Investigation And Analysis Of Non-Traditional Nato Roles In Kosovo: Building Bridges Between Military & Humanitarian Actors

Since the end of the Cold War, Western military forces have found themselves increasingly responding to complex emergencies and humanitarian crises around the world. These experiences have redefined military roles and deepened the way in which commanders view and respond to inter-ethnic conflict. In Kosovo, the unprecedented “humanitarian” intervention, and actions in the decade since, exemplify these changes and demonstrate the non-traditional roles and progressive strategies employed by NATO forces in efforts to assist development and build sustainable peace. Yet despite having similar roles and objectives, a wealth of resources and knowledge to be shared – there is minimal dialogue, collaboration or cooperation between military and humanitarian actors in Kosovo. This Capstone Paper reviews an applied research project which intervenes in the conflict between military-humanitarian actors in Kosovo. The goal of the intervention is to provide the historical context, define patterns and present issues of an organization which is inherently secretive, difficult for “outsiders” to communicate with, and struggling to adapt strategies to an evolving view of the complexities of inter-ethnic conflict. The major product actively addresses the context, systems, and structures which support the ongoing conflict between actors and provides direct recommendations for (re)building lines of communication. It also makes an attempt to transform the attitudes and beliefs of all stakeholders by humanizing conflict parties, rationalizing behaviors, and encouraging stakeholders to enter into constructive dialogue centered on actual issues and patterns

Tarski's world. 1993.

xiv, 313 p. ; 24 cm. 1 computer disk

Graphical revelations: Comparing students' translation errors in graphics and logic.

We are interested in developing a better understanding of what it is that students find difficult in learning logic. We use both natural language and diagram-based methods for teaching students the formal language of first-order logic. In this paper, we present some initial results that demonstrate that, when we look at how students construct diagrammatic representations of information expressed in natural language (NL) sentences, the error patterns are different from those observed when students translate from NL to first-order logic (FOL). In the NL-to-diagram construction task, errors associated with the interpretation of the expression not a small dodecahedron were manifested much more frequently with respect to the objects size than with respect to its shape. In the NL-to-FOL task, however, no such asymmetry was observed. We hypothesize a number of possible factors that might be implicated here: differences between the NL-todiagram and NL-to-FOL tasks; the reduced expressivity of diagrams compared to language; scoping errors in participants NL parsing; and the visuospatial properties of the blocks-world domain. In sum, constructing a diagram requires the student to provide an instantiated representation of the meaning of a natural language sentence; this tests their understanding in a way that translation into firstorder logic does not, by ensuring that they are not simply carrying out a symbol manipulation exercise

Automated Assessment in the Internet Classroom.

A likely feature of the Internet classroom is automated assessment of student exercises. In this paper, we describe the design and implementation of the Grade Grinder, an Internet-based assessment service developed for use with logic-teaching courseware. We discuss the utility of this platform both as a pedagogical resource, and as a provider of data for research on student problem-solving. We end by making some observations in regard to the scope for extending this approach beyond the domain of logic-teaching to other domains

An Empirical Study of Errors in Translating Natural Language into Logic

Every teacher of logic knows that the ease with which a student can translate a natural language sentence into formal logic depends, amongst other things, on just how that natural language sentence is phrased. This paper reports findings from a pilot study of a large scale corpus in the area of formal logic education, where we used a very large dataset to provide empirical evidence for specific characteristics of natural language problem statements that frequently lead to students making mistakes. We developed a rich taxonomy of the types of errors that students make, and implemented tools for automatically classifying student errors into these categories. In this paper, we focus on three specific phenomena that were prevalent in our data: Students were found (a) to have particular difficulties with distinguishing the conditional from the biconditional, (b) to be sensitive to word-order effects during translation, and (c) to be sensitive to factors associated with the naming of constants. We conclude by considering the implications of this kind of large-scale empirical study for improving an automated assessment system specifically, and logic teaching more generally