2,123 research outputs found

    Neuro-fuzzy knowledge processing in intelligent learning environments for improved student diagnosis

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    In this paper, a neural network implementation for a fuzzy logic-based model of the diagnostic process is proposed as a means to achieve accurate student diagnosis and updates of the student model in Intelligent Learning Environments. The neuro-fuzzy synergy allows the diagnostic model to some extent "imitate" teachers in diagnosing students' characteristics, and equips the intelligent learning environment with reasoning capabilities that can be further used to drive pedagogical decisions depending on the student learning style. The neuro-fuzzy implementation helps to encode both structured and non-structured teachers' knowledge: when teachers' reasoning is available and well defined, it can be encoded in the form of fuzzy rules; when teachers' reasoning is not well defined but is available through practical examples illustrating their experience, then the networks can be trained to represent this experience. The proposed approach has been tested in diagnosing aspects of student's learning style in a discovery-learning environment that aims to help students to construct the concepts of vectors in physics and mathematics. The diagnosis outcomes of the model have been compared against the recommendations of a group of five experienced teachers, and the results produced by two alternative soft computing methods. The results of our pilot study show that the neuro-fuzzy model successfully manages the inherent uncertainty of the diagnostic process; especially for marginal cases, i.e. where it is very difficult, even for human tutors, to diagnose and accurately evaluate students by directly synthesizing subjective and, some times, conflicting judgments

    An open learning environment for the diagnosis, assistance and evaluation of students based on artificial intelligence

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    The personalized diagnosis, assistance and evaluation of students in open learning environments can be a challenging task, especially in cases that the processes need to be taking place in real-time, classroom conditions. This paper describes the design of an open learning environment under development, designed to monitor the comprehension of students, assess their prior knowledge, build individual learner profiles, provide personalized assistance and, finally, evaluate their performance by using artificial intelligence. A trial test has been performed, with the participation of 20 students, which displayed promising results

    Evaluation of an intelligent open learning system for engineering education

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    In computer-assisted education, the continuous monitoring and assessment of the learner is crucial for the delivery of personalized education to be effective. In this paper, we present a pilot application of the Student Diagnosis, Assistance, Evaluation System based on Artificial Intelligence (StuDiAsE), an open learning system for unattended student diagnosis, assistance and evaluation based on artificial intelligence. The system demonstrated in this paper has been designed with engineering students in mind and is capable of monitoring their comprehension, assessing their prior knowledge, building individual learner profiles, providing personalized assistance and, finally, evaluating a learner's performance both quantitatively and qualitatively by means of artificial intelligence techniques. The architecture and user interface of the system are being exhibited, the results and feedback received from a pilot application of the system within a theoretical engineering course are being demonstrated and the outcomes are being discussed

    Development of Intelligent Multi-agents System for Collaborative e-learning Support

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    The aim of this paper is the introduction of intelligence in e-learning collaborative system. In such system, the tutor plays an important role to facilitate collaboration between users and boost less active among them to get more involved for good pedagogical action. However, the problem lies in the large number of platform users, and the tutor tasks become difficult if not impossible. Therefore, we used fuzzy logic technics in order to solve this problem by automating tutor tasks and creating an artificial agent. This agent is elaborate in basing on the learners activities, especially the assessment of their collaborative behaviors. After the implementation of intelligent collaborative system by using Moodle platform, we have tested it. The reader will discover our approach and relevant results

    An Advanced eLearning Environment Developed for Engineering Learners

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    Monitoring and evaluating engineering learners through computer-based laboratory exercises is a difficult task, especially under classroom conditions. A complete diagnosis requires the capability to assess both the competence of the learner to use the scientific software and the understanding of the theoretical principles. This monitoring and evaluation needs to be continuous, unobtrusive and personalized in order to be effective. This study presents the results of the pilot application of an eLearning environment developed specifically with engineering learners in mind. As its name suggests, the Learner Diagnosis, Assistance, and Evaluation System based on Artificial Intelligence (StuDiAsE) is an Open Learning Environment that can perform unattended diagnostic, evaluation and feedback tasks based on both quantitative and qualitative parameters. The base architecture of the system, the user interface and its effect on the performance of postgraduate engineering learners are being presented

    Collaborative trails in e-learning environments

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    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

    Adaptive intelligent tutoring for teaching modern standard Arabic

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    A thesis submitted to the University of Bedfordshire, in partial fulfilment of the requirements for the degree of Doctor of PhilosophyThe aim of this PhD thesis is to develop a framework for adaptive intelligent tutoring systems (ITS) in the domain of Modern Standard Arabic language. This framework will comprise of a new approach to using a fuzzy inference mechanism and generic rules in guiding the learning process. In addition, the framework will demonstrate another contribution in which the system can be adapted to be used in the teaching of different languages. A prototype system will be developed to demonstrate these features. This system is targeted at adult English-speaking casual learners with no pre-knowledge of the Arabic language. It will consist of two parts: an ITS for learners to use and a teachers‘ tool for configuring and customising the teaching rules and artificial intelligence components among other configuration operations. The system also provides a diverse teaching-strategies‘ environment based on multiple instructional strategies. This approach is based on general rules that provide means to a reconfigurable prediction. The ITS determines the learner‘s learning characteristics using multiple fuzzy inferences. It has a reconfigurable design that can be altered by the teacher at runtime via a teacher-interface. A framework for an independent domain (i.e. pluggable-domain) for foreign language tutoring systems is introduced in this research. This approach allows the system to adapt to the teaching of a different language with little changes required. Such a feature has the advantages of reducing the time and cost required for building intelligent language tutoring systems. To evaluate the proposed system, two experiments are conducted with two versions of the software: the ITS and a cut down version with no artificial intelligence components. The learners used the ITS had shown an increase in scores between the post-test and the pre-test with learning gain of 35% compared to 25% of the learners from the cut down version

    Studies on Some Aspects of Service Quality Evaluation with Specific Relevance to Indian Service Industries

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    Quality has been treated as a major competing weapon by both the manufacturing industries and service providers to gain market share, improve productivity and profitability and sustain in business from long term perspective. Therefore, organizations throughout the world dealing with products or services or both are contemplating to implement Total Quality Management (TQM) principles for enhancing system effectiveness. Literature on TQM suggests that twenty critical factors ease the process of TQM implementation in any organization. However, few critical factors viz., leadership, customer satisfaction, training, and employee’s participation are emphasized more frequently in the literature compared to other factors. It is also observed that standardization of the best set of principles of TQM and their implementation sequence is difficult because diverse set of TQM principles are being adopted by organizations. Exhaustive investigation on implementation aspects of TQM results in an in..
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