Online Educational Outcomes Could Exceed Those of the Traditional Classroom

An axiom of online education is that teachers should not mechanically translate existing courses into an online format. If so, how should new or ongoing courses be reshaped for the online environment and why? The answers come both from the opportunities offered by the structure of online education and from a body of research from cognitive psychology and cognitive science that provides insight into the way people actually learn. Freed from the time and space constraints inherent in face-to-face higher education settings as well as the deeply ingrained expectations of both teachers and students, online education provides a more flexible palette upon which evidence-based ideas about learning can be integrated into course structure and design. As a result, online education can potentially deliver learning experiences and outcomes that are superior to typical face-to-face classrooms. The ability to integrate experiences that stimulate real, long lasting learning represents one of online education’s greatest potential benefits

Net: A Utility for Building Regular Process Networks on the BBN Butterfly Parallel Processor

Coarse-grained parallel architectures like the BBN Butterfly are difficult to use without tools for building networks of communicating processes. Net is a tool for creating a useful class of process networks. This report describes the Net utility, an example application, and some design decisions and experiences

Thesis Proposal: A Plan-Based Approach to Conversational Implicature

Thesis Proposal.Implicatures are those propositions that must be inferred from an utterance in order to make sense of it in context, but which are not truth conditions or entailments of that utterance. Conversational implicatures are those that can be explained by general principles rather than lexical choice. Conversational implicature was defined in philosophy and discussed in linguistics, but lacks an adequate account in any discipline. For the computational linguist, this means that much information conveyed indirectly in discourse has no computational model. We show that knowledge of goals and plans is necessary for the computation of some implicatures, and very useful for a much larger class of implicatures. Our model uses a set of inference rules about STRIPS-style plans for implicature computation. It incorporates a computational model of speech acts (based on propositional attitudes) and surface speech acts (based on linguistic features). We propose an implementation, and relate it to other research in computational linguistics

Conversation Acts in Task-Oriented Spoken Dialogue

A linguistic form's compositional, timeless meaning can be surrounded or even contradicted by various social, aesthetic, or analogistic companion meanings. This paper addresses a series of problems in the structure of spoken language discourse, including turn-taking and grounding. It views these processes as composed of fine-grained actions, which resemble speech acts both in resulting from a computational mechanism of planning and in having a rich relationship to the specific linguistic features which serve to indicate their presence. The resulting notion of Conversation Acts is more general than speech act theory, encompassing not only the traditional speech acts but turn-taking, grounding, and higher-level argumentation acts as well. Furthermore, the traditional speech acts in this scheme become fully joint actions, whose successful performance requires full listener participation. This paper presents a detailed analysis of spoken language dialogue. It shows the role of each class of conversation acts in discourse structure, and discusses how members of each class can be recognized in conversation. Conversation acts, it will be seen, better account for the success of conversation than speech act theory alone

Linguistic and pragmatic constraints on utterance interpretation

Thesis (Ph. D.)--University of Rochester. Dept. of Computer Science, 1990.To model how people understand language, it becomes necessary to understand not only grammar and logic, but also how people use language to affect their environment. This area of study is known as natural language pragmatics. Speech acts, for instance, are the offers, promises, announcements, and so on that people make by talking. The same expression may be different acts in different contexts, and yet not every expression performs every act. We want to understand how people are able to recognize each other's intentions and implications in saying something. Previous plan-based theories of speech act interpretation do not account for the conventional aspect of speech acts. They can, however, be made sensitive to both linguistic and propositional information. This document presents a method of speech act interpretation which uses patterns of linguistic features (e.g. mood, verb form, sentence adverbials, thematic roles) to identify a range of speech act interpretations for the utterance. These are then filtered and elaborated by inferences about agents' goals and plans. In many cases the plan reasoning consists of short, local inference chains (that are in fact conversational implicatures), and extended reasoning is necessary only for the most difficult cases. The method is able to accommodate a wide range of cases, from those which seem very idiomatic to those which must be analyzed using knowledge about the world and human behavior. It explains how "Can you pass the salt?" can be a request while "Are you able to pass the salt?" is not

Two Constraints on Speech Act Ambiguity

Existing plan-based theories of speech act interpretation do not account for the conventional aspect of speech acts. We use patterns of linguistic features (e.g. mood, verb form, sentence adverbials, thematic roles) to suggest a range of speech act interpretations for the utterance. These are filtered using plan-based conversational implicatures to eliminate inappropriate ones. Extended plan reasoning is available but not necessary for familiar forms. Taking speech act ambiguity seriously, with these two constraints, explains how "Can you pass the salt?" is a typical indirect request while "Are you able to pass the salt?" is not

Parameterization of Mottle Textures

Parameterization of textures can be useful for detection of textual similarities and matching. In this project we have developed a stochastic model to generate a set of parameters from the texture image domain and frequency domain. This model is aimed at quantification of textures for detection of similarities and differences. Our attention has been concentrated on the parameterization of mottled textures. To test the model we have used it to generate texture images back from the parameters obtained from image analysis. The similarities and differences between the generated image and original images are used to refine and test the parametric model