Mutual reconstruction of arguments in dialogue

Analyzing argumentative discourse is not a an activity exclusively reserved for scholars in argumentation theory, rhetoric, and philosophy of language. This paper proposes that the faculty of analyzing argument structure is a basic precondition of und erstanding one another in argumentational interactions. Based on an examination of televised debates, it is demonstrated how participants employ quasi-logical schemata to reconstruct implicit elements in other participants\u27s argument structures for purpo ses of clarification and criticism. This very descriptive approach entrusts, as it were, the actual argument analysis to the language users themselves

Argumentation Mining in User-Generated Web Discourse

The goal of argumentation mining, an evolving research field in computational linguistics, is to design methods capable of analyzing people's argumentation. In this article, we go beyond the state of the art in several ways. (i) We deal with actual Web data and take up the challenges given by the variety of registers, multiple domains, and unrestricted noisy user-generated Web discourse. (ii) We bridge the gap between normative argumentation theories and argumentation phenomena encountered in actual data by adapting an argumentation model tested in an extensive annotation study. (iii) We create a new gold standard corpus (90k tokens in 340 documents) and experiment with several machine learning methods to identify argument components. We offer the data, source codes, and annotation guidelines to the community under free licenses. Our findings show that argumentation mining in user-generated Web discourse is a feasible but challenging task.Comment: Cite as: Habernal, I. & Gurevych, I. (2017). Argumentation Mining in User-Generated Web Discourse. Computational Linguistics 43(1), pp. 125-17

Analytic frameworks for assessing dialogic argumentation in online learning environments

Over the last decade, researchers have developed sophisticated online learning environments to support students engaging in argumentation. This review first considers the range of functionalities incorporated within these online environments. The review then presents five categories of analytic frameworks focusing on (1) formal argumentation structure, (2) normative quality, (3) nature and function of contributions within the dialog, (4) epistemic nature of reasoning, and (5) patterns and trajectories of participant interaction. Example analytic frameworks from each category are presented in detail rich enough to illustrate their nature and structure. This rich detail is intended to facilitate researchers’ identification of possible frameworks to draw upon in developing or adopting analytic methods for their own work. Each framework is applied to a shared segment of student dialog to facilitate this illustration and comparison process. Synthetic discussions of each category consider the frameworks in light of the underlying theoretical perspectives on argumentation, pedagogical goals, and online environmental structures. Ultimately the review underscores the diversity of perspectives represented in this research, the importance of clearly specifying theoretical and environmental commitments throughout the process of developing or adopting an analytic framework, and the role of analytic frameworks in the future development of online learning environments for argumentation

The Dimensions of Argumentative Texts and Their Assessment

The definition and the assessment of the quality of argumentative texts has become an increasingly crucial issue in education, classroom discourse, and argumentation theory. The different methods developed and used in the literature are all characterized by specific perspectives that fail to capture the complexity of the subject matter, which remains ill-defined and not systematically investigated. This paper addresses this problem by building on the four main dimensions of argument quality resulting from the definition of argument and the literature in classroom discourse: dialogicity, accountability, relevance, and textuality (DART). We use and develop the insights from the literature in education and argumentation by integrating the frameworks that capture both the textual and the argumentative nature of argumentative texts. This theoretical background will be used to propose a method for translating the DART dimensions into specific and clear proxies and evaluation criteria

Parsing Argumentation Structures in Persuasive Essays

In this article, we present a novel approach for parsing argumentation structures. We identify argument components using sequence labeling at the token level and apply a new joint model for detecting argumentation structures. The proposed model globally optimizes argument component types and argumentative relations using integer linear programming. We show that our model considerably improves the performance of base classifiers and significantly outperforms challenging heuristic baselines. Moreover, we introduce a novel corpus of persuasive essays annotated with argumentation structures. We show that our annotation scheme and annotation guidelines successfully guide human annotators to substantial agreement. This corpus and the annotation guidelines are freely available for ensuring reproducibility and to encourage future research in computational argumentation.Comment: Under review in Computational Linguistics. First submission: 26 October 2015. Revised submission: 15 July 201

A framework to analyze argumentative knowledge construction in computer-supported collaborative learning

Computer-supported collaborative learning (CSCL) is often based on written argumentative discourse of learners, who discuss their perspectives on a problem with the goal to acquire knowledge. Lately, CSCL research focuses on the facilitation of specific processes of argumentative knowledge construction, e.g., with computer-supported collaboration scripts. In order to refine process-oriented instructional support, such as scripts, we need to measure the influence of scripts on specific processes of argumentative knowledge construction. In this article, we propose a multi-dimensional approach to analyze argumentative knowledge construction in CSCL from sampling and segmentation of the discourse corpora to the analysis of four process dimensions (participation, epistemic, argumentative, social mode)

THE FLOWS OF IDEAS OF ENGLISH ARGUMENTS BY INDONESIAN WRITERS FOUND IN THE OPINION FORUM OF THE JAKARTA POST: AN INDICATION OF LANGUAGE SHIFT

English writing ability is badly needed by professionals and university students, to facilitate their study and career. However, writing coherently is difficult for many of them. Tangkiengsirisin (2010, 1) states that flow of ideas is the main criterion for advanced writing. This study is aimed at finding out the flows of ideas of English Arguments by Indonesian writers. The study is descriptive and qualitative, analyzing 14 articles from The Jakarta Post. The findings reveal that 64 % of the data are developed linearly, contradicting with Kaplan’s explanation that oriental groups express their ideas mostly indirectly, circularly. The socio-cultural context, i.e. globalization has changed the circular into linear pattern

Internal and external scripts in computer-supported collaborative inquiry learning

We investigated how differently structured external scripts interact with learners’ internal scripts concerning individual knowledge acquisition in a Web-based collaborative inquiry learning environment. 90 students from two secondary schools participated. Two versions of an external collaboration script (high vs. low structured) supporting collaborative argumentation were embedded within a Web-based collaborative inquiry learning environment. Students’ internal scripts were classified as either high or low structured, establishing a 2x2-factorial design. Results suggest that the high structured external collaboration script supported the acquisition of domain-general knowledge of all learners regardless of their internal scripts. Learners’ internal scripts influenced the acquisition of domain-specific knowledge. Results are discussed concerning their theoretical relevance and practical implications for Web-based inquiry learning with collaboration scripts