897 resultados para pacs: expert systems and other ai software and techniques


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Final report, February 1979.

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Teaching is a dynamic activity. It can be very effective, if its impact is constantly monitored and adjusted to the demands of changing social contexts and needs of learners. This implies that teachers need to be aware about teaching and learning processes. Moreover, they should constantly question their didactical methods and the learning resources, which they provide to their students. They should reflect if their actions are suitable, and they should regulate their teaching, e.g., by updating learning materials based on new knowledge about learners, or by motivating learners to engage in further learning activities. In the last years, a rising interest in ‘learning analytics’ is observable. This interest is motivated by the availability of massive amounts of educational data. Also, the continuously increasing processing power, and a strong motivation for discovering new information from these pools of educational data, is pushing further developments within the learning analytics research field. Learning analytics could be a method for reflective teaching practice that enables and guides teachers to investigate and evaluate their work in future learning scenarios. However, this potentially positive impact has not yet been sufficiently verified by learning analytics research. Another method that pursues these goals is ‘action research’. Learning analytics promises to initiate action research processes because it facilitates awareness, reflection and regulation of teaching activities analogous to action research. Therefore, this thesis joins both concepts, in order to improve the design of learning analytics tools. Central research question of this thesis are: What are the dimensions of learning analytics in relation to action research, which need to be considered when designing a learning analytics tool? How does a learning analytics dashboard impact the teachers of technology-enhanced university lectures regarding ‘awareness’, ‘reflection’ and ‘action’? Does it initiate action research? Which are central requirements for a learning analytics tool, which pursues such effects? This project followed design-based research principles, in order to answer these research questions. The main contributions are: a theoretical reference model that connects action research and learning analytics, the conceptualization and implementation of a learning analytics tool, a requirements catalogue for useful and usable learning analytics design based on evaluations, a tested procedure for impact analysis, and guidelines for the introduction of learning analytics into higher education.

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Nach wie vor gibt es für die didaktische Gestaltung von Unterrichtssituationen wenig zufrieden stellende Hilfsmittel, die sowohl unerfahrene Pädagoginnen und Pädagogen unterstützen, gleichzeitig aber auch Kreativität und didaktische Vielfalt von Expertinnen und Experten fördern. Dieses Buch präsentiert für dieses Dilemma einen neuen Lösungsansatz.

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Web 2.0 und soziale Netzwerke gaben erste Impulse für neue Formen der Online-Lehre, welche die umfassende Vernetzung von Objekten und Nutzern im Internet nachhaltig einsetzen. Die Vielfältigkeit der unterschiedlichen Systeme erschwert aber deren ganzheitliche Nutzung in einem umfassenden Lernszenario, das den Anforderungen der modernen Informationsgesellschaft genügt. In diesem Beitrag wird eine auf dem Konnektivismus basierende Plattform für die Online-Lehre namens “Wiki-Learnia” präsentiert, welche alle wesentlichen Abschnitte des lebenslangen Lernens abbildet. Unter Einsatz zeitgemäßer Technologien werden nicht nur Nutzer untereinander verbunden, sondern auch Nutzer mit dedizierten Inhalten sowie ggf. zugehörigen Autoren und/oder Tutoren verknüpft. Für ersteres werden verschiedene Kommunikations-Werkzeuge des Web 2.0 (soziale Netzwerke, Chats, Foren etc.) eingesetzt. Letzteres fußt auf dem sogenannten “Learning-Hub”-Ansatz, welcher mit Hilfe von Web-3.0-Mechanismen insbesondere durch eine semantische Metasuchmaschine instrumentiert wird. Zum Aufzeigen der praktischen Relevanz des Ansatzes wird das mediengestützte Juniorstudium der Universität Rostock vorgestellt, ein Projekt, das Schüler der Abiturstufe aufs Studium vorbereitet. Anhand der speziellen Anforderungen dieses Vorhabens werden der enorme Funktionsumfang und die große Flexibilität von Wiki-Learnia demonstriert.

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Web 2.0 und soziale Netzwerke gaben erste Impulse für neue Formen der Online-Lehre, welche die umfassende Vernetzung von Objekten und Nutzern im Internet nachhaltig einsetzen. Die Vielfältigkeit der unterschiedlichen Systeme erschwert aber deren ganzheitliche Nutzung in einem umfassenden Lernszenario, das den Anforderungen der modernen Informationsgesellschaft genügt. In diesem Beitrag wird eine auf dem Konnektivismus basierende Plattform für die Online-Lehre namens “Wiki-Learnia” präsentiert, welche alle wesentlichen Abschnitte des lebenslangen Lernens abbildet. Unter Einsatz zeitgemäßer Technologien werden nicht nur Nutzer untereinander verbunden, sondern auch Nutzer mit dedizierten Inhalten sowie ggf. zugehörigen Autoren und/oder Tutoren verknüpft. Für ersteres werden verschiedene Kommunikations-Werkzeuge des Web 2.0 (soziale Netzwerke, Chats, Foren etc.) eingesetzt. Letzteres fußt auf dem sogenannten “Learning-Hub”-Ansatz, welcher mit Hilfe von Web-3.0-Mechanismen insbesondere durch eine semantische Metasuchmaschine instrumentiert wird. Zum Aufzeigen der praktischen Relevanz des Ansatzes wird das mediengestützte Juniorstudium der Universität Rostock vorgestellt, ein Projekt, das Schüler der Abiturstufe aufs Studium vorbereitet. Anhand der speziellen Anforderungen dieses Vorhabens werden der enorme Funktionsumfang und die große Flexibilität von Wiki-Learnia demonstriert.

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Der Beitrag fokussiert die Entwicklung, den Einsatz und die Nutzung von innovativen Technologien zur Unterstützung von Bildungsszenarien in Schule, Hochschule und Weiterbildung. Ausgehend von den verschiedenen Phasen des Corporate Learning, Social Learning, Mobile Learning und Intelligent Learning wird in einem ersten Abschnitt das Nutzungsverhalten von Technologien durch Kinder, Jugendliche und (junge) Erwachsene in Schule, Studium und Lehre betrachtet. Es folgt die Darstellung technologischer Entwicklungen auf Basis des Technology Life Cycle und die Konsequenzen von unterschiedlichen Entwicklungszuständen und Reifegraden von Technologien wie Content Learning Management, sozialen Netzwerken, mobilen Endgeräten, multidimensionalen und -modalen Räumen bis hin zu Anwendungen augmentierter Realität und des Internets der Dinge, Dienste und Daten für den Einsatz und die Nutzung in Bildungsszenarien. Nach der Darstellung von Anforderungen an digitale Technologien hinsichtlich Inhalte, Didaktik und Methodik wie etwa hinsichtlich der Erstellung von Inhalten, deren Wiederverwendung, Digitalisierung und Auffindbarkeit sowie Standards werden methodische Hinweise zur Nutzung digitaler Technologien zur Interaktion von Lernenden, von Lehrenden, sozialer Interaktion, kollaborativem Autorieren, Kommentierung, Evaluation und Begutachtung gegeben. Abschließend werden - differenziert für Schule und Hochschule - Erkenntnisse zu Rahmenbedingungen, Einflussgrößen, hemmenden und fördernden Faktoren sowie Herausförderungen bei der Einführung und nachhaltigen Implementation digitaler Technologien im schulischen Unterricht, in Lehre, Studium und Weiterbildung im Überblick zusammengefasst.

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This paper analyzes the relationship between the techniques used to build expert systems and the behaviors they exhibit to show that there is not sufficient evidence to link the behavioral shortcomings of first-generation expert systems to the shallow methods of representation and inference they employ. There is only evidence that the shortcomings are a consequence of a general lack of knowledge. Moreover, the paper shows that the first-generation of expert systems employ both shallow methods and most of the so-called deep methods. Lastly, we show that deeper methods augment but do not replace shallow reasoning methods; most expert systems should possess both."

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The survival of organisations, especially SMEs, depends, to the greatest extent, on those who supply them with the required material input. This is because if the supplier fails to deliver the right materials at the right time and place, and at the right price, then the recipient organisation is bound to fail in its obligations to satisfy the needs of its customers, and to stay in business. Hence, the task of choosing a supplier(s) from a list of vendors, that an organisation will trust with its very existence, is not an easy one. This project investigated how purchasing personnel in organisations solve the problem of vendor selection. The investigation went further to ascertain whether an Expert Systems model could be developed and used as a plausible solution to the problem. An extensive literature review indicated that very scanty research has been conducted in the area of Expert Systems for Vendor Selection, whereas many research theories in expert systems and in purchasing and supply management chain, respectively, had been reported. A survey questionnaire was designed and circulated to people in the industries who actually perform the vendor selection tasks. Analysis of the collected data confirmed the various factors which are considered during the selection process, and established the order in which those factors are ranked. Five of the factors, namely, Production Methods Used, Vendors Financial Background, Manufacturing Capacity, Size of Vendor Organisations, and Suppliers Position in the Industry; appeared to have similar patterns in the way organisations ranked them. These patterns suggested that the bigger the organisation, the more importantly they regarded the above factors. Further investigations revealed that respondents agreed that the most important factors were: Product Quality, Product Price and Delivery Date. The most apparent pattern was observed for the Vendors Financial Background. This generated curiosity which led to the design and development of a prototype expert system for assessing the financial profile of a potential supplier(s). This prototype was called ESfNS. It determines whether a prospective supplier(s) has good financial background or not. ESNS was tested by the potential users who then confirmed that expert systems have great prospects and commercial viability in the domain for solving vendor selection problems.

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The research described in this thesis investigates three issues related to the use of expert systems for decision making in organizations. These are the effectiveness of ESs when used in different roles, to replace a human decision maker or to advise a human decision maker, the users' behaviourand opinions towards using an expertadvisory system and, the possibility of organization-wide deployment of expert systems and the role of an ES in different organizational levels. The research was based on the development of expert systems within a business game environment, a simulation of a manufacturing company. This was chosen to give more control over the `experiments' than would be possible in a real organization. An expert system (EXGAME) was developed based on a structure derived from Anthony's three levels of decision making to manage the simulated company in the business game itself with little user intervention. On the basis of EXGAME, an expert advisory system (ADGAME) was built to help game players to make better decisions in managing the game company. EXGAME and ADGAME are thus two expert systems in the same domain performing different roles; it was found that ADGAME had, in places, to be different from EXGAME, not simply an extension of it. EXGAME was tested several times against human rivals and was evaluated by measuring its performance. ADGAME was also tested by different users and was assessed by measuring the users' performance and analysing their opinions towards it as a helpful decision making aid. The results showed that an expert system was able to replace a human at the operational level, but had difficulty at the strategic level. It also showed the success of the organization-wide deployment of expert systems in this simulated company.

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The work described was carried out as part of a collaborative Alvey software engineering project (project number SE057). The project collaborators were the Inter-Disciplinary Higher Degrees Scheme of the University of Aston in Birmingham, BIS Applied Systems Ltd. (BIS) and the British Steel Corporation. The aim of the project was to investigate the potential application of knowledge-based systems (KBSs) to the design of commercial data processing (DP) systems. The work was primarily concerned with BIS's Structured Systems Design (SSD) methodology for DP systems development and how users of this methodology could be supported using KBS tools. The problems encountered by users of SSD are discussed and potential forms of computer-based support for inexpert designers are identified. The architecture for a support environment for SSD is proposed based on the integration of KBS and non-KBS tools for individual design tasks within SSD - The Intellipse system. The Intellipse system has two modes of operation - Advisor and Designer. The design, implementation and user-evaluation of Advisor are discussed. The results of a Designer feasibility study, the aim of which was to analyse major design tasks in SSD to assess their suitability for KBS support, are reported. The potential role of KBS tools in the domain of database design is discussed. The project involved extensive knowledge engineering sessions with expert DP systems designers. Some practical lessons in relation to KBS development are derived from this experience. The nature of the expertise possessed by expert designers is discussed. The need for operational KBSs to be built to the same standards as other commercial and industrial software is identified. A comparison between current KBS and conventional DP systems development is made. On the basis of this analysis, a structured development method for KBSs in proposed - the POLITE model. Some initial results of applying this method to KBS development are discussed. Several areas for further research and development are identified.