14,555 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

    Кибербезопасность в образовательных сетях

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    The paper discusses the possible impact of digital space on a human, as well as human-related directions in cyber-security analysis in the education: levels of cyber-security, social engineering role in cyber-security of education, “cognitive vaccination”. “A Human” is considered in general meaning, mainly as a learner. The analysis is provided on the basis of experience of hybrid war in Ukraine that have demonstrated the change of the target of military operations from military personnel and critical infrastructure to a human in general. Young people are the vulnerable group that can be the main goal of cognitive operations in long-term perspective, and they are the weakest link of the System.У статті обговорюється можливий вплив цифрового простору на людину, а також пов'язані з людиною напрямки кібербезпеки в освіті: рівні кібербезпеки, роль соціального інжинірингу в кібербезпеці освіти, «когнітивна вакцинація». «Людина» розглядається в загальному значенні, головним чином як та, що навчається. Аналіз надається на основі досвіду гібридної війни в Україні, яка продемонструвала зміну цілей військових операцій з військовослужбовців та критичної інфраструктури на людину загалом. Молодь - це вразлива група, яка може бути основною метою таких операцій в довгостроковій перспективі, і вони є найслабшою ланкою системи.В документе обсуждается возможное влияние цифрового пространства на человека, а также связанные с ним направления в анализе кибербезопасности в образовании: уровни кибербезопасности, роль социальной инженерии в кибербезопасности образования, «когнитивная вакцинация». «Человек» рассматривается в общем смысле, в основном как ученик. Анализ представлен на основе опыта гибридной войны в Украине, которая продемонстрировала изменение цели военных действий с военного персонала и критической инфраструктуры на человека в целом. Молодые люди являются уязвимой группой, которая может быть главной целью когнитивных операций в долгосрочной перспективе, и они являются самым слабым звеном Систем

    Multi-agent knowledge integration mechanism using particle swarm optimization

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    This is the post-print version of the final paper published in Technological Forecasting and Social Change. The published article is available from the link below. Changes resulting from the publishing process, such as peer review, editing, corrections, structural formatting, and other quality control mechanisms may not be reflected in this document. Changes may have been made to this work since it was submitted for publication. Copyright @ 2011 Elsevier B.V.Unstructured group decision-making is burdened with several central difficulties: unifying the knowledge of multiple experts in an unbiased manner and computational inefficiencies. In addition, a proper means of storing such unified knowledge for later use has not yet been established. Storage difficulties stem from of the integration of the logic underlying multiple experts' decision-making processes and the structured quantification of the impact of each opinion on the final product. To address these difficulties, this paper proposes a novel approach called the multiple agent-based knowledge integration mechanism (MAKIM), in which a fuzzy cognitive map (FCM) is used as a knowledge representation and storage vehicle. In this approach, we use particle swarm optimization (PSO) to adjust causal relationships and causality coefficients from the perspective of global optimization. Once an optimized FCM is constructed an agent based model (ABM) is applied to the inference of the FCM to solve real world problem. The final aggregate knowledge is stored in FCM form and is used to produce proper inference results for other target problems. To test the validity of our approach, we applied MAKIM to a real-world group decision-making problem, an IT project risk assessment, and found MAKIM to be statistically robust.Ministry of Education, Science and Technology (Korea

    Information systems for interactive learning: Design perspective

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    This paper aims to present and discuss educational issues and relevant research to universities and colleges in the Arabian Gulf Region. This include cultural, students’ learning preferences and the use of information and communication technology. It particularly focuses on interactive learning through the consideration of learning styles. It explores the sequential-global learning styles profile of undergraduate students as part of a continuous research in Information Systems design with a particular focus on the design of Interactive Learning Systems (ILSs). A study to examine the learning style profile of undergraduate students in a cohort of Management Information Systems at a UAE university has been conducted, and a discussion and recommendations on how these findings can be reflected on the design of ILSs are provided

    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

    Responsible research and innovation in science education: insights from evaluating the impact of using digital media and arts-based methods on RRI values

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    The European Commission policy approach of Responsible Research and Innovation (RRI) is gaining momentum in European research planning and development as a strategy to align scientific and technological progress with socially desirable and acceptable ends. One of the RRI agendas is science education, aiming to foster future generations' acquisition of skills and values needed to engage in society responsibly. To this end, it is argued that RRI-based science education can benefit from more interdisciplinary methods such as those based on arts and digital technologies. However, the evidence existing on the impact of science education activities using digital media and arts-based methods on RRI values remains underexplored. This article comparatively reviews previous evidence on the evaluation of these activities, from primary to higher education, to examine whether and how RRI-related learning outcomes are evaluated and how these activities impact on students' learning. Forty academic publications were selected and its content analysed according to five RRI values: creative and critical thinking, engagement, inclusiveness, gender equality and integration of ethical issues. When evaluating the impact of digital and arts-based methods in science education activities, creative and critical thinking, engagement and partly inclusiveness are the RRI values mainly addressed. In contrast, gender equality and ethics integration are neglected. Digital-based methods seem to be more focused on students' questioning and inquiry skills, whereas those using arts often examine imagination, curiosity and autonomy. Differences in the evaluation focus between studies on digital media and those on arts partly explain differences in their impact on RRI values, but also result in non-documented outcomes and undermine their potential. Further developments in interdisciplinary approaches to science education following the RRI policy agenda should reinforce the design of the activities as well as procedural aspects of the evaluation research
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