Presentation on theme: "I-TRACE PROJECT, 1st Partners Meeting, Catania, November 25-26, 2005 University “Politehnica” of Bucharest Artificial Intelligence and Multi-Agent Systems."— Presentation transcript:
I-TRACE PROJECT, 1st Partners Meeting, Catania, November 25-26, 2005 University “Politehnica” of Bucharest Artificial Intelligence and Multi-Agent Systems Laboratory http://turing.cs.pub.ro/ai_mas
I-TRACE PROJECT, 1st Partners Meeting, Catania, November 25-26, 2005 University “Politehnica” of Bucharest Founded in 1818 Comprises 13 faculties specialised in several domains of engineering sciences Houses 37 Research Centres, among which 4 were recognized as Centres of Excellence at national level and 8 grew into Multi-User Research Infrastructures with the support of the Romania - World Bank Program. Has bilateral co-operation agreements with 74 universities from Europe, America, Asia and Africa Is member of international academic organizations such as: CESAER, EUA, IAU, AUF Actively participates in R&D international programmes like: COST, FP5, FP6, CORINT, NATO, Socrates, etc. http://www.pub.ro
I-TRACE PROJECT, 1st Partners Meeting, Catania, November 25-26, 2005 Faculty of Automatic Control and Computer Science Created in 1966 Offers degrees in “Computer Science and System Science” Undergraduate and graduate programmes: Bachelor of Science in: Computer Science and Engineering Automatic Control and Applied Informatics Master of Science programmes Ph.D. programmes http://www.acs.pub.ro
I-TRACE PROJECT, 1st Partners Meeting, Catania, November 25-26, 2005 Faculty of Automatic Control and Computer Science Department of Computer Science and Engineering Department of Automatic Control and Systems Engineering Department of Control and Industrial Informatics Excellence in teaching and research Scientific research, as well as design, consulting, and expertise activities are carried out in: –Research centers –Research laboratories and research groups http://www.acs.pub.ro
I-TRACE PROJECT, 1st Partners Meeting, Catania, November 25-26, 2005 AI-MAS Laboratory Cognitive multi-agent systems: coordination mechanisms automated negotiation MAS architectures multi-agent learning Models of affective computing Constructive e-learning Agent-based tools for cooperative learning and tele-working http://turing.cs.pub.ro
I-TRACE PROJECT, 1st Partners Meeting, Catania, November 25-26, 2005AI-MAS The targeted areas of applications are: organisation coordination e-commerce mobile environments virtual environments for learning CSCW The AI-MAS Laboratory is member of FP6 AgentLink III: Network of Excellence for Agent- Based Computing, and was also a member of FP5 AgentLink II
I-TRACE PROJECT, 1st Partners Meeting, Catania, November 25-26, 2005 AI-MAS - Partnerships LIPN, Université Paris Nord, Institut Galilée EU Socrates Programme, E-learning project École Nationale Superiéure des Mines de Saint-Etienne EU Socrates Programme, Theses en co-tutelle École Polytechnique de l'Université de Nantes DEA-ECD between EPUN and UPB, E-learning project, EU Socrates Programme
Some projects I-TRACE PROJECT, 1st Partners Meeting, Catania, November 25-26, 2005 Projects financed by the World Bank A system for organisational design and coordination using intelligent agents, 1999-2002 Education Program on Intelligent Agents Technology, 2001-2002 International projects Agents intelligents, Grant of AUF, 2001-2002 Continuous Education Program on Intelligent Agents Technology and Knowledge Processing, Socrates-Erasmus IP, 2001 Représentation logique des connaissances pour les agents intelligents, Grant of AUF, 1999-2000 Participation in the current EU projects Central European Centre for Women and Youth in Science, FP6, 2004-2007 EU-NCIT: NCIT Leading to EU-IST Excellency, FP6, 2005-2007
I-TRACE PROJECT, 1st Partners Meeting, Catania, November 25-26, 2005 One of our current projects Research on emotional agents learning Emotions have been shown to have an important impact on several human processes such as decision-making, planning, cognition, and learning Focus research on: An artificial tutor endowed with synthesized emotions according to a BDE (Belief-Desire-Emotion) model (developed by our group) Analyzes possible student reactions my means of an emotion sensing glove and how these reactions may be influenced by the tutor actions
I-TRACE PROJECT, 1st Partners Meeting, Catania, November 25-26, 2005 Proposed contribution to I-TRACE A1. Investigate the use of pen-based input and graphical interaction to understand how annotational capabilities may be used for educational activities: What does exist? (documentation) Integration of annotation techniques in an on-line module of the course DSA A2. Study of the impact of hand-written note-taking, sketching, and graphical annotation on learner's preferences, learning styles, and the provided added value: Study cognitive/learning styles Study of the impact of hand-written note-taking, sketching, and graphical annotation on learning styles A3. Evaluation of the interfaces allowing pen-based graphical interaction based on the outcome of A1. Conduct several experiments with a target group of 50 students at DCS
I-TRACE PROJECT, 1st Partners Meeting, Catania, November 25-26, 2005 Proposed contribution to I-TRACE A4. Use of pen based input and graphical interaction for creating cognitive (mind) maps for: summarising lectures supplementary readings A5. Evaluation of the added value and impact of the use of cognitive maps on increasing efficiency of the learning process Conduct several experiments with a target group of 20 students at DCS A6. Study of different aspects related to standardization and interoperability and drawing directions for a set of proposed standards relevant to pen-based graphical interaction in ODL (LET) to be sent to ISO/JTC1/SC36. ?? depending on available results
I-TRACE PROJECT, 1st Partners Meeting, Catania, November 25-26, 2005 Tennant (1988) defined cognitive styles as "an individual’s characteristic and consistent approach to organizing and processing information" In many situations, cognitive styles and learning styles are used interchangeably. Generally, cognitive styles are more related to theoretical or academic research, while learning styles are more related to practical applications. A major difference between these two terms is the number of style elements involved. Cognitive styles are more related to a bipolar dimension while learning styles are not necessarily either/or extremes. There are several classifications of cognitive styles, according to different dimensions. Cognitive/learning styles in the literature have been viewed in three major respects: structure, process, or both structure and process (Riding & Cheema, 1991; Squires, 1981; Tennant, 1988; Wilson, 1981). Learning styles
I-TRACE PROJECT, 1st Partners Meeting, Catania, November 25-26, 2005 Active learners understand new information by doing something with it. Reflective learners prefer to think about new information first before acting on it. Sensing learners like learning facts and solving problems by well established methods. Visual learners understand new information best by seeing it in the form of pictures, demonstrations, diagrams, charts, films, and so on. Sequential learners understand new information in linear steps where each step follows logically from the previous one. Intuitive learners prefer discovering new relationships and can be innovative in their approach to problem solving. Verbal learners understand new information best through written and spoken words. Global learners tend to learn in large jumps by absorbing material in a random order without necessarily seeing any connections until they have grasped the whole concept.
I-TRACE PROJECT, 1st Partners Meeting, Catania, November 25-26, 2005 Mind mapping involves writing down a central idea and thinking up new and related ideas which radiate out from the centre. By focusing on key ideas written down and then looking for branches out and connections between the ideas, students are mapping knowledge in a manner which helps them understand and remember new information. Mind maps Mind (cognitive) mapping can help understand and remember the important issues in a lecture or readings Picture from the Academic Support Division of James Cook University
I-TRACE PROJECT, 1st Partners Meeting, Catania, November 25-26, 2005 Proposed output An interactive collaborative course module and assessment module on Data Structures and Algorithms – Y1 A set of good practices of use of hand-written note-taking, sketching, and graphical annotation of teaching materials in Computer Science with focus on DSA – Y1 A minimal set of relevant features for characterising the learner’s preferences and the learning style, particularly focussed on graphical interaction techniques. - Y1 end + Y2 – beginning An interactive module to construct cognitive maps using pen based input – Y2 A set of relevant good practices of use of cognitive maps to enhance learning efficiency – Y2 Survey results of A3 and A5. – Y1 and Y2 We shall also bring our contribution to project Website, by providing relevant materials, to the reports elaborated by the project, and dissemination of results.
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