Cognitive Model

Cognitive agent programming frameworks facilitate the development of intelligent virtual agents. By adding a computational model of emotion to such a framework, one can program agents capable of using and reasoning over emotions. Computational models of emotion are generally based on cognitive appraisal theory; however, these theories introduce a large set of appraisal processes, which are not specified in enough detail for unambiguous implementation in cognitive agent programming frameworks. We present CAAF (Cognitive Affective Agent programming Framework), a framework based on the belief-desire theory of emotions (BDTE), that enables the computation of emotions for cognitive agents (i.e., making them cognitive affective agents). In this paper we bridge the remaining gap between BDTE and cognitive agent programming frameworks. We conclude that CAAF models consistent, domain independent emotions for cognitive agent programming.

This paper describes a computational cognitive model of human language processing under development in the ACT-R cognitive architecture. The paper begins with the context for the research, followed by a discussion of the primary theoretical and modeling commitments. The main theoretical commitment is to develop a language model which is at once functional and cognitively plausible. The paper continues with a description of the word recognition subcomponent of the language model which uses a perceptual span and ACT-R"s spreading activation mechanism to activate and select the lexical unit that most closely matches the perceptual input. Next we present a description of the linguistic structure building component of the model which combines parallel, probabilistic processing with serial, pseudodeterministic processing, including a non-monotonic context accommodation mechanism. A description of the mapping of linguistic representations into a situation model, follows. The paper concludes with a summary and conclusions.

The aim of this work has been to explore the use of video conferencing technology to expand the peer network for students who use communication aids. Evidence indicates that users of communication aids often have a different mix of communication partners to their speaking peers (Reinhart, 2005) and that their partners tend to be skewed towards adults . This project is considering whether video conferencing can aid users of communication aids in meeting and getting to know peers (both speaking and non speaking) and lead to a change in the balance of their communication partners. This project is still at an early stage and the work presented here describes the initial sessions and the outcomes. Networking sessions were performed as an activity within school time and linked students at four schools via a video conferencing tool (Skype). Feedback from students and staff was collected following these sessions and and indicated that students enjoyed the experience and liked meeting students from other schools. The results of these sessions have suggested that video conferencing could be a useful tool in expanding peer networks for users of communication aids and currently a research project is being planned to more formally evaluate the effects of the use of this tool.

To those brought up in a logic-based tradition there seems to be a simple and clear definition of proof. But this is largely a 20 th century invention; many earlier proofs had a different nature. We will look particularly at the faulty proof of Euler's Theorem and Lakatos' rational reconstruction of the history of this proof. We will ask: how is it possible for the errors in a faulty proof to remain undetected for several years -even when counter-examples to it are known? How is it possible to have a proof about concepts that are only partially defined? And can we give a logicbased account of such phenomena? We introduce the concept of schematic proofs and argue that they offer a possible cognitive model for the human construction of proofs in mathematics. In particular, we show how they can account for persistent errors in proofs.

present a social cognitive model of self-regulated writing. We offer four caveats concerning Zimmerman's and Risemberg's model. First, self-regulation is a field containing multiple theoretical perspectives, and descriptions considerably different from the one offered by Zimmerman and Risemberg can be constructed. Second, self-regulation may play a more modest role in writing than commonly assumed. Third, a high level of self-regulation is a necessary but not sufficient condition to become an expert writer, but the development of a moderate to high degree of self-regulation may be enough to become a competent writer. Fourth, the effects of self-regulation are not always positive. Areas in need of future research are also examined and methods for promoting self-regulatory behaviors in writing are identified. ᭧ 1997 Academic Press Writing is commonly viewed as a difficult and demanding task, requiring extensive self-regulation and attentional control (Kellogg, 1996; McCutchen, in press). As Flower and Hayes (1980) noted, ''a great part of the skill in writing'' involves the ability to exert deliberate control over the process of composing (p. 39). Not surprisingly, the role of self-regulation in writing is acknowledged, either explicitly or implicitly, in most current models of composing (see Hayes, 1996;, and constructs such as the writing ''monitor'' and executive control are used to account for the self-regulation and volitional processes that occur during writing. Many of the details and implications of self-regulation, however, are not fully specified in current models of writing, including descriptions of key processes, the source of motivation to self-regulate when writing, and factors that nurture or inhibit the development of self-regulated writing. Zimmerman and Risemberg (1997) rectify this situation, at least in part, by providing a more fully developed theoretical description of self-regulated writing. Zimmerman's and Risemberg's (1997) primary tenet is that skilled writing depends on high levels of self-regulation because writing is typically an intentional and self-initiated and self-sustained activity. To bolster this claim, they present anecdotal evidence, showing that professional writers use a variety of strategies to regulate the environment, their behavior, or covert processes when writing. A second (although unstated) implication is that the development of self-regulation in writing is an important instructional goal,

An ecological-cognitive fimnework of analysis and a modeltracing amhitecture are presented and used in the analysis cf data recorded flom users browsing a large document collection. The usem interacted with the Scatter/Gather browser, which clusters documents into groups of similar content and presents users with summaries of cluster content. Predictions made by a computational model d navigation and information foraging are matched against the observed activity.

In this chapter, we describe our research and development efforts relating to eliciting, representing, and analyzing how individuals and small groups conceptualize complex problems. The methods described herein have all been developed and are in various states of being validated. In addition, the methods we describe have been automated and most have been integrated in an online modelbased set of tools called HIMATT (Highly Interactive Model-based Assessment Tools and Technologies; available for research purposes at freiburg.de/cgi-bin/hrun/himatt.pl and soon to be available on a server at Florida State University). HIMATT continues to expand in terms of the tools and technologies included. Our methods and tools represent an approach to learning and instruction that is now embedded in many of the graduate courses at Florida State University and also at the University of Freiburg. We call our approach model-based because it integrates representations of mental models and internal cognitive processes with tools that are used to (a) assess progress of learning, and (b) provide the basis for informative and reflective feedback during instruction. Belief networks • Causal diagrams • Cognitive modeling • Concept mapping • Mental models • Model-based assessment • Technology-based assessment This quote by John Dewey nearly 100 years ago is particularly relevant now. That is, in our increasingly technological society, understanding the ebb and flow of

A thesis submitted to the Faculty of Humanities, University of Witwatersrand, Johannesburg, in fulfilment of the requirements for the degree of Master of Arts Clinical Psychology. important determinants of women's HIV risk. This research aims to explore adolescent girls' understanding of their identity and heterosexual sexuality. In addition, this study intends to assess the implications that gendered powered relations held for understanding the risks and dilemmas that young women are confronted with in relation to HIV/AIDS contraction. This research presents the findings of a qualitative and quantitative study conducted using a self-constructed questionnaire that was administered to a purposive sample of adolescent girls aged 13-18. Content analysis is used to analyse the data, the aim being to extract themes as they emerged from the data. Some of the following themes were identified as significant in the girls' responses: The physical changes that occur during adolescence were highlighted alongside the viewpoint that adolescence is a time of inconsistency and turmoil. Self-worth was closely linked and related to socially desirable characteristics, and in addition gendered behaviour was widely endorsed amongst these girls. Romantic relationships were an important component of these girls' lives. However, many described their relationships as being less sexual and more emotional in nature. The awareness of sexual readiness and choice hold positive implications for HIV/AIDS. A common consensus existed regarding practicing safe sex and almost all respondents agreed that the onset of sexual intercourse should be postponed until the age of 18 years or older. It appeared that although adhering to feminine stereotyped behaviour could be protective in the sense that it may result in less risky sexual engagement, it however, was also apparent that it could render females less powerful within their heterosexual relationships, thereby increasing their vulnerability to HIV infection. Although only a small proportion of the respondents experienced being forced into a sexual encounter against their will, an underlying fear of sexual coercion or threat nevertheless, emerged. It is concluded that sex education should engage with gender-stereotyped behaviour especially during early and middle adolescence when identities are being formed and developed. The following is an outline of the structure of this research report: Chapter two follows this introduction and provides a review of the related literature concerning adolescent heterosexual romantic relationships. It reviews the factors that put young girls at risk of contracting HIV within the context of their romantic relationships. It identifies the extent of the HIV/AIDS epidemic both internationally and in South Africa, with a particular focus on South African adolescents. The issues of identity development, sexual development, dating and conflict resolution are addressed. It then focuses on the dynamics of coercive sexual practices that may occur in the context of heterosexual relationships. Chapter three presents the methodology of the present study. It begins by discussing the research approach and then goes on to outline the procedure and instruments used, and the data collection method. This is followed by a description of how the data was analysed and is concluded by a discussion of the ethical considerations of this research. Chapter four focuses on the analysis and discussion of the data. Some of the research findings are supported by tables. A discursive commentary is also offered as pertaining to the findings. Finally an overview of the findings is presented; and the different strands of this and the discussion are brought together. Chapter five is the concluding section of the research report. Here, the study is critically evaluated, implications and recommendations are discussed, and finally suggestions for future research are highlighted.

Background and Objectives: There are two lines of research examining the role of cognition in depression. One line of research focuses on risk for depression, and shows that a negative cognitive style interacts with stressful life events to create depression. The second line of research focuses on recovery, and shows that an enhancing cognitive style interacts with positive life events to reduce depression. The goal of this study was to integrate these two areas and provide a more comprehensive test of the cognitive model of depression. Methods: A 4-week prospective longitudinal design was used to test the interaction between cognitive style (both negative and enhancing) and life events (both negative and positive) in a sample of undergraduates (n ¼ 128). Results: Cognitively vulnerable individuals were buffered from the depressive effects of stress if they also possessed an enhancing cognitive style or experienced high numbers of positive life events. Individuals with low levels of negative cognitive style and life stress, but high levels of enhancing cognitive style or positive life events were the most resilient to depressive symptoms. Limitations: Future research is needed to determine if the results of this study generalize to a more diverse sample as well as to clinically significant forms of depression. The results provide some of the first evidence for the protective role of enhancing cognitive style and positive live events among vulnerable individuals. These findings underscore the importance of examining a broader environmental context when investigating risk and resiliency to depression.

In this paper, an explanatory program understander that can analyse student solutions for programming assignments is described. The approach uses a number of reverse engineering techniques and is grounded on a cognitive model of procedural programming knowledge. It will be shown that, through the use of reverse engineering techniques, a lot of feedback (e.g. on errors) can be generated without having to use any prior knowledge on what the program is supposed to do. When such information is available, problem-specific feedback can also be generated. Furthermore, the use of the cognitive programming concepts allows one to specify the errors in an understandable way using exactly the same words and concepts as human programmers. This opens interesting possibilities for other uses of the proposed program understanding technique described in this article.

The DARWARS Tactical Language Training System (TLTS) helps learners acquire basic communicative skills in foreign languages and cultures. Learners practice their communication skills in a simulated village, where they must develop rapport with the local people, who in term will help them accomplish missions such as post-war reconstruction. Each learner is accompanied by a virtual aide who can provide assistance and guidance if needed, tailored to each learner's individual skills. The aide can also act as a virtual tutor as part of an intelligent tutoring system, giving the learner feedback on their performance. Learners communicate via a multimodal interface, which permits them to speak and choose gestures on behalf of their character in the simulation. The system employs video game technologies and design techniques, in order to motivate and engage learners. A version for Levantine Arabic has been developed, and versions for other languages are in the process of being developed. A first version is scheduled to be transitioned into use by US Special Forces in late 2004. The TLTS project has developed and integrated several advanced technologies, including speech recognition tailored for learner speech, motivational tutorial dialog, learner modeling, and multi-agent social simulations. The virtual aide in the game is implemented as a pedagogical agent, able to interact with learners at a motivational and social level as well as a cognitive level. Character behavior in the game is controlled by the Psychsim cognitive modeling system, that models the motivations of social agents. Multi-user authoring tools enable linguists, instructional designers, and simulation developers to collaborate in the specification and construction of lessons and simulations in multiple languages. The TLTS is part of the DARWARS Training Superiority program developing new technologies for military training.

Approach motivation consists of the active, engaged pursuit of one's goals. The purpose of the present three studies (N ϭ 258) was to examine whether approach motivation could be cognitively modeled, thereby providing process-based insights into personality functioning. Behavioral facilitation was assessed in terms of faster (or facilitated) reaction time with practice. As hypothesized, such tendencies predicted higher levels of approach motivation, higher levels of positive affect, and lower levels of depressive symptoms and did so across cognitive, behavioral, self-reported, and peer-reported outcomes. Tendencies toward behavioral facilitation, on the other hand, did not correlate with self-reported traits (Study 1) and did not predict avoidance motivation or negative affect (all studies). The results indicate a systematic relationship between behavioral facilitation in cognitive tasks and approach motivation in daily life. Results are discussed in terms of the benefits of modeling the cognitive processes hypothesized to underlie individual differences motivation, affect, and depression.

Despite the importance of cognitive control in many cognitive tasks involving uncertainty, the computational mechanisms of cognitive control in response to uncertainty remain unclear. In this study, we develop biologically realistic neural network models to investigate the instantiation of cognitive control in a majority function task, where one determines the category to which the majority of items in a group belong. Two models are constructed, both of which include the same set of modules representing task-relevant brain functions and share the same model structure. However, with a critical change of a model parameter setting, the two models implement two different underlying algorithms: one for grouping search (where a subgroup of items are sampled and re-sampled until a congruent sample is found) and the other for self-terminating search (where the items are scanned and counted one-by-one until the majority is decided). The two algorithms hold distinct implications for the involvement of cognitive control. The modeling results show that while both models are able to perform the task, the grouping search model fit the human data better than the self-terminating search model. An examination of the dynamics underlying model performance reveals how cognitive control might be instantiated in the brain for computing the majority function.

Ця стаття являє собою всебічний розгляд концепту ЕМПАТІЯ (лексикалізованого словом "емпатія") у сучасному англійському дискурсі. Мета дослідження подвійна: а) отримати розуміння того, як концепт ЕМПАТІЯ (як динамічна когнітивна модель) використовується мовцями, тобто осягнути його природу та характер; б) запропонувати теорію про самоорганізацію трьох концептуальних вимірів ЕМПАТІЇ: логічного, ідентифікаційного та структурного.Эта статья представляет собой всестороннее рассмотрение концепта ЭМПАТИЯ (лексикализированного словом "эмпатия") в современном английском дискурсе. Цель исследования двойная: а) получить понимание того, как концепт ЭМПАТИЯ (как динамическая когнитивная модель) используется говорящими, то есть постичь его природу и характер; б) предложить теорию о самоорганизации трех концептуальных измерений эмпатии: логического, идентификационного и структурного.This article encompasses a comprehensive consideration of the concept of EMPATHY (lexicalized by...

Recent neurocognitive studies of visual word recognition provide information about neuronal networks correlated with processes involved in lexical access and their time course (e.g., [Holcomb, Ph.J., Grainger J. and O'Rourke, T. ( ). An Electrophysiological Study of the Effects of Orthographic Neighborhood Size on Printed Word Perception, J. of

The automated negotiation topic plays an important role in e-commerce research. However, despite considerable work on automated negotiation, few research efforts have aimed at software engineering facilities such a reuse and flexibility. To address this issue, we propose a novel computation environment for building agents with flexible negotiation strategies to function in various virtual business domains. Regarding the negotiation strategies, some decision taking assistance techniques may be used in group, e.g. rule-based reasoning and techniques to machine learning. Considering the flexibility of acting in various business domains, a specific agent can be programmed to work in as many business domains as necessary, and essentially, it will also be possible to reconfigure the agent´s business domains at execution time. All the experiments in this work were idealized in the terms of a tourism negotiation package. Results from these experiments demonstrate effectiveness of our proposal.

The automated negotiation topic plays an important role in e-commerce research. However, despite considerable work on automated negotiation, few research efforts have aimed at software engineering facilities such a reuse and flexibility. To address this issue, we propose a novel computation environment for building agents with flexible negotiation strategies to function in various virtual business domains. Regarding the negotiation strategies, some decision taking assistance techniques may be used in group, e.g. rule-based reasoning and techniques to machine learning. Considering the flexibility of acting in various business domains, a specific agent can be programmed to work in as many business domains as necessary, and essentially, it will also be possible to reconfigure the agent´s business domains at execution time. All the experiments in this work were idealized in the terms of a tourism negotiation package. Results from these experiments demonstrate effectiveness of our proposal.

Working with leading experts in the field of cognitive neuroscience and computational intelligence, SNL has developed a computational architecture that represents neurocognitive mechanisms associated with how humans remember experiences in their past. The architecture represents how knowledge is organized and updated through information from individual experiences (episodes) via the cortical-hippocampal declarative memory system. We compared the simulated behavioral characteristics with those of humans measured under well established experimental standards, controlling for unmodeled aspects of human processing, such as perception. We used this knowledge to create robust simulations of & human memory behaviors that should help move the scientific community closer to understanding how humans remember information. These behaviors were experimentally validated against actual human subjects, which was published. An important outcome of the validation process will be the joining of specific experimental testing procedures from the field of neuroscience with computational representations from the field of cognitive modeling and simulation.

Research shows that most agent-based collaborations suffer from lack of flexibility. This is due to the fact that most agent-based applications assume pre-defined knowledge of agents' capabilities and/or neglect basic cognitive and interactional requirements in multi-agent collaboration. The highlight of this paper is that it brings cognitive models (inspired from cognitive sciences and HCI) proposing architectural and knowledge-based requirements for agents to structure ontological models for cognitive profiling in order to increase cognitive awareness between themselves, which in turn promotes flexibility, reusability and predictability of agent behavior; thus contributing towards minimizing cognitive overload incurred on humans. The semantic web is used as an action mediating space, where shared knowledge base in the form of ontological models provides affordances for improving cognitive awareness.

This is the second in a series of five papers describing the information, decision, and action in crew context (IDAC) model for human reliability analysis. An example application of this modeling technique is also discussed in this series. The model is developed to probabilistically predict the responses of the nuclear power plant control room operating crew in accident conditions. The operator response spectrum includes cognitive, psychological, and physical activities during the course of an accident. This paper identifies the IDAC set of performance influencing factors (PIFs), providing their definitions and causal organization in the form of a modular influence diagram. Fifty PIFs are identified to support the IDAC model to be implemented in a computer simulation environment. They are classified into eleven hierarchically structured groups. The PIFs within each group are independent to each other; however, dependencies may exist between PIFs within different groups. The supporting evidence for the selection and organization of the influence paths based on psychological literature, observations, and various human reliability analysis methodologies is also indicated.

This paper presents a model-based human error taxonomy and data collection. The underlying model, IDA (described in two companion papers), is a cognitive model of behavior developed for analysis of the actions of nuclear power plant operating crew during abnormal situations. The taxonomy is established with reference to three external reference points (i.e. plant status, procedures, and crew) and four reference points internal to the model (i.e. information collected, diagnosis, decision, action). The taxonomy helps the analyst: (1) recognize errors as such; (2) categorize the error in terms of generic characteristics such as 'error in selection of problem solving strategies' and (3) identify the root causes of the error. The data collection methodology is summarized in post event operator interview and analysis summary forms. The root cause analysis methodology is illustrated using a subset of an actual event. Statistics, which extract generic characteristics of error prone behaviors and error prone situations are presented. Finally, applications of the human error data collection are reviewed. A primary benefit of this methodology is to define better symptom-based and other auxiliary procedures with associated training to minimize or preclude certain human errors. It also helps in design of control rooms, and in assessment of human error probabilities in the probabilistic risk assessment framework.

Educational software applications may be more effective if they can adapt their teaching strategies to the needs of individual students. Individualisation may be achieved through student modelling, which is the main practice for Intelligent Tutoring Systems (ITS). In this paper, we show how principles of cognitive psychology have been adapted and incorporated into the student modelling component of a knowledge-based authoring tool for the generation of ITSs. The cognitive model takes into account the time that has passed since the learning of a fact has occurred and gives the system an insight of what is known and remembered and what needs to be revised and when. This model is individualised by using evidence from each individual student's actions.

We present computational experiments on language segmentation using a general information-theoretic cognitive model. We present a method which uses the statistical regularities of language to segment a continuous stream of symbols into “meaningful units” at a range of levels. Given a string of symbols—in the present approach, textual representations of phonemes—we attempt to find the syllables such as grea and sy (in the word greasy); words such as in, greasy, wash, and water ; and phrases such as in greasy wash water. The approach is entirely information-theoretic, and requires no knowledge of the units themselves; it is thus assumed to require only general cognitive abilities, and has previously been applied to music. We tested our approach on two spoken language corpora, and we discuss our results in the context of learning as a statistical processes.

A person applies her knowledge when she performs a cognitive task. The representation of a person's knowledge of a task is accessible from a cognitive task analysis. The think -aloud method is useful for carrying out a cognitive task analysis because think -aloud data represent closely a person's knowledge. Various cognitive tasks were analyzed and models of cognitive tasks were developed based on the external and internal environments of task s. Comparison between models of cognitive tasks shows similarities between the models. Further analysis suggests common features which formed the basis for the construction of a generalized model of cognitive tasks. This study proposed a generalized model which has four major categories referred to as (a) properties, (b) events, (c) essence and (d) rules of a task. These categories represent information and knowledge in the external and internal environments of cognitive tasks.

Recently, there has been a profound resurgence interest in expanding the effectiveness of human machine systems. The motivation for this interest stems not only from the growing realization that better designed systemstailored to augment their user's innate skills and capabilities -will enable users to 'do more', but also from the fact that the world with which we interact is becoming increasingly reliant on machines. In the past, the human machine interface was bridged through engineering based principles, but, with our expanding understanding of how the human brain drives behavior it is now possible to consider, as never before, human machine design efforts that fully address human and machine needs at the same time.

In the past twenty or so years the scientific community has made impressive advancements in the modeling and simulation of general human cognition. This progress has led to the beginnings of wide-spread applications and use. In fact, we are now at a point where the community can begin to make fairly accurate predictions as to how this technology will be used in the next twenty-plus years. Accordingly, the purpose of this panel is to engage the community at large regarding the future needs and requirements associated with building cognitive models for various scientific and engineering endeavors. Specifically, this panel will discuss and make recommendations with regard to the future functionality of cognitive modeling that could be encompassed in nextgeneration capabilities. To do this, we will concentrate on four different domain areas. These are: academic use of cognitive modeling, cognitive model development, neuroscience-related issues, and practical applications of cognitive modeling.

The automated negotiation topic plays an important role in e-commerce research. However, despite considerable work on automated negotiation, few research efforts have aimed at software engineering facilities such a reuse and flexibility. To address this issue, we propose a novel computation environment for building agents with flexible negotiation strategies to function in various virtual business domains. Regarding the negotiation strategies, some decision taking assistance techniques may be used in group, e.g. rule-based reasoning and techniques to machine learning. Considering the flexibility of acting in various business domains, a specific agent can be programmed to work in as many business domains as necessary, and essentially, it will also be possible to reconfigure the agent´s business domains at execution time. All the experiments in this work were idealized in the terms of a tourism negotiation package. Results from these experiments demonstrate effectiveness of our proposal.

This paper presents experiments on using ChatGPT4 and Google Bard to create ACT-R and Soar models. The study involves two simulated cognitive tasks, where ChatGPT4 and Google Bard (Large Language Models, LLMs) serve as conversational interfaces within the ACT-R and Soar framework development environments. The first task involves creating an intelligent driving model using ACT-R with motor and perceptual behavior and can further interact with an unmodified interface. The second task evaluates the development of educational skills using Soar. Prompts were designed to represent cognitive operations and actions, including providing context, asking perception-related questions, decision-making scenarios, and evaluating the system's responses, and they were iteratively refined based on model behavior evaluation. Results demonstrate the potential of using LLMs to serve as interactive interfaces to develop ACT-R and Soar models within a human-in-the-loop model development process. We documented the mistakes LLMs made during this integration and provided corresponding resolutions when adopting this modeling approach. Furthermore, we presented a framework of prompt patterns that maximizes LLMs interaction for artificial cognitive architectures.

Senturk worked on the project as an ETS summer intern during June and July. Our subject matter expert consultants were invaluable in working through the issues of standards, claims, and evidence that underlie the project, and in offering suggestions along the way for the prototype.

In the behavioural animation field of research, the simulation of populated virtual cities requires that agents are able to navigate autonomously through their environment. It is of interest to tend to the most realistic human-like planning and navigation. In order to do ...

Jugendliche zeigen riskantes Gesundheitsverhalten als Strategie zur Bewältigung von Entwicklungsaufgaben (Pinquart & Silbereisen, 2004). Sozialkognitive Modelle zur Erklärung und Prädiktion von Gesundheitsverhalten betrachten menschliches Verhalten als Resultat vernunftgesteuerter Prozesse, vernachlässigen allerdings emotionale Faktoren (Pant, 2003). Die vorliegende Studie exploriert Emotionen vor, während und nach dem ersten Geschlechtsverkehr und deren Rolle bei STDs-präventivem Verhalten. 32 Mädchen (x age =17.19; SD age =0.998) wurden interviewt. Das vollständig transkribierte Material wurde mittels Qualitativer Inhaltsanalyse (Mayring, 2003) ausgewertet. Die Quantifizierung der qualitativen Daten ermöglichte die Methodenintegration auf Datenebene im Sinne der Mixed Methods (Teddlie & Tashakkori, 2003). Der erste Geschlechtsverkehr von Mädchen ist durch ein komplexes emotionales Erleben charakterisiert. Hinsichtlich der Dimensionen positiver und negativer Affekt und der spezifischen Emotionen zeigen sich Veränderungen im zeitlichen Verlauf. Mädchen, denen die Kondomverwendung beim ersten Mal schwerer fiel als später, berichten häufig von Angst vor der Reaktion des Partners auf das Einfordern des Kondoms. Für Personen, die beim ersten Mal nicht alkoholisiert waren, sind Reue und Kondomnichtgebrauch assoziiert. Mädchen, die intendieren beim zweiten Mal ein Kondom zu verwenden, nennen mehr positive Emotionen nach dem ersten Mal. Präventive Bemühungen sollten demnach verstärkt die emotionale Kompetenz (Salisch, 2002) fokussieren.

How to best sequence instruction in a collection of basic facts is a problem often faced by intelligent tutoring systems. To solve this problem, the following work details two tests of a system to provide drill practice (test trials with feedback) for foreign language vocabulary learning using a practice schedule determined to be optimal according to a cognitive model. In the first test, students chose between an optimized version and a version that merely cycled the vocabulary items. Examination of the time on task data revealed a preference for practice based on the decisions of the cognitive model. In the second test, the system was used to train the component parts of Chinese characters and measure the transfer of knowledge to subsequent learning of Chinese characters. Chinese character learning was improved for students with the relevant optimized training.

Pediatric Obsessive-Compulsive Disorder (OCD) is a chronic condition that disrupts mental health, family dynamics, and social functioning, often requiring family involvement for effective treatment. This paper explores how family accommodation reinforces symptoms and highlights evidence-based interventions, such as Family-Based Cognitive Behavioral Therapy (FB-CBT) and Exposure and Response Prevention (ERP), to reduce these behaviors and foster long-term recovery. Cultural considerations, diagnostic challenges, and the role of siblings and extended family are discussed, emphasizing the importance of tailored and inclusive approaches. Strategies to overcome barriers to family engagement, including psychoeducation, telehealth options, and motivational interviewing, are presented alongside case examples to illustrate practical applications. Finally, the paper calls for further research into culturally adapted interventions, technology-assisted therapies, and long-term outcomes to ensure sustainable, accessible, and family-centered care. By addressing these complexities, the paper provides a comprehensive roadmap for clinicians and families navigating pediatric OCD treatment.

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In cognitive science, the dynamical systems theory (DST) has recently been advocated as an approach to cognitive modeling that is better suited to the dynamics of cognitive processes than the symbolic/computational approaches are. Often, the differences between DST and the symbolic/computational approach are emphasized. However, alternatively their commonalities can be analyzed and a unifying framework can be sought. In this paper, the possibility of such a unifying perspective on dynamics is analyzed. The analysis covers dynamics in cognitive disciplines, as well as in physics, mathematics and computer science. The unifying perspective warrants the development of integrated approaches covering both DST aspects and symbolic/computational aspects. The concept of a statedetermined system, which is based on the assumption that properties of a given state fully determine the properties of future states, lies at the heart of DST. Taking this assumption as a premise, the explanatory problem of dynamics is analyzed in more detail. The analysis of four cases within different disciplines (cognitive science, physics, mathematics, computer science) shows how in history this perspective led to numerous often used concepts within them. In cognitive science, the concepts desire and intention were introduced, and in classical mechanics the concepts momentum, energy and force. Similarly, in mathematics a number of concepts have been developed to formalize the state-determined system assumption [e.g. derivatives (of different orders) of a function, Taylor approximations]. Furthermore, transition systems-a currently popular format for specification of dynamical systems within computer science-can also be interpreted from this perspective. One of the main contributions of the paper is that the case studies provide a unified view on the explanation of dynamics across the chosen disciplines. All approaches to dynamics analyzed in this paper share the state-determined system assumption and the (explicit or implicit) use of anticipatory state properties. Within cognitive science, realism is one of the problems identified for the symbolic/computational

The computational agent model presented in this paper generates prior and retrospective ownership states for an action based on principles from recent neurological theories. A prior ownership state is affected by prediction of the effects of a prepared action, and exerts control by strengthening or suppressing actual execution of the action. A retrospective ownership state depends on whether the sensed consequences of an executed action cooccur with the predicted consequences, and is the basis for acknowledging authorship of actions, for example, in social context. It is shown how a number of known phenomena can occur. For example, scenarios were shown for vetoing a prepared action due to unsatisfactory predicted effects, and for mirroring an observed action performed by another agent, without imitating the action. Moreover, it is shown how poor action effect prediction capabilities can lead to reduced retrospective ownership states, as in persons suffering from schizophrenia. The obtained computational model can be used as a basis for simulationbased training, for example, to develop a virtual patient based on the model so that a psychiatrist or psychotherapist (e.g., during his or her education) can gain insight in the processes in certain types of patients, or to analyse how effective a certain form of therapy can be. A second type of application is in the area of gaming or virtual stories in which, for example, persons with deviations in ownership states play a role and based on that show unexpected behaviour.

In this paper an agent-based ambient agent architecture is presented based on monitoring human's interaction with his or her environment and performing cognitive analysis of the causes of observed or predicted behaviour. Within this agent architecture, a cognitive model for the human is taken as a point of departure. From the cognitive model it is automatically derived how internal cognitive states affect human's performance aspects. Furthermore, for these cognitive states representation relations are derived from the cognitive model, expressed by temporal specifications involving events that will be monitored. The representation relations are verified on the monitoring information automatically, resulting in the identification of cognitive states, which affect the performance aspects. In such a way the ambient agent model is able to provide a more in depth cognitive analysis of causes of (un)satisfactory performance and based on this analysis to generate interventions in a knowledgeable manner. The application of the architecture proposed is demonstrated by two examples from the ambient-assisted living domain and the computer-assisted instruction domain.

This study investigated the relationship between self-appraisals of performance, symptom severity and post-event rumination in social phobia, and evaluated the effect of treatment on these variables. A socially phobic group and a nonanxious control group performed an impromptu speech and were told that their performance would be evaluated. Participants appraised their performance immediately after the speech and 1 week later, and the frequency of post-event rumination during the week following the speech was assessed. The socially phobic group maintained the negative appraisals of their speech over the week, whereas the nonclinical group showed increased positivity about their performance. The socially phobic group also engaged in more negative rumination than controls. Treatment improved perceptions of performance and reduced negative rumination. These results are discussed in the light of cognitive models of social phobia.

Emotions are an integral part of human decision making. It follows that emotions should take part in the decision process towards the design of more realistic artificial agents. Three psychological models for emotions are examined and a corresponding algorithm is developed for each depicting its process. A generalized multi-agent model is designed to demonstrate the implementation of each of the three methods. An agent thus represents a human capable of exhibiting emotional state in response to an arbitrary emotionally charged event of varying impact.

This paper proposes a transformation of the Cognitive Walkthrough (CW), a theory-based usability inspection method that has proven useful in designing applications that support use by exploration. The new Cognitive Walkthrough for the Web (CWW) is superior for evaluating how well websites support users' navigation and information search tasks. The CWW uses Latent Semantic Analysis to objectively estimate the degree of semantic similarity (information scent) between representative user goal statements (100-200 words) and heading/link texts on each web page. Using an actual website, the paper shows how the CWW identifies three types of problems in web page designs. Three experiments test CWW predictions of users' success rates in accomplishing goals, verifying the value of CWW for identifying these usability problems.

The aim of this paper is to understand the human mind functions such that we can simulate them into a computational model for making cognitive systems more intelligent. We then present this model with formulae using a top-down approach. We propose that the human thought process, which is the fundamental unit for the human mind and all the different emotions coming from it, can be implemented as a computational model to a reasonable extent. Furthermore, we argue that our model has the ability to derive certain mind functions such as dreams, distraction, etc. The model utilizes a top-down approach for understanding the factors involved in the thought process while explaining the factors involved. We also propose interpretations of certain mind functions such as dreams, distraction, etc. We also present the formulae's application against certain hypothetical small sets of data which explains how this model identifies certain cognitive mind functions. The authors are intending to make continuous improvements in this framework as more scientific advances happen in the understanding of the human cognitive functions.

Previous studies on program comprehension were carried out largely in the context of procedural languages. Our purpose is to develop and evaluate a cognitive model of object-oriented (OO) program understanding. Our model is based on the van Dijk and Kintsch's model of text understanding (1983). One key aspect of this theoretical approach is the distinction between two kinds of representation the reader might construct from a text: the textbase and the situation model. On the basis of results of an experiment we have conducted, we evaluate the cognitive validity of this distinction in OO program understanding. We examine how the construction of these two representations is differentially affected by the programmer's expertise and how they evolve differentially over time.