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I-TRACE PROJECT, 1st Partners Meeting, Catania, November 25-26, 2005 University “Politehnica” of Bucharest Artificial Intelligence and Multi-Agent Systems.

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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:

1 I-TRACE PROJECT, 1st Partners Meeting, Catania, November 25-26, 2005 University “Politehnica” of Bucharest Artificial Intelligence and Multi-Agent Systems Laboratory

2 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.

3 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

4 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

5 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

6 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

7 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

8 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, Education Program on Intelligent Agents Technology,  International projects Agents intelligents, Grant of AUF, 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,  Participation in the current EU projects Central European Centre for Women and Youth in Science, FP6, EU-NCIT: NCIT Leading to EU-IST Excellency, FP6,

9 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

10 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

11 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

12 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

13 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.

14 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

15 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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