Simon McAlister

Combining interaction and context design to support collaborative argumentation using a tool for synchronous CMC

Empirical studies and theory suggest that educational dialogue can be used to support learners in the development of reasoning, critical thinking and argumentation. This paper presents an educational design for synchronous online peer discussion that guides student dialogue in ways that lead to improved argumentation and collaborative knowledge development. This design includes a mediating interface – or tool, linked to a broader set of online educational activities – a designed local context, where the latter aims to provide conditions that support argumentation. The approach is based on collaborative working and dialogue game approaches to discussion. Preliminary findings with UK Open University students showed the argumentation process was more coherent, varied, deeper and extended when using our interaction design compared with the use of a simple unstructured interface.

Investigating and promoting educational argumentation: towards new digital practices

This article reviews and synthesizes over a decade of research that has used discourse analysis, dialogue modelling and empirical techniques to investigate educational argumentation and to design digital tools that support its practice. This approach – incorporating theoretical, empirical and design‐based methods according to what tends to now be called a ‘learning science’ approach – has investigated argumentation through developing the notion of ‘dialogue games’. This is a paradigm that can be used analytically or prescriptively to further our understanding of argumentation processes and how these can be orchestrated for educational purposes. The article explains why argument is important; concisely reviews a range of analytic, empirical and design‐based studies of argumentation and related digital tools; critiques these methods and approaches; raises questions and provides some pointers for researching and supporting new and emerging argumentative practices within the developing digital landscape.

Mining Arguments From 19th Century Philosophical Texts Using Topic Based Modelling

In this paper we look at the manual analysis of arguments and how this compares to the current state of automatic argument analysis. These considerations are used to develop a new approach combining a machine learning algorithm to extract propositions from text, with a topic model to determine argument structure. The results of this method are compared to a manual

Digital Games and Learning in Cyberspace: A Dialogical Approach

Currently there is considerable enthusiasm for exploring how we can apply digital gaming paradigms to learning. But these approaches are often weak in linking the game-playing activity to transferable social or conceptual processes and skills that constitute, or are related to, learning. In contrast, this article describes a ‘dialogue game’ approach to learning in cyberspace related to Wittgensteins notion of a ‘language game’ that seeks to explicitly link game-playing activity to the development of generic dialogical and reasoning skills that lead to improved conceptual understanding and collaborative knowledge refinement. This article initially discusses the current articulations of gaming as an approach to learning before justifying and describing the dialogue game approach the authors are currently adopting. This is followed by a summary of empirical evidence in support of this design paradigm and a desciption of a socio-cognitive tool called InterLoc that organises, mediates, structures and scaffolds educational dialogue games. The approach is demonstrated and the implications it holds for designing gaming or other types of educational interaction are then discussed in the context of existing and near-future possibilities within the evolving e-learning landscape.

Multi-level computational methods for interdisciplinary research in the HathiTrust Digital Library

We show how faceted search using a combination of traditional classification systems and mixed-membership topic models can go beyond keyword search to inform resource discovery, hypothesis formulation, and argument extraction for interdisciplinary research. Our test domain is the history and philosophy of scientific work on animal mind and cognition. The methods can be generalized to other research areas and ultimately support a system for semi-automatic identification of argument structures. We provide a case study for the application of the methods to the problem of identifying and extracting arguments about anthropomorphism during a critical period in the development of comparative psychology. We show how a combination of classification systems and mixed-membership models trained over large digital libraries can inform resource discovery in this domain. Through a novel approach of “drill-down” topic modeling—simultaneously reducing both the size of the corpus and the unit of analysis—we are able to reduce a large collection of fulltext volumes to a much smaller set of pages within six focal volumes containing arguments of interest to historians and philosophers of comparative psychology. The volumes identified in this way did not appear among the first ten results of the keyword search in the HathiTrust digital library and the pages bear the kind of “close reading” needed to generate original interpretations that is the heart of scholarly work in the humanities. Zooming back out, we provide a way to place the books onto a map of science originally constructed from very different data and for different purposes. The multilevel approach advances understanding of the intellectual and societal contexts in which writings are interpreted.