2. Macerata, where is?

4. E-Learning at Macerata University CELFI e-Learning centre provides resources and technologies supporting personalised, online/blended learning activities. 4 Faculties 17 Degree Programmes 1069 students 5 Postgraduate Masters 3 Postgraduate Courses 1420 students 2 Lifelong learning courses 1800 students Ph.D. programme in e-Learning and Knowledge Management 25 students Faculty of Law Faculty of Humanities and Philosophy Faculty of Educational Science Faculty of Political Science The department of Educational Science is responsible for research and development of advanced learning content.

5. Support centres CAIM - Centre for Informatics and Multimedia supports ICT-based learning through the implementation and maintenance of dedicated services and equipment providing a technological infrastructure to students, researchers, administrative and teaching staff. CELFI - e-Learning Centre supports and coordinates the progressive methodological and technical strengthening of teaching and learning processes based on ICT and multimedia. The Centre serves as a strategic resource for the integration of e-Learning technologies both in teacher didactics and in student activities. It manages e-Learning events and distance/frontal courses jointly with academic departments. CIEM Centre for Informatics, E-Learning and Multimedia 35 people 7 laboratories 410 workstations structured into two organisations

19. Online Learning Environment The conceptual artifacts (materials) are “ Boundary Objects ” connecting the three dimensions Self-Directed - Directed from Others Group - Individual 1 Instructional Activities 2 Collective and regulative activities 3 Reflective and personal activities Materials Materials Materials

23. Online Learning Environment 3 Self-Directed - Directed from Others Community - Personal Instructional Delivery, Test 1 Community of Practice, Knowledge 2 Management (elicitation, collaboration, regulation) Personal Learning Space, ePortfolio (identity, trajectories, learning, awareness) Communities of Practice Individual in the Community Tools for reflection and individual writing are predominant Tools for research, organization and collaboration are predominant Tools for selection, sharing and negotiation are predominant Materials are predominant Individual Learning with support Self-directed peer group Individual and Informal education Class and Formal education Reflection and Individual activities are predominant The attention to content and discipline is predominant

28. Personal page, blog Self introduction Personal blog

29. Learning unit entry page Activity introduction Study materials Forum discussion Suggested activities

30. Map, aggregation tool Simply drag & drop study materials to create node elements into map and document personal learning paths showing the activities carried out.

32. e-Portfolio

33. Circular model Students’ deliveries Evaluation Teacher-added materials Students’ notes, comments, reflections

34. Student activity monitoring Every activity / action is logged for group readings / writings. SNA graphs are dynamically generated.

44. ILE Architecture / Concept OLAT LMS - System Video Conference Subsystem OpenMeeting AI – ILE Subsystem LMS Authentication AI Interaction Agent AI Tutor Interface AI Knowledge Base LMS DB

45. LMS – ILE Environment LMS – ILE Environment Global Architecture of the ILE Platform

47. OLAT – ILE integration OLAT – ILE INTEGRATION ILE-AI Push/Pull Servlet ILE-AI LMS Communicator AI - Engine

49. AI – ILE “the Agent” Plug-ins Blackboard (Method for inter Agent Communication) Agent Publish (Push) Subscribe (Pull) Message Queue

50. AI – ILE Agent Framework System specific Variable Boundary Cougaar Agent Reference Model Framework Infrastructure Application domain specific component servic e BB Behavior effecter coordinator sensor component service servic e component library Agent BB Behavior effecter coordinator sensor component component service servic e library Agent Abstracted Environment

51. AI - Architectural Mapping Concept Sensor-Based Control Loop Model-Based Control Loop Cognitive Control Loop Model Policy Situation inference rules days to minutes secs to msecs Network Disk management plane data plane Sensor/ Activity Proxy Agents Real-time Optimizer Agents processing status coordination resource status coordination resource trends coordination Cognitive Learner Agents processing. trends coordination Situation Predictor Agents processing pattern coordination resource pattern coordination Sensor/Activity Proxy Agents Processing Units CPU

55. Thank you! Prof. Pier Giuseppe Rossi, director [email_address] Ing. Attilio Pedrazzoli, PhD professor [email_address]