A tutorial on machine learning for interactive pedagogical systems

This paper provides a short introduction to the field of machine learning for interactive pedagogical systems. Departing from different examples encountered in interactive pedagogical systems—such as intelligent tutoring systems or serious games—we go over several representative families of methods in machine learning, introducing key concepts in this field. We discuss common challenges in machine learning and how current methods address such challenges. Conversely, by anchoring our presentation on actual interactive pedagogical systems, highlight how machine learning can benefit the development of such systems

Modelling human teaching tactics and strategies for tutoring systems

One of the promises of ITSs and ILEs is that they will teach and assist learning in an intelligent manner. Historically this has tended to mean concentrating on the interface, on the representation of the domain and on the representation of the student’s knowledge. So systems have attempted to provide students with reifications both of what is to be learned and of the learning process, as well as optimally sequencing and adjusting activities, problems and feedback to best help them learn that domain. We now have embodied (and disembodied) teaching agents and computer-based peers, and the field demonstrates a much greater interest in metacognition and in collaborative activities and tools to support that collaboration. Nevertheless the issue of the teaching competence of ITSs and ILEs is still important, as well as the more specific question as to whether systems can and should mimic human teachers. Indeed increasing interest in embodied agents has thrown the spotlight back on how such agents should behave with respect to learners. In the mid 1980s Ohlsson and others offered critiques of ITSs and ILEs in terms of the limited range and adaptability of their teaching actions as compared to the wealth of tactics and strategies employed by human expert teachers. So are we in any better position in modelling teaching than we were in the 80s? Are these criticisms still as valid today as they were then? This paper reviews progress in understanding certain aspects of human expert teaching and in developing tutoring systems that implement those human teaching strategies and tactics. It concentrates particularly on how systems have dealt with student answers and how they have dealt with motivational issues, referring particularly to work carried out at Sussex: for example, on responding effectively to the student’s motivational state, on contingent and Vygotskian inspired teaching strategies and on the plausibility problem. This latter is concerned with whether tactics that are effectively applied by human teachers can be as effective when embodied in machine teachers

A hybrid method for the analysis of learner behaviour in active learning environments

Software-mediated learning requires adjustments in the teaching and learning process. In particular active learning facilitated through interactive learning software differs from traditional instructor-oriented, classroom-based teaching. We present behaviour analysis techniques for Web-mediated learning. Motivation, acceptance of the learning approach and technology, learning organisation and actual tool usage are aspects of behaviour that require different analysis techniques to be used. A hybrid method based on a combination of survey methods and Web usage mining techniques can provide accurate and comprehensive analysis results. These techniques allow us to evaluate active learning approaches implemented in form of Web tutorials

An active learning and training environment for database programming

Active learning facilitated through interactive, self-controlled learning environments differs substantially from traditional instructor-oriented, classroom-based teaching. We present a tool for database programming that integrates knowledge learning and skills training. How these tools are used most effectively is still an open question. Therefore, we discuss analysis and evaluation of these Web-based environments focusing on different aspects of learning behaviour and tool usage. Motivation, acceptance of the learning approach, learning organisation and actual tool usage are aspects of behaviour that require different techniques to be used

Lyceum: internet voice groupware for distance learning

This paper describes the design, implementation and deployment of Lyceum, a groupware system providing students and tutors with real time voice conferencing and visual workspace tools, over the standard internet. Lyceum uses a Java client/server architecture to tackle a formidable set of networking requirements: multi-way voice communication with synchronous shared displays, scalable to hundreds of simultaneous users, running over normal modem connections via unknown internet service providers, on home PCs. Additionally, the design had to support multiple courses with different requirements. We describe the interdisciplinary requirements analysis, and iterative design process, by which an academic course team was able to specify and evaluate prototypes. We present the systemís architecture, describe the technical successes and failures from Lyceumís first large scale deployment, and summarise its affordances for interaction and learning

Genisa: A web-based interactive learning environment for teaching simulation modelling

Intelligent Tutoring Systems (ITS) provide students with adaptive instruction and can facilitate the acquisition of problem solving skills in an interactive environment. This paper discusses the role of pedagogical strategies that have been implemented to facilitate the development of simulation modelling knowledge. The learning environment integrates case-based reasoning with interactive tools to guide tutorial remediation. The evaluation of the system shows that the model for pedagogical activities is a useful method for providing efficient simulation modelling instruction

Does interactivity require multimedia? The case of SAKI

SAKI is a self‐adaptive touch‐typing tutor with a pedigree dating back to the mid‐1950s. Even in its most recent form it eschews the temptation to present itself with the trimmings now commonly associated with microcomputer products. This paper argues that while the absence of such features may be a limiting factor in the commercial success of the program, SAKI is nevertheless a prime example of the way in which a computer can successfully react to and interact with a user, and indeed one which would actually lose educational value if it were to undergo an interface‐lift

OFMTutor: An operator function model intelligent tutoring system

The design, implementation, and evaluation of an Operator Function Model intelligent tutoring system (OFMTutor) is presented. OFMTutor is intended to provide intelligent tutoring in the context of complex dynamic systems for which an operator function model (OFM) can be constructed. The human operator's role in such complex, dynamic, and highly automated systems is that of a supervisory controller whose primary responsibilities are routine monitoring and fine-tuning of system parameters and occasional compensation for system abnormalities. The automated systems must support the human operator. One potentially useful form of support is the use of intelligent tutoring systems to teach the operator about the system and how to function within that system. Previous research on intelligent tutoring systems (ITS) is considered. The proposed design for OFMTutor is presented, and an experimental evaluation is described

From conditioning to learning communities: Implications of fifty years of research in e‐learning interaction design

This paper will consider e‐learning in terms of the underlying learning processes and interactions that are stimulated, supported or favoured by new media and the contexts or communities in which it is used. We will review and critique a selection of research and development from the past fifty years that has linked pedagogical and learning theory to the design of innovative e‐learning systems and activities, and discuss their implications. It will include approaches that are, essentially, behaviourist (Skinner and Gagné), cognitivist (Pask, Piaget and Papert), situated (Lave, Wenger and Seely‐Brown), socio‐constructivist (Vygotsky), socio‐cultural (Nardi and Engestrom) and community‐based (Wenger and Preece). Emerging from this review is the argument that effective e‐learning usually requires, or involves, high‐quality educational discourse, that leads to, at the least, improved knowledge, and at the best, conceptual development and improved understanding. To achieve this I argue that we need to adopt a more holistic approach to design that synthesizes features of the included approaches, leading to a framework that emphasizes the relationships between cognitive changes, dialogue processes and the communities, or contexts for e‐learning