by…

A connectionist model of causal attribution is presented, emphasizing the use of domain-general principles of processing and learning previously employed in models of semantic cognition. The model categorizes objects dependent upon their observed 'causal properties' and is capable of making several types of inferences that 4-year-old children have…

How children go about learning the general regularities that govern language, as well as keeping track of the exceptions to them, remains one of the challenging open questions in the cognitive science of language. Computational modeling is an important methodology in research aimed at addressing this issue. We must determine appropriate learning…

Suggests that argument be seen as a private cognitive phenomenon, in contrast to the more traditional view of argument as a public message-based document. Differences between the views are noted and the respects in which argument creates and depends on cognitive order are discussed. (JMF)