1,196 research outputs found

    DESIGNING CHATBOTS FOR HIGHER EDUCATION PRACTICE

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    In this research–in–progress paper, we employ design science research to articulate design knowledge for chatbots in higher education practice. We conducted a literature review to factor previous research into the design process. In addition, we performed a content analysis of student e-mails and forum posts from four instances of a basic Java programming course. Drawing from literature and data, we present a conceptual architecture for chatbots in higher education, discuss its rationale, and provide a proof-of-concept implementation. We conclude with a discussion including tentative design recommendations and a plan for continued research

    Procedural-Reasoning Architecture for Applied Behavior Analysis-based Instructions

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    Autism Spectrum Disorder (ASD) is a complex developmental disability affecting as many as 1 in every 88 children. While there is no known cure for ASD, there are known behavioral and developmental interventions, based on demonstrated efficacy, that have become the predominant treatments for improving social, adaptive, and behavioral functions in children. Applied Behavioral Analysis (ABA)-based early childhood interventions are evidence based, efficacious therapies for autism that are widely recognized as effective approaches to remediation of the symptoms of ASD. They are, however, labor intensive and consequently often inaccessible at the recommended levels. Recent advancements in socially assistive robotics and applications of virtual intelligent agents have shown that children with ASD accept intelligent agents as effective and often preferred substitutes for human therapists. This research is nascent and highly experimental with no unifying, interdisciplinary, and integral approach to development of intelligent agents based therapies, especially not in the area of behavioral interventions. Motivated by the absence of the unifying framework, we developed a conceptual procedural-reasoning agent architecture (PRA-ABA) that, we propose, could serve as a foundation for ABA-based assistive technologies involving virtual, mixed or embodied agents, including robots. This architecture and related research presented in this disser- tation encompass two main areas: (a) knowledge representation and computational model of the behavioral aspects of ABA as applicable to autism intervention practices, and (b) abstract architecture for multi-modal, agent-mediated implementation of these practices

    Agents for educational games and simulations

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    This book consists mainly of revised papers that were presented at the Agents for Educational Games and Simulation (AEGS) workshop held on May 2, 2011, as part of the Autonomous Agents and MultiAgent Systems (AAMAS) conference in Taipei, Taiwan. The 12 full papers presented were carefully reviewed and selected from various submissions. The papers are organized topical sections on middleware applications, dialogues and learning, adaption and convergence, and agent applications

    Corroborating Emotion Theory with Role Theory and Agent Technology: a Framework for Designing Emotional Agents as Motivational Tutoring Entities

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    Nowadays, more and more applications require systems that can interact with humans. Agents can be perceived as computing services that humans, or even other agents, can request in order to accomplish their tasks. Some services may be simple and others rather complex. A way to determine the best agents (services) to be implemented is to identify who the actors are in the object of study, which roles they play, and (if possible) what kind of knowledge they use. Socially Intelligent Agents (SIAs) are agent systems that are able to connect and interface with humans, i.e. robotic or computational systems that show aspects of human-style social intelligence. In addition to their relevance in application areas such as e-commerce and entertainment, building artefacts in software and hardware has been recognized as a powerful tool for establishing a science of social minds which is a constructive approach toward understanding social intelligence in humans and other animals. Social intelligence in humans and other animals has a number of fascinating facets and implications for the design of SIAs. Human beings are biological agents that are embodied members of a social environment and are autobiographic agents who have a unique personality. They are situated in time and space and interpret new experiences based on reconstructions of previous experiences. Due to their physical embodiment, they have a unique perspective on the world and a unique history: an autobiography. Also, humans are able to express and recognize emotions, that are important in regulating individual survival and problem-solving as well as social interactions. Like artificial intelligence research trend, SIA research trend can be pursued with different goals in mind. A deep AI approach seeks to simulate real social intelligence and processes. A shallow AI approach, which will be highlighted also within this thesis, aims to create artefacts that are not socially intelligent per se, but rather appear socially intelligent to a given user. The shallow approach does not seek to create social intelligence unless it is meaningful social intelligence vis-à-vis some user situation In order to develop believable SIAs we do not have to know how beliefs-desires and intentions actually relate to each other in the real minds of the people. If one wants to create the impression of an artificial social agent driven by beliefs and desires, it is enough to draw on investigations on how people with different cultural background, develop and use theories of mind to understand the behaviours of others. Therefore, SIA technology needs to model the folk-theory reasoning rather than the real thing. To a shallow AI approach, a model of mind based on folk-psychology is as valid as one based on cognitive theory. Distance education is understood as online learning that is technology-based training which encompasses both computer-assisted and Web-based training. These systems, which appear to offer something for everyone at any time, in any place, do not always live up to the great promise they offer. The usage of social intelligent agents in online learning environments can enable the design of “enhanced-learning environments” that allow for the development and the assessment of social competences as well as the common professional competences. Within this thesis it is shown how to corroborate affective theory with role theory with agent technology in a synchronous virtual environment in order to overcome several inconveniences of distance education systems. This research embraces also the shallow approach of SIA and aims to provide the first steps of a method for creating a believable life-like tutor agent which can partially replace human-teachers and assist the students in the process of learning. The starting point for this research came from the fact: anxious, angry or depressed students do not learn; people in these conditions do not absorb information efficiently, consequentially it is an illusion to think that learning environments that do not consider motivational and emotional factors are adequate

    Software-based dialogue systems: Survey, taxonomy and challenges

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    The use of natural language interfaces in the field of human-computer interaction is undergoing intense study through dedicated scientific and industrial research. The latest contributions in the field, including deep learning approaches like recurrent neural networks, the potential of context-aware strategies and user-centred design approaches, have brought back the attention of the community to software-based dialogue systems, generally known as conversational agents or chatbots. Nonetheless, and given the novelty of the field, a generic, context-independent overview on the current state of research of conversational agents covering all research perspectives involved is missing. Motivated by this context, this paper reports a survey of the current state of research of conversational agents through a systematic literature review of secondary studies. The conducted research is designed to develop an exhaustive perspective through a clear presentation of the aggregated knowledge published by recent literature within a variety of domains, research focuses and contexts. As a result, this research proposes a holistic taxonomy of the different dimensions involved in the conversational agents’ field, which is expected to help researchers and to lay the groundwork for future research in the field of natural language interfaces.With the support from the Secretariat for Universities and Research of the Ministry of Business and Knowledge of the Government of Catalonia and the European Social Fund. The corresponding author gratefully acknowledges the Universitat Politècnica de Catalunya and Banco Santander for the inancial support of his predoctoral grant FPI-UPC. This paper has been funded by the Spanish Ministerio de Ciencia e Innovación under project / funding scheme PID2020-117191RB-I00 / AEI/10.13039/501100011033.Peer ReviewedPostprint (author's final draft

    An XRI Mixed-Reality Internet-of-Things Architectural Framework Toward Immersive and Adaptive Smart Environments

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    The internet-of-things (IoT) refers to the growing number of embedded interconnected devices within everyday ubiquitous objects and environments, especially their networks, edge controllers, data gathering and management, sharing, and contextual analysis capabilities. However, the IoT suffers from inherent limitations in terms of human-computer interaction. In this landscape, there is a need for interfaces that have the potential to translate the IoT more solidly into the foreground of everyday smart environments, where its users are multimodal, multifaceted, and where new forms of presentation, adaptation, and immersion are essential. This work highlights the synergetic opportunities for both IoT and XR to converge toward hybrid XR objects with strong real-world connectivity, and IoT objects with rich XR interfaces. The paper contributes i) an understanding of this multi-disciplinary domain XR-IoT (XRI); ii) a theoretical perspective on how to design XRI agents based on the literature; iii) a system design architectural framework for XRI smart environment development; and iv) an early discussion of this process. It is hoped that this research enables future researchers in both communities to better understand and deploy hybrid smart XRI environments
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