Series, held Thursday through Saturday, November 5-7, at he Association for the Advancement of Artificial Intelligence the Westin Arlington Gateway in Arlington, Virginia. The titles of the seven symposia were as follows: (1) Biologically Inspired Cognitive Biologically Inspired Cognitive Architectures Architectures, (2) Cognitive and Metacognitive Cognitive and Metacognitive Educational Systems Educational Systems, (3) Complex Adaptive Complex Adaptive Systems and the Threshold Effect: Views from the Natural Systems and the Threshold Effect: Views and Social Sciences from the Natural and Social Sciences, (4) Manifold Manifold Learning and Its Applications Learning and Its Applications, (5) Multirepresentational Architectures for Human-Level Multirepresentational Architectures for Human-Level Intelligence Intelligence, (6) The Uses of Computational The Uses of Computational Argumentation Argumentation, and (7) Virtual Healthcare Virtual Healthcare Interaction Interaction. An informal reception was held on Thursday, November 5. A general plenary session, in which the highlights of each symposium were presented, was held on Friday, November 6. The challenge of creating a real-life computational equivalent of the human mind requires that we better understand at a computational level how natural intelligent systems develop their cognitive and learning functions. They will behave, variety of disjoined communities and schools of learn, communicate, and "think" as conscious thought that used to speak different languages and beings in general, in addition to being able to perform ignore each other.

Learning about complex and challenging science topics with advanced learning technologies requires students to regulate their learning. The deployment of key cognitive and metacognitive regulatory processes is key to enhancing learning in open-ended learning environments such as hypermedia. In this paper, we propose a metaphor—Computers as MetaCognitive tools—to characterize the complex nature of the learning context, self- regulatory processes, task conditions, and features of advanced learning technologies. We briefly outline the theoretical and conceptual assumptions of self-regulated learning (SRL) underlying MetaTutor, a hypermedia environment designed to train and foster students’ SRL processes in biology. Lastly, we provide preliminary learning outcome and SRL process data on the deployment of SRL processes during learning with MetaTutor.

The goal of this paper is to present four key assumptions regarding the measurement of cognitive and metacognitive regulatory processes used during learning with hypermedia. First, we assume it is possible to detect, trace, model, and foster SRL processes during learning with hypermedia. Second, understanding the complex nature of the regulatory processes during learning with hypermedia is critical in determining why certain processes are used throughout a learning task. Third, it is assumed that the use of SRL processes can dynamically change over time and that they are cyclical in nature (influenced by internal and external conditions and feedback mechanisms). Fourth, capturing, identifying, and classifying SRL processes used during learning with hypermedia is a rather challenging task.

Unfortunately, many students stop using these beneficial learning practices as soon Presented by Stephen Grossberg, Department of Cognitive as the metatutoring ceases. Apparently, the metatutors were and Neural Systems, Center for Adaptive Systems, and Center nagging rather than convincing. This talk will present a of Excellence for Learning in Education, Science, and study of Pyrenees, a metatutor that coaches students to focus Technology, Boston University, Boston, MA 02215 on learning domain principles rather than solutions to A deep and rational understanding of the factors that influence examples. It was convincing, in that students who were effective education and learning technologies depends taught probability with Pyrenees used principle-based problem on a corresponding understanding of how the brain in health solving on post-test more so than students taught by Andes, and disease controls learned behaviors. There has been a which did not focus students on principles. Moreover, revolution in discovering new computational paradigms, organizational when all students were transferred to Andes for learning principles, mechanisms, and models of how of physics, those who were metatutored used the principlefocused learning processes enable brains to give rise to minds.

This paper presents GnuTutor, an open source intelligent tutoring system (ITS) inspired by the AutoTutor ITS. The goal of GnuTutor is to create a freely available, open source ITS platform that can be used by schools and researchers alike. To achieve this goal, significant departures from AutoTutor's current design were made so that GnuTutor would use a smaller, non-proprietary code base but have the major functionality of AutoTutor, including mixed-initiative dialogue, an animated agent, speech act classification, and natural language understanding using latent semantic analysis. This paper describes the GnuTutor system, its components, and the major differences between GnuTutor and AutoTutor.

Students must be able to competently compose essays in order to succeed in school and progress into the workplace. Current intelligent tutoring systems (ITS) attempt to provide individual training that is lacking in the current educational system. To provide efficient individual training through ITS, the systems must be able to effectively assess writing input from students. Necessary components for computer-based writing tutors are algorithms that mimic human judgments of writing. The current study attempts to establish a connection between paragraph position and human ratings of paragraph type through the use of computational measures provided by Coh-Metrix. We find that expert raters do not easily identify paragraph type and ratings of paragraph type do not map onto paragraph position.

In this paper we propose a novel approach to the task of paraphrase identification. The proposed approach quantifies both the similarity and dissimilarity between two sentences. The similarity and dissimilarity is assessed based on lexico-semantic information, i.e., word semantics, and syntactic information in the form of dependencies, which are explicit syntactic relations between words in a sentence. Word semantics requires mapping words onto concepts in a taxonomy and then using word-to-word similarity metrics to compute their semantic relatedness. Dependencies are obtained using state-of-the-art dependency parsers. One important aspect of our approach is the weighting of missing dependencies, i.e., syntactic relations present in one sentence but not the other. We report experimental results on the Microsoft Paraphrase Corpus, a standard data set for evaluating approaches to paraphrase identification. The experiments showed that the proposed approach offers state-of-the-art results. In particular, our approach offers better precision when compared to other state-of-the-art systems.

Using the already validated Coh-Metrix tool, this study examines whether there are significant linguistic and discourse differences between biomedical abstracts for American and Korean English. Also, the current study accounts for variation among journals’ countries of origin, distinguishing between biomedical journals published in the United States from biomedical journals published in South Korea. The significance of these studies regards the growing number of second language (L2) biomedical researchers attempting to publish their research in national and international English-language journals, but who find themselves locked out of the discussion because of differences in linguistic and discourse conventions. The present study aims to provide a more thorough and quantitative understanding of the prototypical linguistic components in biomedical rhetoric, and to suggest how word-, sentence-, and discourse-level structures can be researched, taught, and developed into materials. This improved understanding is expected to provide a powerful apparatus for the promotion of L2 English writers in the biomedical field.