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

論述における談話構造および論理構造の解析

Tohoku University博士（情報科学）thesi

Proceedings ICPW'07: 2nd International Conference on the Pragmatic Web, 22-23 Oct. 2007, Tilburg: NL

Proceedings ICPW'07: 2nd International Conference on the Pragmatic Web, 22-23 Oct. 2007, Tilburg: N

Analyzing collaborative learning processes automatically

In this article we describe the emerging area of text classification research focused on the problem of collaborative learning process analysis both from a broad perspective and more specifically in terms of a publicly available tool set called TagHelper tools. Analyzing the variety of pedagogically valuable facets of learners’ interactions is a time consuming and effortful process. Improving automated analyses of such highly valued processes of collaborative learning by adapting and applying recent text classification technologies would make it a less arduous task to obtain insights from corpus data. This endeavor also holds the potential for enabling substantially improved on-line instruction both by providing teachers and facilitators with reports about the groups they are moderating and by triggering context sensitive collaborative learning support on an as-needed basis. In this article, we report on an interdisciplinary research project, which has been investigating the effectiveness of applying text classification technology to a large CSCL corpus that has been analyzed by human coders using a theory-based multidimensional coding scheme. We report promising results and include an in-depth discussion of important issues such as reliability, validity, and efficiency that should be considered when deciding on the appropriateness of adopting a new technology such as TagHelper tools. One major technical contribution of this work is a demonstration that an important piece of the work towards making text classification technology effective for this purpose is designing and building linguistic pattern detectors, otherwise known as features, that can be extracted reliably from texts and that have high predictive power for the categories of discourse actions that the CSCL community is interested in

論述における非明示的推論の解析：オーバーナイトアプローチ

Tohoku University博士（情報科学）thesi

Neural End-to-End Learning for Computational Argumentation Mining

We investigate neural techniques for end-to-end computational argumentation mining (AM). We frame AM both as a token-based dependency parsing and as a token-based sequence tagging problem, including a multi-task learning setup. Contrary to models that operate on the argument component level, we find that framing AM as dependency parsing leads to subpar performance results. In contrast, less complex (local) tagging models based on BiLSTMs perform robustly across classification scenarios, being able to catch long-range dependencies inherent to the AM problem. Moreover, we find that jointly learning 'natural' subtasks, in a multi-task learning setup, improves performance.Comment: To be published at ACL 201

Urban modelling as storytelling: using simulation models as a narrative

This article examines the distinctions between empirical and simulation models using the metaphors of argument and narrative. It argues that all argumentation is contextualized within a narrative that is either inferred or communicated. The paper provides another semantic structure for urban models that applies elements of systems- dynamic method to construct "stories" of the past and possible futures of communities in a watershed in southern Arizona. By constructing such narratives this paper demonstrates how computer-based urban models can "tell a story"

Mathematical conjecturing and proving

Most university courses in mathematics programs are characterized by a strong focus on the axiomatic nature of mathematics, and thus also on proof as the central scientific method of mathematics (Selden, A. & Selden, 2008). Lecturers write proofs on the blackboard, students attempt to demonstrate their understanding and skills by proving theorems on their own or in collaboration with others. However, there is often little systematic discussion in these courses on how new mathematical conjectures can be generated and on how proofs are constructed (Alcock, 2010). Students’ experiences with conjecturing and proving in schools or in university mathematics courses often lead them to “consider proof as a static product rather than a negotiated process that can help students justify and make sense of mathematical ideas” (Otten, Bleiler-Baxter, & Engledowl, 2017, p. 112). Yet, several authors (e.g., Epp, 2003; Savic, 2015a; Selden, A. & Selden, 2008) have hypothesized that often only little time can be devoted to illustrate students which strategies and processes may help to step through the proof construction process and to recover from proving impasses. Furthermore, the knowledge about what characterizes proof processes that lead to a successful outcome (i.e., an acceptable mathematical proof [according to local acceptance criteria]) is rare. To approach this issue, an extensive systematic literature search was conducted to summarize common claims and empirical findings about promising conjecturing and proving processes. 126 articles that focussed on conjecturing and proving were clustered using a topic modeling method. The algorithm identified 17 different topics. The most representative papers for each topic, in total 45 papers, were qualitatively analysed with regard to their research perspectives on which they were based and their claims and findings about the processes that are needed to successfully generate conjectures and construct proofs. This combination of statistical clustering and qualitative analyses allowed a systematic categorization of claims and empirical findings about successful conjecturing and proving processes in the literature. Based on this review, a set of characteristics of conjecturing and proving processes, that are assumed or reported to be crucial for success, is proposed. For the further analysis of such process characteristics, we started from a model differentiating students’ prerequisites they bring to bear on the proving situation, the conjecturing and proving processes they engage in, and the quality of the resulting product. The main question of the empirical work in this dissertation was, which process characteristics influence the quality of the final product (the formulated conjecture and constructed proof), and in which way they mediate the impact of students’ prerequisites on this product. Specifically, we distinguished between individual-mathematical and social-discursive process characteristics of conjecturing and proving. These process characteristics were extracted from prior research in mathematics education or in educational psychology or in the Learning Sciences. The central aim of this dissertation was to develop an instrument for assessing (prospective undergraduate) mathematics students’ conjecturing and proving processes in collaborative situations. A high-inference rating scheme with seven scales, based on theoretical considerations and on rating guidelines adapted from educational research was designed. The rating scheme was evaluated in a study with N=98 prospective undergraduate students working in dyads on an open-ended conjecturing and proving task. The results of the empirical study with regard to the basic analyses showed that collaborative conjecturing and proving processes could be rated with sufficient reliability and that the structure of the data corresponded to the underlying theoretical assumption that two dimensions, one related to individual-mathematical and one related to social-discursive process characteristics can be distinguished. The in-depth analyses pointed out that individual-mathematical process characteristics were predictive for the quality of the resulting product and mediated the relation between prerequisites (students’ prior knowledge on proof) and the quality of the product. In this way, the dissertation contributes to the scientific debate on how to assess (mathematical argumentation) skills (e.g., Blömeke, Gustafsson, & Shavelson, 2015; Koeppen, Hartig, Klieme, & Leutner, 2008) and provides theoretical and empirical insights on individual-mathematical and social-discursive process characteristics that describe the quality of collaborative conjecturing and proving processes

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)

Conceptualizing and supporting awareness of collaborative argumentation

In this thesis, we introduce “Argue(a)ware”. This is a concept for an instructional group awareness tool which aims at supporting social interactions in co-located computer-supported collaborative argumentation settings. Argue(a)ware is designed to support the social interactions in the content (i.e., task-related) and in the relational (i.e., social and interpersonal) space of co-located collaborative argumentation (Barron, 2003). The support for social interactions in the content space of collaboration is facilitated with the use of collaborative scripts for argumentation (i.e., instructions and scaffolds of argument construction) as well with the use of an argument mapping tool (i.e., visualization of argumentation outcomes in a form of diagrams) (Stegmann, Weinberger, & Fischer, 2007; van Gelder, 2013). The support for social interactions in the relational space of collaboration is facilitated with the use of different awareness mechanisms from the CSCL and the CSCW research fields (i.e., monitoring, mirroring and awareness notification tools). In this thesis, we examined how different awareness mechanisms facilitate the regulation of collaborative processes in the relational space of collaborative argumentation. Moreover, we studied how they affect the perceived team effectiveness (i.e., process outcome) and group performance (i.e., learning outcome) in the content space of collaboration. Thereby, we studied also the effects of the design of the awareness mechanisms on the application of the mechanisms and the user experience with them. In line with the design-based research paradigm, we attempted to simultaneously improve and study the effect of Argue(a)ware on collaborative argumentation (Herrington, McKenney, Reeves & Oliver, 2007). Through a series of design-based research studies we tested and refined the prototypes of the instructional group awareness tool. Moreover, we studied the ecological validity of dominant awareness and instructional theories in the context of co-located computer-supported collaborative argumentation. The underlying premise of the Argue(a)ware tool is that a combination of awareness and instructional support will result in increased awareness of collaboration, which will, in turn, mediate the regulation of collaborative processes. Moreover, we assume that successful regulation of collaboration will result in high perceived team effectiveness and the group performance in turn. In the first phase of development of the Argue(a)ware tool, we built support of the content space of collaborative argumentation with argument scaffold elements in a pedagogical face-to-face macro-script and an argument mapping tool. Furthermore, we extended the use of the script for supporting the relational space of collaboration by embedding awareness prompts for reflecting on collaboration during regular breaks in the script. Following, we designed two variations of the same pedagogical face-to-face macro-script which differ with respect to the type of group awareness prompts they used for supporting the relational space of collaboration i.e. behavioral and social. Upon designing the two script variations, we conducted a longitudinal, multiple-case study with ten groups of Media Informatics master students (n = 28, in groups of three or two, group=case, 4 sessions x70 min, Behavioural Awareness Script group= 5, Social Awareness Script group =5.) where each group was conceptualized as a case. Students collaborated every time for arguing to solve one different ill-structured problem and for transferring their arguments in the argument mapping tool Rationale. Thereby, we intended to investigate the effects of different awareness prompts on (a) collaborative metacognitive processes i.e., regulation, reflection, and evaluation (b) the relation between collaborative metacognitive processes and the quality of collaborative argumentation as well as (c) the impact of the two script variations on perceived team effectiveness and (d) what was experience with the different parts of the script variations in the two groups and how this fits into the design framework by Buder (2011). The quantitative analysis of argument outcomes from the groups yield no significant difference between the groups that worked with the BAS and the SAS variations. No significant difference between the script variations with respect to the results from the team effectiveness questionnaires was found either. Prompts for regulating collaboration processes were found to be the most successfully and consistently applied ones, especially in the most successful cases from both script variations and have influenced the argumentation outcomes. The awareness prompts afforded an explicit feedback display format (e.g. assessment of participation levels of self- and others) through discussion (Buder, 2011). The prompted explicit feedback display format (i.e., ratings of one’s self and of others) was criticized for running only on subjective awareness information on participation, contribution efforts and performance in the role. This resulted in evaluation apprehension phenomena (Cottrell, 1972) and evaluation bias (i.e., users may have not assessed themselves or others frankly) (Ghadirian et al., 2016). The awareness prompts for reflection and evaluation did reveal frictions in the plan making process (i.e., dropping out of the plan for collaboration) in the least successful groups. Problems with group dynamics (i.e., free-loading and presence of dominance) but were not powerful enough to trigger the desired changes in the behaviors of the students. The prompts for evaluating the collaboration in both script variations had no apparent connection to argumentation outcomes. The results indicated that dominant presence phenomena inhibited substantive argumentation in the least successful groups. They also indicated that the role-assignment influenced the group dynamics by helping student’s making clear the labor division in the group. In the second phase of development of the Argue(a)ware tool, the focus is on structuring and regulating social interactions in the relational space of collaborative argumentation by means of scripted roles and role-based awareness scaffolds. We designed support for mirroring participation in the role (i.e., a role-based awareness visualization) and support for monitoring participation, coordination and collaboration efforts in the role (i.e., self-assessment questionnaire). Moreover, we designed additional support for guiding participation in the role i.e., role-based reminders as notifications on smartwatches. In a between-subjects study, ten groups of three university students each (n = 30, Mage =22y, mixed educational backgrounds, 1x90min) worked with two variants of the Argue(a)ware for arguing to solve one ill-structured problem and transferring their arguments in the argument mapping tool Rationale. Next, to that, students should monitor their progress in their role with the role-based awareness visualization and the self-assessment questionnaire with the basic awareness support (role-based awareness visualization with the intermediate self-assessment) and the enhanced awareness support (additional role-based awareness reminders). Half of the groups worked only with the role-based awareness visualization and the self-assessment questionnaire (Basic Awareness Condition-BAC) while the other half groups received additional text-based awareness notifications via smartwatches that were sent to students privately (Enhanced Awareness Condition- EAC). Thereby, we tested the use of different degrees of awareness support in the two conditions with respect to their impact on a) self-perceived awareness of performance in the role and of collaboration and coordination efforts (measured with the same questionnaire at two time points), b) on perceive team effectiveness, c) group performance. We hypothesized that students in EAC will perform better thanks to the additional awareness reminders that increased the directivity and influenced their awareness in the role. The mixed methods analysis revealed that the awareness reminders, when perceived on time, succeeded in guiding collaboration (i.e., resulted in more role-specific behaviors). Students in the EAC condition improved their awareness over time (between the two measurements). These results indicated that enhanced awareness support in the form of additional guidance through awareness reminders can boost the awareness of students’ performance in the role as well as the awareness of their coordination and collaboration efforts over time by directing them back to the mirroring and monitoring tools. Moreover, students in EAC exhibited higher perceived team effectiveness than the students in BAC. However, no significant differences in building of shared mental models or performing in mutual performance monitoring were found between the groups. However, students in BAC and EAC did not differ significantly with respect to the formal correctness or evidence sufficiency of their group argumentation outcomes. Moreover, technical difficulties with the smartphones used as delivery devices for the awareness reminders (i.e., low vibration modus) hindered the timely perception of the reminders and thus their effect on participation. Finally, the questionnaire on the experience with the different parts of Argue(a)ware system indicated the need for exploring further media for supporting the awareness reminders to avoid the overwhelming effects of the multiple displays of the system and enhancing higher perceptiveness of the reminders with low interruption costs for other group members. The rather high satisfaction with the use of the role-based awareness visualization and the positive comments on the motivating aspects of monitoring how the personal success contributes to the group performance indicate that the group mirror succeeded in making group norms visible to group members in a non-obtrusive way. The high interpersonal comparability of performances without moderating the group ‘s interaction directly in the basic awareness condition was proven to be the favored design approach compared to the combination of group mirror and awareness reminders in the enhance awareness condition. In the third phase of development of Argue(a)ware, we focused on designing and testing different notification modes on different ubiquitous mobile devices for facilitating the next prototype of a notification system for role-based awareness reminders. Thereby, the aim of the system was again to guide students’ active participation in collaborative argumentation. More specifically, we focused on raising students’ attention to the reminders and triggering a prompter reaction to the contents of the reminders whilst avoiding a high interruption cost for the primary task (i.e., arguing for solving the problem at hand) in the group. These goals were translated into design challenges for the design of the role-based awareness notification system. The system should afford low interruptions, high reaction and high comprehension of notifications. Notification systems with this particular configuration of IRC values are known as "secondary display" systems (McCrickard et al., 2003). Next, we designed three low-fidelity prototypes for a role-based notification system for delivering awareness reminders: The first ran on a smartwatch and afforded text-based information with vibration and light notification modalities. The second ran on smartphone and afforded text-based information with vibrotactile and light-based notification modalities. Finally, the third prototype run on a smart-ring which afforded graphical- based (i.e. abstract light) information with and light and vibration notification modalities. To test the suitability of these prototypes for acting as “secondary display” systems, we conducted a within-subjects user study where three university students (n= 3, Mage=28, mixed educational background) argued for solving three different problem cases and producing an argument map in each of the three consecutive meetings (max 90min) in the Argue(a)ware instructional system. Students were assigned the roles of writer, corrector and devil`s advocate and were instructed to maintain the same role across the three meetings. In each meeting, students worked with a different role-based awareness notification prototype, where they received a notification indicating their balloon is not growing bigger after five minutes of not exhibiting any role-specific behaviors. The role-based awareness notification prototypes aimed at introducing timely interventions which would prompt students to check on their own progress in the role and the group progress as visualized by the role-based awareness visualization on the large display. Ultimately, this should prompt them to reflect on the awareness information from the visualization and adapt their behaviors to the desired behavior standards over time. Results showed that students perceived the notifications from all media mostly based on vibration cues. Thereby, the vibration cues on the wrist (smartwatch) were considered the least disruptive to the main task compared to the vibration cues on finger (smartwatch) and the vibration cues on the desk (smartphone). Students also declared that vibration cues on wrist prompted the fastest reaction i.e., attending to notification by interacting with the smartwatch. These results indicate that vibration cues on the wrist can be a suitable notification mechanism for increasing the perceived urgency of the message and prompting the reaction on it without causing great distraction to the main task, as studies previous studies showed before (Pielot, Church, & deOliveira, 2013; Hernández-Leo, Balestrini, Nieves & Blat, 2012). Based on very limited qualitative data on light as notification modality and awareness representation type no inferences could be made about its influence on the cost of interruption, reaction and comprehension parameters comprehensiveness. The qualitative and quantitative data on the experience with different media as awareness notification systems indicate that smartwatches may be the most suitable medium for acting as awareness notification medium with a “secondary display” IRC configuration (low-high-high). However, this inference needs to be tested in terms of a follow up study. In the next study, the great limitations of study (limited data due to low power and mal-structured measurement instruments) need to be repaired. Finally, the focus should be on comparing notification modalities of one medium (e.g., smartphone) based on a larger set of participants and with the use of objective measurements for the IRC parameter values (Chewar, McCrickard & Sutcliffe, 2004). Finally, we draw conclusions based on the findings from the three studies with respect to the role of awareness mechanisms for facilitating collaborative processes and outcomes and provide replicable and generalizable design principles. These principles are formed as heuristic statements and are subject to refinement by further research (Bell, Hoadley, & Linn, 2004; Van den Akker, 1999). We conclude with the limitations of the study and ideas for future work with Argue(a)ware