University “Politehnica” of Bucharest

1. University “Politehnica” of Bucharest Artificial Intelligence and Multi-Agent Systems Laboratory http://turing.cs.pub.ro/ai_mas

2. 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

3. 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

4. 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

5. 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

6. AI-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. 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. I-TRACE PROJECT, 1st Partners Meeting, Catania, November 25-26, 2005 Some projects • 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

9. One of our current projects • Research on emotional agents • 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. 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. 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. Learning styles • 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).

13. I-TRACE PROJECT, 1st Partners Meeting, Catania, November 25-26, 2005 Learning styles • Active learners understand new information by doing something with it. • Reflective learners prefer to think about new information first before acting on it. • Intuitive learners prefer discovering new relationships and can be innovative in their approach to problem solving. • Sensing learners like learning facts and solving problems by well established methods. • Verbal learners understand new information best through written and spoken words. • 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. • 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. Mind maps • 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 (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. 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.