Evidence-Based Dialogue Maps as a research tool to evaluate the quality of school pupils’ scientific argumentation

This pilot study focuses on the potential of Evidence-based Dialogue Mapping as a participatory action research tool to investigate young teenagers’ scientific argumentation. Evidence-based Dialogue Mapping is a technique for representing graphically an argumentative dialogue through Questions, Ideas, Pros, Cons and Data. Our research objective is to better understand the usage of Compendium, a Dialogue Mapping software tool, as both (1) a learning strategy to scaffold school pupils’ argumentation and (2) as a method to investigate the quality of their argumentative essays. The participants were a science teacher-researcher, a knowledge mapping researcher and 20 pupils, 12-13 years old, in a summer science course for “gifted and talented” children in the UK. This study draws on multiple data sources: discussion forum, science teacher-researcher’s and pupils’ Dialogue Maps, pupil essays, and reflective comments about the uses of mapping for writing. Through qualitative analysis of two case studies, we examine the role of Evidence-based Dialogue Maps as a mediating tool in scientific reasoning: as conceptual bridges for linking and making knowledge intelligible; as support for the linearisation task of generating a coherent document outline; as a reflective aid to rethinking reasoning in response to teacher feedback; and as a visual language for making arguments tangible via cartographic conventions

Using Toulmin Argumentation to develop an Online Dispute Resolution Environment

Our goal is to model reasoning in discretionary legal domains. To do so, we use Knowledge Discovery from Database Techniques. However there are obstacles to this approach, including difficulties in generating explanations once conclusions have been inferred, difficulties associated with the collection of sufficient data from past cases and difficulties associated with integrating two vastly different paradigms. Toulmin’s treatise on the uses of argument can be gainfully employed to construct legal decision support systems in discretionary domains. We show how we can use Toulmin’s approach to build such systems with examples taken from the domains of eligibility for legal aid, evaluation of eyewitness evidence, family law, refugee law and sentencing. We then show how Toulmin Argument Structures can be developed to construct an Online Dispute Resolution environment that allows for determining BATNAs, exchanging opinions and providing advice about tradeoffs

Argumentation-Based Contract Monitoring in Uncertain Domains

Publisher PD

Argumentation models and their use in corpus annotation: practice, prospects, and challenges

The study of argumentation is transversal to several research domains, from philosophy to linguistics, from the law to computer science and artificial intelligence. In discourse analysis, several distinct models have been proposed to harness argumentation, each with a different focus or aim. To analyze the use of argumentation in natural language, several corpora annotation efforts have been carried out, with a more or less explicit grounding on one of such theoretical argumentation models. In fact, given the recent growing interest in argument mining applications, argument-annotated corpora are crucial to train machine learning models in a supervised way. However, the proliferation of such corpora has led to a wide disparity in the granularity of the argument annotations employed. In this paper, we review the most relevant theoretical argumentation models, after which we survey argument annotation projects closely following those theoretical models. We also highlight the main simplifications that are often introduced in practice. Furthermore, we glimpse other annotation efforts that are not so theoretically grounded but instead follow a shallower approach. It turns out that most argument annotation projects make their own assumptions and simplifications, both in terms of the textual genre they focus on and in terms of adapting the adopted theoretical argumentation model for their own agenda. Issues of compatibility among argument-annotated corpora are discussed by looking at the problem from a syntactical, semantic, and practical perspective. Finally, we discuss current and prospective applications of models that take advantage of argument-annotated corpora

AI & Law, logic and argument schemes

This paper reviews the history of AI & Law research from the perspective of argument schemes. It starts with the observation that logic, although very well applicable to legal reasoning when there is uncertainty, vagueness and disagreement, is too abstract to give a fully satisfactory classification of legal argument types. It therefore needs to be supplemented with an argument-scheme approach, which classifies arguments not according to their logical form but according to their content, in particular, according to the roles that the various elements of an argument can play. This approach is then applied to legal reasoning, to identify some of the main legal argument schemes. It is also argued that much AI & Law research in fact employs the argument-scheme approach, although it usually is not presented as such. Finally, it is argued that the argument-scheme approach and the way it has been employed in AI & Law respects some of the main lessons to be learnt from Toulmin's The Uses of Argument

Ontological Approaches to Modelling Narrative

We outline a simple taxonomy of approaches to modelling narrative, explain how these might be realised ontologically, and describe our continuing work to apply these techniques to the problem of Memories for Life