70,077 research outputs found
Optimising ITS behaviour with Bayesian networks and decision theory
We propose and demonstrate a methodology for building tractable normative intelligent tutoring systems (ITSs). A normative ITS uses a Bayesian network for long-term student modelling and decision theory to select the next tutorial action. Because normative theories are a general framework for rational behaviour, they can be used to both define and apply learning theories in a rational, and therefore optimal, way. This contrasts to the more traditional approach of using an ad-hoc scheme to implement the learning theory. A key step of the methodology is the induction and the continual adaptation of the Bayesian network student model from student performance data, a step that is distinct from other recent Bayesian net approaches in which the network structure and probabilities are either chosen beforehand by an expert, or by efficiency considerations. The methodology is demonstrated by a description and evaluation of CAPIT, a normative constraint-based tutor for English capitalisation and punctuation. Our evaluation results show that a class using the full normative version of CAPIT learned the domain rules at a faster rate than the class that used a non-normative version of the same system
Dirichlet belief networks for topic structure learning
Recently, considerable research effort has been devoted to developing deep
architectures for topic models to learn topic structures. Although several deep
models have been proposed to learn better topic proportions of documents, how
to leverage the benefits of deep structures for learning word distributions of
topics has not yet been rigorously studied. Here we propose a new multi-layer
generative process on word distributions of topics, where each layer consists
of a set of topics and each topic is drawn from a mixture of the topics of the
layer above. As the topics in all layers can be directly interpreted by words,
the proposed model is able to discover interpretable topic hierarchies. As a
self-contained module, our model can be flexibly adapted to different kinds of
topic models to improve their modelling accuracy and interpretability.
Extensive experiments on text corpora demonstrate the advantages of the
proposed model.Comment: accepted in NIPS 201
Innovation and Employability in Knowledge Management Curriculum Design
During 2007/8, Southampton Solent University worked on a Leadership Foundation project focused on the utility of the multi-functional team approach as a vehicle to deliver innovation in strategic and operational terms in higher education (HE). The Task-Orientated Multi-Functional Team Approach (TOMFTA) project took two significant undertakings for Southampton Solent as key areas for investigation, one academic and one administrative in focus. The academic project was the development of an innovative and novel degree programme in knowledge management (KM).
The new KM Honours degree programme is timely both in recognition of the increasing importance to organisations of knowledge as a commodity, and in its adoption of a distinctive structure and pedagogy. The methodology for the KM curriculum design brings together student-centred and market-driven approaches: positioning the programme for the interests of students and requirements of employers, rather than just the capabilities of staff; while looking at ways that courses can be delivered with more flexibility, e.g. accelerated and block-mode; with level-differentiated activities, common cross-year content and material that is multi-purpose for use in short courses. In order to permit context at multiple levels in common, a graduate skills strand is taught separately as part of the University’s business-facing education agenda.
The KM portfolio offers a programme of practically-based courses integrating key themes in knowledge management, business, information distribution and development of the media. They develop problem-solving, communications, teamwork and other employability skills as well as the domain skills needed by emerging information management technologies. The new courses are built on activities which focus on different aspects of KM, drawing on existing content as a knowledge base. This paper presents the ongoing development of the KM programme through the key aspects in its conception and design
Template-driven teacher modelling approach : a thesis submitted in partial fulfilment of the requirements for the degree of Master of Science in Information Science at Massey University, Palmerston North
This thesis describes the Template-driven Teacher Modeling Approach, the initial implementation of the template server and the formative evaluation on the prototype. The initiative of Template-driven teacher modeling is to integrate the template server and intelligent teacher models in Web-based education systems for course authoring. There are a number of key components in the proposed system: user interface, template server and content repository. The Template-Driven Teacher Modeling (TDTM) architecture supports the course authoring by providing higher degree of control over the generation of presentation. The collection of accumulated templates in the template repository for a teacher or a group of teachers are selected as the inputs for the inference mechanism in teacher's model to calculate the best representation of the teaching strategy, and then predict teacher intention when he or she interacts with the system. Moreover, the presentation templates are kept to support the re-use of the on-line content at the level of individual screens with the help of Template Server
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Area 1: An Overview of Evidence for the National Approach to Professional Learning in Education
This report reviews published literature on the way that countries around the globe have organised and systematised professional learning for teachers in a time of curriculum change. It first reviews country specific literature and then presents evidence on the organisation of professional learning from more general literature, which is more concerned with improvements in practice. All literature used is either from peer-reviewed journals or from academic books. The literature was found by using scholarly search engines, searching under various terms indicating professional learning. In this way literature was uncovered that will be used to support or to question the approach that the Welsh Government takes towards professional learning in education
KEMNAD: A Knowledge Engineering Methodology for Negotiating Agent Development
Automated negotiation is widely applied in various domains. However, the development of such systems is a complex knowledge and software engineering task. So, a methodology there will be helpful. Unfortunately, none of existing methodologies can offer sufficient, detailed support for such system development. To remove this limitation, this paper develops a new methodology made up of: (1) a generic framework (architectural pattern) for the main task, and (2) a library of modular and reusable design pattern (templates) of subtasks. Thus, it is much easier to build a negotiating agent by assembling these standardised components rather than reinventing the wheel each time. Moreover, since these patterns are identified from a wide variety of existing negotiating agents(especially high impact ones), they can also improve the quality of the final systems developed. In addition, our methodology reveals what types of domain knowledge need to be input into the negotiating agents. This in turn provides a basis for developing techniques to acquire the domain knowledge from human users. This is important because negotiation agents act faithfully on the behalf of their human users and thus the relevant domain knowledge must be acquired from the human users. Finally, our methodology is validated with one high impact system
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