Discourse markers in diplomatic setting: Ministerial dialogue between Australia and Indonesia

This descriptive research discusses the use of discourse markers in a diplomatic setting between the governments of Indonesia and Australia during a Joint Press Conference between Indonesia-Australia Foreign and Defence Ministers. The particular aims of this research are to identify and analyze forms of discourse markers employed by the representatives of each government and describe the most frequent discourse markers used by these representatives. The data were collected from the transcript of the Joint Press Conference between Indonesia and Australia Foreign and Defence Ministers (2+2) Dialogue. The data are classified based on the typology of discourse markers and analyzed to identify their function within the diplomatic discourse. The data are input into the AntConc corpus analysis toolkit for analysis. The results show that the Foreign and Defence Ministers of Indonesia employed three forms of discourse markers, namely textual discourse marker, interpersonal discourse marker, and cognitive discourse marker, whereas the Foreign and Defence Ministers of Australia only applied textual discourse marker and cognitive discourse marker. Both representatives employed textual discourse markers more frequently than other forms of discourse markers. Discourse markers partially control how meaning is constructed by showing turns between speakers, joining concepts, displaying attitude, and finally, controlling communication. By understanding the discourse markers in ministerial dialogues, spectators can learn to find clues in the change of direction in their talks to better understand the conversation that affects the policies and citizens of both countries involved

Reporting Verbs in Applied Linguistics Research Articles by Native and Non-native Writers

This study investigated the differences between applied linguistics research articles written by non-native writers and their native counterparts in English, focusing on the use of reporting verbs in quoting other authors. The corpus consisted of 63 articles (about 200000 words) written by native and non-native writers of English published in three scholarly journals in the fields of language teaching and applied linguistics. The results showed significant differences in the choices writers made in using reporting verbs. The corpus was also analyzed to determine the degree to which writers quoted different authors directly or indirectly. The number of verbs were tallied and recorded and then classified on the basis of Thompson and Ye’s (1991) classification. Finally, the results of the analysis of reporting verbs used by native and non-native writers were compared. The findings showed higher use of direct quotations by native writers which might be interpreted to be the result of their linguistic capability in handling linguistic materials produced by other authors

Sculptors, architects, and painters conceive of depicted spaces differently

Sculptors, architects, and painters are three professional groups that require a comprehensive understanding of how to manipulate spatial structures. While it has been speculated that they may differ in the way they conceive of space due to the different professional demands, this has not been empirically tested. To achieve this, we asked architects, painters, sculptors, and a control group questions about spatially complex pictures. Verbalizations elicited were examined using cognitive discourse analysis. We found significant differences between each group. Only painters shifted consistently between 2D and 3D concepts, architects were concerned with paths and spatial physical boundedness, and sculptors produced responses that fell between architects and painters. All three differed from controls, whose verbalizations were generally less elaborate and detailed. Thus, for the case of sculptors, architects, and painters, profession appears to relate to a different spatial conceptualization manifested through a systematically contrasting way of talking about space

Cognitive Discourse Analysis: accessing cognitive representations and processes through language data

abstractThis paper offers the first general introduction to CODA (Cognitive Discourse Analysis), a methodology for analyzing verbal protocols and other types of unconstrained language use, as a resource for researchers interested in mental representations and high-level cognitive processes. CODA can be used to investigate verbalizations of perceived scenes and events, spatio-temporal concepts, complex cognitive processes such as problem-solving and cognitive strategies and heuristics, and other concepts that are accessible for verbalization. CODA builds on and extends relevant established methodologies such as cognitive linguistic perspectives, verbal protocol analysis in cognitive psychology and interdisciplinary content analysis, linguistic discourse analysis, and psycholinguistic experimentation.</jats:p

Regular geometry towards effective visitors wayfinding: a case study of KLCC vicinity

In developed cities, large office buildings occupy the city centre thereby destroying the legibility of these areas. These areas confront with a lack of visibility and difficult cognitive map. As a regular spatial configuration, Squares have had an effect on the characteristics of urban space such as intelligibility, synergy and accessibility. The goal of this study is to identify the importance of geometry of space on legibility, cognitive map of visitors and wayfinding. Kuala Lumpur City Centre (KLCC) was chosen as a case study because of its historical and cultural significance. Importance should be placed on its preservation for the future especially for tourists. A model of KLCC has been developed within the square that combines streets and KLCC area. It has been used as proof of the concept for a Space Syntax model network analysis using axial analysis and observations. Meanwhile, this study investigates the views of visitors including 86 respondents using surveys and interviews. Results show that there is a negative correlation between cognitive map and urban stress. Furthermore, all quantitative and qualitative data suggest viable cognitive map due to applying regular geometry may strongly improve legibility. The results show that there was a moderate positive correlation between legibility and regular geometry in general. On the other hand, existing geometry had a negligible effect on legibility. The role of the square suggestion is more immediate in high integration in the vicinity of KLCC. Moreover, the square can provide context for PETRONAS Twin Tower as landmark and symbolic building. Square as regular geometry is a good way to increase viable cognitive map. It affects the legibility of urban space where wayfinding will more strongly confirm that visitors display sociability and accessibility interaction. An implication for architects, tourism managers and urban designers is that square as a regular geometry associated with landmarks increases legibility. As a result, viable cognitive map by regular geometry is associated with easy wayfinding which decreases stress

Embodied interaction with visualization and spatial navigation in time-sensitive scenarios

Paraphrasing the theory of embodied cognition, all aspects of our cognition are determined primarily by the contextual information and the means of physical interaction with data and information. In hybrid human-machine systems involving complex decision making, continuously maintaining a high level of attention while employing a deep understanding concerning the task performed as well as its context are essential. Utilizing embodied interaction to interact with machines has the potential to promote thinking and learning according to the theory of embodied cognition proposed by Lakoff. Additionally, the hybrid human-machine system utilizing natural and intuitive communication channels (e.g., gestures, speech, and body stances) should afford an array of cognitive benefits outstripping the more static forms of interaction (e.g., computer keyboard). This research proposes such a computational framework based on a Bayesian approach; this framework infers operator\u27s focus of attention based on the physical expressions of the operators. Specifically, this work aims to assess the effect of embodied interaction on attention during the solution of complex, time-sensitive, spatial navigational problems. Toward the goal of assessing the level of operator\u27s attention, we present a method linking the operator\u27s interaction utility, inference, and reasoning. The level of attention was inferred through networks coined Bayesian Attentional Networks (BANs). BANs are structures describing cause-effect relationships between operator\u27s attention, physical actions and decision-making. The proposed framework also generated a representative BAN, called the Consensus (Majority) Model (CMM); the CMM consists of an iteratively derived and agreed graph among candidate BANs obtained by experts and by the automatic learning process. Finally, the best combinations of interaction modalities and feedback were determined by the use of particular utility functions. This methodology was applied to a spatial navigational scenario; wherein, the operators interacted with dynamic images through a series of decision making processes. Real-world experiments were conducted to assess the framework\u27s ability to infer the operator\u27s levels of attention. Users were instructed to complete a series of spatial-navigational tasks using an assigned pairing of an interaction modality out of five categories (vision-based gesture, glove-based gesture, speech, feet, or body balance) and a feedback modality out of two (visual-based or auditory-based). Experimental results have confirmed that physical expressions are a determining factor in the quality of the solutions in a spatial navigational problem. Moreover, it was found that the combination of foot gestures with visual feedback resulted in the best task performance (p\u3c .001). Results have also shown that embodied interaction-based multimodal interface decreased execution errors that occurred in the cyber-physical scenarios (p \u3c .001). Therefore we conclude that appropriate use of interaction and feedback modalities allows the operators maintain their focus of attention, reduce errors, and enhance task performance in solving the decision making problems

Proceedings of the KI 2009 Workshop on Complex Cognition

The KI ´09 workshop on Complex Cognition was a joint venture of the Cognition group of the Special Interest Group Artificial Intelligence of the German Computer Science Society (Gesellschaft für Informatik) and the German Cognitive Science Association. Dealing with complexity has become one of the great challenges for modern information societies. To reason and decide, plan and act in complex domains is no longer limited to highly specialized professionals in restricted areas such as medical diagnosis, controlling technical processes, or serious game playing. Complexity has reached everyday life and affects people in such mundane activities as buying a train ticket, investing money, or connecting a home desktop to the internet. Research in cognitive AI can contribute to supporting people navigating through the jungle of everyday reasoning, decision making, planning and acting by providing intelligent support technology. Lessons learned from expert systems research of the nineteen-eighties show that the aim should not be to provide for fully automated systems which can solve specialized tasks autonomously but instead to develop interactive assistant systems where user and system work together by taking advantage of the respective strengths of human and machine. To accomplish a smooth collaboration between humans and intelligent systems, basic research in cognition is a necessary precondition. Insights into cognitive structures and processes underlying successful human reasoning and planning can provide suggestions for algorithm design. Even more important, insights into restrictions and typical errors and misconceptions of the cognitive systems provide information about those parts of a complex task from which the human should be relieved. For successful human-computer interaction in complex domains it has, furthermore, to be decided which information should be presented when, in what way, to the user. We strongly believe that symbolic approaches of AI and psychological research of higher cognition are at the core of success for the endeavor to create intelligent assistant system for complex domains. While insight into the neurological processes of the brain and into the realization of basic processes of perception, attention and senso-motoric coordination are important for the basic understanding of the principles of human intelligence, these processes have a much too fine granularity for the design and realization of interactive systems which must communicate with the user on knowledge level. If human system users are not to be incapacitated by a system, system decisions must be transparent for the user and the system must be able to provide explanations for the reasons of its proposals and recommendations. Therefore, even when some of the underlying algorithms are based on statistical or neuronal approaches, the top-level of such systems must be symbolical and rule-based. The papers presented at this workshop on complex cognition give an inspiring and promising overview of current work in the field which can provide first building stones for our endeavor to create knowledge level intelligent assistant systems for complex domains. The topics cover modelling basic cognitive processes, interfacing subsymbolic and symbolic representations, dealing with continuous time, Bayesian identification of problem solving strategies, linguistically inspired methods for assessing complex cognitive processes and complex domains such as recognition of sketches, predicting changes in stocks, spatial information processing, and coping with critical situations

Linguistic Representation of Problem Solving Processes in Unaided Object Assembly

This thesis investigates the linguistic representation of problem solving processes in data recorded during unaided object assembly. It combines traditional approaches of analyzing verbal protocols with the recent approach of Cognitive Discourse Analysis