19,323 research outputs found

    A vignette model for distributed teaching and learning

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    Computer software and telecommunication technologies are being assimilated into the education sector. At a slower pace, educational methodologies have been evolving and gradually adopted by educators. The widespread and rapid assimilation of technology may be outstripping the uptake of better pedagogical strategies. Non‐pedagogical development of content could lead to the development of legacy systems that constrain future developments. Problems have arisen with computer‐based learning (CBL) materials, such as the lack of uptake of monolithic programmes that cannot be easily changed to keep pace with natural progress or the different requirements of different teachers and institutions. Also, hypertext/hypermedia learning environments have limitations in that following predefined paths is no more interactive than page turning. These considerations require a flexible and dynamic approach for the benefit of both the teacher and student. Courses may be constructed from vignettes to meet a desired purpose and to avoid the problems of adoption for the reasons that programmes cannot easily be changed or are not designed to meet particular needs. Vignettes are small, first‐principle, first‐person, heuristic activities (which are mimetic) from which courses can be constructed Vignettes use an object‐orientated approach to the development of computer‐based learning materials. Vignettes are objects that can be manipulated via a property sheet, which enables changing the object's inherent character or behaviour. A vignette object can interact with other vignette objects to create more complex educational interactions or models. The vignette approach leads to a development concept that is horizontally distributed across disciplines rather than vertically limited to single subjects

    Pattern languages in HCI: A critical review

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    This article presents a critical review of patterns and pattern languages in human-computer interaction (HCI). In recent years, patterns and pattern languages have received considerable attention in HCI for their potential as a means for developing and communicating information and knowledge to support good design. This review examines the background to patterns and pattern languages in HCI, and seeks to locate pattern languages in relation to other approaches to interaction design. The review explores four key issues: What is a pattern? What is a pattern language? How are patterns and pattern languages used? and How are values reflected in the pattern-based approach to design? Following on from the review, a future research agenda is proposed for patterns and pattern languages in HCI

    Unifying an Introduction to Artificial Intelligence Course through Machine Learning Laboratory Experiences

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    This paper presents work on a collaborative project funded by the National Science Foundation that incorporates machine learning as a unifying theme to teach fundamental concepts typically covered in the introductory Artificial Intelligence courses. The project involves the development of an adaptable framework for the presentation of core AI topics. This is accomplished through the development, implementation, and testing of a suite of adaptable, hands-on laboratory projects that can be closely integrated into the AI course. Through the design and implementation of learning systems that enhance commonly-deployed applications, our model acknowledges that intelligent systems are best taught through their application to challenging problems. The goals of the project are to (1) enhance the student learning experience in the AI course, (2) increase student interest and motivation to learn AI by providing a framework for the presentation of the major AI topics that emphasizes the strong connection between AI and computer science and engineering, and (3) highlight the bridge that machine learning provides between AI technology and modern software engineering

    Expert system technology

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    The expert system is a computer program which attempts to reproduce the problem-solving behavior of an expert, who is able to view problems from a broad perspective and arrive at conclusions rapidly, using intuition, shortcuts, and analogies to previous situations. Expert systems are a departure from the usual artificial intelligence approach to problem solving. Researchers have traditionally tried to develop general modes of human intelligence that could be applied to many different situations. Expert systems, on the other hand, tend to rely on large quantities of domain specific knowledge, much of it heuristic. The reasoning component of the system is relatively simple and straightforward. For this reason, expert systems are often called knowledge based systems. The report expands on the foregoing. Section 1 discusses the architecture of a typical expert system. Section 2 deals with the characteristics that make a problem a suitable candidate for expert system solution. Section 3 surveys current technology, describing some of the software aids available for expert system development. Section 4 discusses the limitations of the latter. The concluding section makes predictions of future trends

    Issues in designing learning by teaching systems

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    Abstract: Learning by teaching systems are a relatively recent approach to designing Intelligent Learning Environments that place learners in the role of tutors. These systems are based on the practice of peer tutoring where students take on defined roles of tutor and tutee. An architecture for learning by teaching systems is described that does not require the domain model of an Intelligent Tutoring System. However a mutual communication language is needed and is defined by a conceptual syntax that delimits the domain content of the dialogue. An example learning by teaching system is described for the domain of qualitative economics. The construction and testing of this system inform a discussion of the major design issues involved: the nature of the learnt model, the form of the conceptual syntax, the control of the interaction and the possible introduction of domain knowledge. 1

    Adaptive development and maintenance of user-centric software systems

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    A software system cannot be developed without considering the various facets of its environment. Stakeholders – including the users that play a central role – have their needs, expectations, and perceptions of a system. Organisational and technical aspects of the environment are constantly changing. The ability to adapt a software system and its requirements to its environment throughout its full lifecycle is of paramount importance in a constantly changing environment. The continuous involvement of users is as important as the constant evaluation of the system and the observation of evolving environments. We present a methodology for adaptive software systems development and maintenance. We draw upon a diverse range of accepted methods including participatory design, software architecture, and evolutionary design. Our focus is on user-centred software systems
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