7 research outputs found
Intelligent Tutoring Systems for Generation Z's Addiction
As generation Z's big data is flooding the Internet through social nets,
neural network based data processing is turning an important cornerstone,
showing significant potential for fast extraction of data patterns. Online
course delivery and associated tutoring are transforming into customizable,
on-demand services driven by the learner. Besides automated grading, strong
potential exists for the development and deployment of next generation
intelligent tutoring software agents. Self-adaptive, online tutoring agents
exhibiting "intelligent-like" behavior, being capable "to learn" from the
learner, will become the next educational superstars. Over the past decade,
computer-based tutoring agents were deployed in a variety of extended reality
environments, from patient rehabilitation to psychological trauma healing. Most
of these agents are driven by a set of conditional control statements and a
large answers/questions pairs dataset. This article provides a brief
introduction on Generation Z's addiction to digital information, highlights
important efforts for the development of intelligent dialogue systems, and
explains the main components and important design decisions for Intelligent
Tutoring System.Comment: 4 page
A Metamodel for Designing an Intelligent Tutoring Systems Authoring Tool
Previous intelligent tutoring systems (ITS) and ITS authoring studies predominantly simulated and evaluated artificial intelligence (AI) techniques and cognitive architectures/notions in educational domains. Current research focuses on software design that is priori driven by educational theories; it concerns the conception of
Augmented Conversation and Cognitive Apprenticeship Metamodel (ACCAM). The pedagogy driven metamodelâACCAMâforms the basis for a formal (theory based) approach to designing ITS authoring tools for numerical aspect of numerical disciplines. This research, therefore, showcases the convergence of two
theoretical perspectivesâthe Conversation Theory (CT) and Cognitive Apprenticeship (CA)âwhich were never considered together before now. The novel conceptual platformâthe ACCAMâflows and benefited from the synergistic effect of the stated theories through the introduction of the concept of âaugmented conversationâ
within the resulting integrated framework. Thus, current work draws on the pedagogical import of the mentioned educational theories, elicits new meanings, and lays the foundation as well as opens future evaluation of a pedagogical engineering methodology that flows therefrom
Constraint-based knowledge representation for individualized instruction
Traditional knowledge representations were developed to
encode complete, explicit and executable programs, a goal that makes
them less than ideal for representing the incomplete and partial
knowledge of a student. In this paper, we discuss state constraints, a
type of knowledge unit originally invented to explain how people can
detect and correct their own errors. Constraint-based student modeling
has been implemented in several intelligent tutoring systems (ITS) so
far, and the empirical data verifies that students learn while interacting
with these systems. Furthermore, learning curves are smooth when
plotted in terms of individual constraints, supporting the psychological
appropriateness of the representation. We discuss the differences
between constraints and other representational formats, the advantages
of constraint-based models and the types of domains in which they are
likely to be useful
Designing Embodied Interactive Software Agents for E-Learning: Principles, Components, and Roles
Embodied interactive software agents are complex autonomous, adaptive, and social software systems with a digital embodiment that enables them to act on and react to other entities (users, objects, and other agents) in their environment through bodily actions, which include the use of verbal and non-verbal communicative behaviors in face-to-face interactions with the user. These agents have been developed for various roles in different application domains, in which they perform tasks that have been assigned to them by their developers or delegated to them by their users or by other agents. In computer-assisted learning, embodied interactive pedagogical software agents have the general task to promote human learning by working with students (and other agents) in computer-based learning environments, among them e-learning platforms based on Internet technologies, such as the Virtual Linguistics Campus (www.linguistics-online.com). In these environments, pedagogical agents provide contextualized, qualified, personalized, and timely assistance, cooperation, instruction, motivation, and services for both individual learners and groups of learners.
This thesis develops a comprehensive, multidisciplinary, and user-oriented view of the design of embodied interactive pedagogical software agents, which integrates theoretical and practical insights from various academic and other fields. The research intends to contribute to the scientific understanding of issues, methods, theories, and technologies that are involved in the design, implementation, and evaluation of embodied interactive software agents for different roles in e-learning and other areas. For developers, the thesis provides sixteen basic principles (Added Value, Perceptible Qualities, Balanced Design, Coherence, Consistency, Completeness, Comprehensibility, Individuality, Variability, Communicative Ability, Modularity, Teamwork, Participatory Design, Role Awareness, Cultural Awareness, and Relationship Building) plus a large number of specific guidelines for the design of embodied interactive software agents and their components. Furthermore, it offers critical reviews of theories, concepts, approaches, and technologies from different areas and disciplines that are relevant to agent design. Finally, it discusses three pedagogical agent roles (virtual native speaker, coach, and peer) in the scenario of the linguistic fieldwork classes on the Virtual Linguistics Campus and presents detailed considerations for the design of an agent for one of these roles (the virtual native speaker)
Augmented Conversation and Cognitive Apprenticeship Metamodel Based Intelligent Learning Activity Builder System
This research focused on a formal (theory based) approach to designing Intelligent Tutoring System (ITS) authoring tool involving two specific conventional pedagogical theoriesâConversation Theory (CT) and Cognitive Apprenticeship (CA). The research conceptualised an Augmented Conversation and Cognitive Apprenticeship Metamodel (ACCAM) based on apriori theoretical knowledge and assumptions of its underlying theories. ACCAM was implemented in an Intelligent Learning Activity Builder System (ILABS)âan ITS authoring tool. ACCAMâs implementation aims to facilitate formally designed tutoring systems, hence, ILABSâthe practical implementation of ACCAMâ constructs metamodels for Intelligent Learning Activity Tools (ILATs) in a numerical problem-solving context (focusing on the construction of procedural knowledge in applied numerical disciplines). Also, an Intelligent Learning Activity Management System (ILAMS), although not the focus of this research, was developed as a launchpad for ILATs constructed and to administer learning activities. Hence, ACCAM and ILABS constitute the conceptual and practical contributions that respectively flow from this research.
ACCAMâs implementation was tested through the evaluation of ILABS and ILATs within an applied numerical domainâthe accounting domain. The evaluation focused on the key constructs of ACCAMâcognitive visibility and conversation, implemented through a tutoring strategy employing Process Monitoring (PM). PM augments conversation within a cognitive apprenticeship framework; it aims to improve the visibility of the cognitive process of a learner and infers intelligence in tutoring systems. PM was implemented via an interface that attempts to bring learnerâs thought process to the surface. This approach contrasted with previous studies that adopted standard Artificial Intelligence (AI) based inference techniques. The interface-based PM extends the existing CT and CA work. The strategy (i.e. interface-based PM) makes available a new tutoring approach that aimed fine-grain (or step-wise) feedbacks, unlike the goal-oriented feedbacks of model-tracing. The impact of PMâas a preventive strategy (or intervention) and to aid diagnosis of learnersâ cognitive processâwas investigated in relation to other constructs from the literature (such as detection of misconception, feedback generation and perceived learning effectiveness). Thus, the conceptualisation and implementation of PM via an interface also contributes to knowledge and practice.
The evaluation of the ACCAM-based design approach and investigation of the above mentioned constructs were undertaken through usersâ reaction/perception to ILABS and ILAT. This involved, principally, quantitative approach. However, a qualitative approach was also utilised to gain deeper insight. Findings from the evaluation supports the formal (theory based) design approachâthe design of ILABS through interaction with ACCAM. Empirical data revealed the presence of conversation and cognitive visibility constructs in ILATs, which were determined through its behaviour during the learning process. This research identified some other theoretical elements (e.g. motivation, reflection, remediation, evaluation, etc.) that possibly play out in a learning process. This clarifies key conceptual variables that should be considered when constructing tutoring systems for applied numerical disciplines (e.g. accounting, engineering). Also, the research revealed that PM enhances the detection of a learnerâs misconception and feedback generation. Nevertheless, qualitative data revealed that frequent feedbacks due to the implementation of PM could be obstructive to thought process at advance stage of learning. Thus, PM implementations should also include delayed diagnosis, especially for advance learners who prefer to have it on request. Despite that, current implementation allows users to turn PM off, thereby using alternative learning route. Overall, the research revealed that the implementation of interface-based PM (i.e. conversation and cognitive visibility) improved the visibility of learnerâs cognitive process, and this in turn enhanced learningâas perceived
UDC 681.5.015 Constraint-Based Knowledge Representation for Individualized Instruction
Abstract. Traditional knowledge representations were developed to encode complete, explicit and executable programs, a goal that makes them less than ideal for representing the incomplete and partial knowledge of a student. In this paper, we discuss state constraints, a type of knowledge unit originally invented to explain how people can detect and correct their own errors. Constraint-based student modeling has been implemented in several intelligent tutoring systems (ITS) so far, and the empirical data verifies that students learn while interacting with these systems. Furthermore, learning curves are smooth when plotted in terms of individual constraints, supporting the psychological appropriateness of the representation. We discuss the differences between constraints and other representational formats, the advantages of constraint-based models and the types of domains in which they are likely to be useful. 1