Negotiated Tutoring: An Approach to Interaction in Intelligent Tutoring Systems

This thesis describes a general approach to tutorial interaction in Intelligent Tutoring Systems, called "Negotiated Tutoring". Some aspects of the approach have been implemented as a computer program in the 'KANT' (Kritical Argument Negotiated Tutoring) system. Negotiated Tutoring synthesises some recent trends in Intelligent Tutoring Systems research, including interaction symmetry, use of explicit negotiation in dialogue, multiple interaction styles, and an emphasis on cognitive and metacognitive skill acquisition in domains characterised by justified belief. This combination of features has not been previously incorporated into models for intelligent tutoring dialogues. Our approach depends on modelling the high-level decision-making processes and memory representations used by a participant in dialogue. Dialogue generation is controlled by reasoning mechanisms which operate on a 'dialogue state', consisting of conversants' beliefs, a set of possible dialogue moves, and a restricted representation of the recent utterances generated by both conversants. The representation for conversants' beliefs is based on Anderson's (1983) model for semantic memory, and includes a model for dialogue focus based on spreading activation. Decisions in dialogue are based on preconditions with respect to the dialogue state, higher level educational preferences which choose between relevant alternative dialogue moves, and negotiation mechanisms designed to ensure cooperativity. The domain model for KANT was based on a cognitive model for perception of musical structures in tonal melodies, which extends the theory of Lerdahl and Jackendoff (1983). Our model ('GRAF' - GRouping Analysis with Frames) addresses a number of problems with Lerdahl and Jackendoff's theory, notably in describing how a number of unconscious processes in music cognition interact, including elements of top-down and bottom-up processing. GRAF includes a parser for musical chord functions, a mechanism for performing musical reductions, low-level feature detectors and a frame-system (Minsky 1977) for musical phrase structures

Collaborative trails in e-learning environments

This deliverable focuses on collaboration within groups of learners, and hence collaborative trails. We begin by reviewing the theoretical background to collaborative learning and looking at the kinds of support that computers can give to groups of learners working collaboratively, and then look more deeply at some of the issues in designing environments to support collaborative learning trails and at tools and techniques, including collaborative filtering, that can be used for analysing collaborative trails. We then review the state-of-the-art in supporting collaborative learning in three different areas – experimental academic systems, systems using mobile technology (which are also generally academic), and commercially available systems. The final part of the deliverable presents three scenarios that show where technology that supports groups working collaboratively and producing collaborative trails may be heading in the near future

Archaeological knowledge and its representation an inter-disciplinary study of the problems of knowledge representation

The thesis is a study of archaeology viewed from a perspective informed by (a) social constructionist theory and pragmatism; (b) techniques of Belief and Knowledge Representation developed by Artificial Intelligence research and (c) the conception of history and historical practice propounded by the philosopher, historian and archaeologist, R.G. Collingwood. It is argued that Gibsonian affordances and von Uexkull's notion of the Umwelt, recently discussed by Rom Harré, provide the basis for a description and understanding of human action and agency. Further, belief and knowledge representation techniques embodied in Expert Systems and Intelligent Tutoring Systems provide a means of implementing models of human action which may bridge intentionality and process and thereby provide a unifying learning environment in which the relationships of language, social action and material transformation of the physical world can be explored in a unified way. The central claim made by the thesis is that Collingwood's logic (dialectic) of Question & Answer developed in 1917 as a hermeneutic procedure, may be seen as a fore-runner of Newell and Simon's Heuristic Search, and thereby amenable to modem approaches to problem solving. Collingwood's own approach to History/ Archaeology is grounded on many shared ideas with pragmatism and a social constructionist conception of mind and is conducted within a problem solving framework. Collingwood is therefore seen as a three-way bridge between Social Psychology, Artificial Intelligence and Archaeology. The thesis concludes that Social Psychology, Artificial Intelligence and Archaeology can be integrated through the use of Intelligent Tutoring Systems informed by a Collingwoodian perspective on Archaeology, Mind and History - construed as Mind's self-knowledge

Educational Technology: The influence of theory

In this paper we explore the role of theories in current practice in educational technology. We review a range of writings from the past 30 years on the nature of learning technology research. We discuss influences on learning technologies from the related fields of Artificial Intelligence in Education (AIED) and Human-Computer Interaction (HCI). We identify two groups of theories which have been used. The first group are related to principled decisions about the design of learning materials. The second group influence the ways in which we frame our research on learning. Research in learning technologies in the future will need to draw on both groups of theories. In this paper, we draw on our own experiences as educational technologists and the purpose of the paper is to encourage other educational technologists to join with us in reflecting on their own use of theories

English language teachers’ conceptualizations of one-to-one private tutoring: An international phenomenographic study

Private English tutoring, understood as the paid English teaching service offered to students to supplement their learning of English at school or prepare them for an examination in English, has become a popular out-of-school learning activity. In order to obtain deeper insights into its intricacies, the need arises to examine the experience of one of its pivotal stakeholders – the private tutors. This article is based on a phenomenographic study with a view to investigating the conceptions of private tutoring held by 15 English teachers from three countries (Poland, Portugal, and Turkey) who offer private teaching services in English in their local contexts. The findings suggest that there are at least three conceptions according to which private tutoring can be experienced by the participants: as a source of income, as helping, and as professional development. The study also poses the question if there is space for formal training of private tutors and calls for further research into English private tutoring

Integration of Action and Language Knowledge: A Roadmap for Developmental Robotics

“This material is presented to ensure timely dissemination of scholarly and technical work. Copyright and all rights therein are retained by authors or by other copyright holders. All persons copying this information are expected to adhere to the terms and constraints invoked by each author's copyright. In most cases, these works may not be reposted without the explicit permission of the copyright holder." “Copyright IEEE. Personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution to servers or lists, or to reuse any copyrighted component of this work in other works must be obtained from the IEEE.”This position paper proposes that the study of embodied cognitive agents, such as humanoid robots, can advance our understanding of the cognitive development of complex sensorimotor, linguistic, and social learning skills. This in turn will benefit the design of cognitive robots capable of learning to handle and manipulate objects and tools autonomously, to cooperate and communicate with other robots and humans, and to adapt their abilities to changing internal, environmental, and social conditions. Four key areas of research challenges are discussed, specifically for the issues related to the understanding of: 1) how agents learn and represent compositional actions; 2) how agents learn and represent compositional lexica; 3) the dynamics of social interaction and learning; and 4) how compositional action and language representations are integrated to bootstrap the cognitive system. The review of specific issues and progress in these areas is then translated into a practical roadmap based on a series of milestones. These milestones provide a possible set of cognitive robotics goals and test scenarios, thus acting as a research roadmap for future work on cognitive developmental robotics.Peer reviewe

A methodology for evaluating intelligent tutoring systems

DissertationThis dissertation proposes a generic methodology for evaluating intelligent tutoring systems (ITSs), and applies it to the evaluation of the SQL-Tutor, an ITS for the database language SQL. An examination of the historical development, theory and architecture of intelligent tutoring systems, as well as the theory, architecture and behaviour of the SQL-Tutor sets the context for this study. The characteristics and criteria for evaluating computer-aided instruction (CAl) systems are considered as a background to an in-depth investigation of the characteristics and criteria appropriate for evaluating ITSs. These criteria are categorised along internal and external dimensions with the internal dimension focusing on the intrinsic features and behavioural aspects of ITSs, and the external dimension focusing on its educational impact. Several issues surrounding the evaluation of ITSs namely, approaches, methods, techniques and principles are examined, and integrated within a framework for assessing the added value of ITS technology for instructional purposes.Educational StudiesM. Sc. (Information Systems

Knowledge Elicitation Methods for Affect Modelling in Education

Research on the relationship between affect and cognition in Artificial Intelligence in Education (AIEd) brings an important dimension to our understanding of how learning occurs and how it can be facilitated. Emotions are crucial to learning, but their nature, the conditions under which they occur, and their exact impact on learning for different learners in diverse contexts still needs to be mapped out. The study of affect during learning can be challenging, because emotions are subjective, fleeting phenomena that are often difficult for learners to report accurately and for observers to perceive reliably. Context forms an integral part of learners’ affect and the study thereof. This review provides a synthesis of the current knowledge elicitation methods that are used to aid the study of learners’ affect and to inform the design of intelligent technologies for learning. Advantages and disadvantages of the specific methods are discussed along with their respective potential for enhancing research in this area, and issues related to the interpretation of data that emerges as the result of their use. References to related research are also provided together with illustrative examples of where the individual methods have been used in the past. Therefore, this review is intended as a resource for methodological decision making for those who want to study emotions and their antecedents in AIEd contexts, i.e. where the aim is to inform the design and implementation of an intelligent learning environment or to evaluate its use and educational efficacy

Developing Student Model for Intelligent Tutoring System

The effectiveness of an e-learning environment mainly encompasses on how efficiently the tutor presents the learning content to the candidate based on their learning capability. It is therefore inevitable for the teaching community to understand the learning style of their students and to cater for the needs of their students. One such system that can cater to the needs of the students is the Intelligent Tutoring System (ITS). To overcome the challenges faced by the teachers and to cater to the needs of their students, e-learning experts in recent times have focused in Intelligent Tutoring System (ITS). There is sufficient literature that suggested that meaningful, constructive and adaptive feedback is the essential feature of ITSs, and it is such feedback that helps students achieve strong learning gains. At the same time, in an ITS, it is the student model that plays a main role in planning the training path, supplying feedback information to the pedagogical module of the system. Added to it, the student model is the preliminary component, which stores the information to the specific individual learner. In this study, Multiple-choice questions (MCQs) was administered to capture the student ability with respect to three levels of difficulty, namely, low, medium and high in Physics domain to train the neural network. Further, neural network and psychometric analysis were used for understanding the student characteristic and determining the student’s classification with respect to their ability. Thus, this study focused on developing a student model by using the Multiple-Choice Questions (MCQ) for integrating it with an ITS by applying the neural network and psychometric analysis. The findings of this research showed that even though the linear regression between real test scores and that of the Final exam scores were marginally weak (37%), still the success of the student classification to the extent of 80 percent (79.8%) makes this student model a good fit for clustering students in groups according to their common characteristics. This finding is in line with that of the findings discussed in the literature review of this study. Further, the outcome of this research is most likely to generate a new dimension for cluster based student modelling approaches for an online learning environment that uses aptitude tests (MCQ’s) for learners using ITS. The use of psychometric analysis and neural network for student classification makes this study unique towards the development of a new student model for ITS in supporting online learning. Therefore, the student model developed in this study seems to be a good model fit for all those who wish to infuse aptitude test based student modelling approach in an ITS system for an online learning environment. (Abstract by Author