e-learning at macerata university
TRANSCRIPT
e-Learninge-LearningPROVISION andPROVISION and
RESEARCHRESEARCH
University of Macerata
University of Macerata
Macerata, where is?Macerata, where is?
University of Macerata
SummarySummary• E-Learning at Macerata University
– WHO we are, WHAT we do– Focus areas, research areas
• Background– Pedagogical model– Technologies– Results– Future challenges
• ILE, Intelligent Learning Environment– Aims and objectives– Structure and technologies
University of Macerata
CELFI e-Learning centre provides CELFI e-Learning centre provides resources and technologies resources and technologies supporting personalised, supporting personalised, online/blended learning activities. online/blended learning activities.
44 Faculties
1717 Degree Programmes
10691069 students
55 Postgraduate Masters
33 Postgraduate Courses
14201420 students
22 Lifelong learning courses 1800 1800 students
Ph.D. programme Ph.D. programme in e-Learning and Knowledge Management
2525 students
E-Learning at Macerata E-Learning at Macerata UniversityUniversity
Faculty of LawFaculty of Law
Faculty of Humanities and Faculty of Humanities and Philosophy Philosophy
Faculty of Educational ScienceFaculty of Political Science
The department of Educational Science is responsible for research and development of advanced learning content.
University of Macerata
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 Multimedia35 people 7 laboratories 410 workstations
structured into two organisations
Support centresSupport centres
University of Macerata
CELFI CELFI activity AREASactivity AREASCELFI focus areasCELFI focus areas• Strategic, pedagogic and organisational modelling of
university’s online learning;• Teacher and online tutor training;• Faculties’ online learning environment setup;• Pedagogical models, research and organisation of
national and international conferences;• Coordination and development of international
project.
University of Macerata
CELFI and Ph.D. rCELFI and Ph.D. research esearch areasareas• Models for e-Learning;• Online environment design and e-Learning tools;• Knowledge Management and Ontologies for e-
Learning;• Semantic web and e-Learning; (mash up)• Multimedia and interactive video streaming;• e-Portfolio.
University of Macerata
Pedagogical Pedagogical modelmodelOur didactical approach enables a flexible, non-neutral pedagogical model
University of Macerata
AssumptionsAssumptions• Real world complexity and class heterogeneity
(cultural, motivational, etc.);• Different learning styles of students;• Different motivation and awareness;• Different teacher educational philosophies;• The importance of personal reflection and
awareness of own identity (individual activities next to personal spaces) (PLEs);
• To relate Formal and Informal education;• To make technology and didactics interacting.
University of Macerata
Theorical referencesTheorical references• Intersubjectivity and collaborative knowledge
construction (Wenger, 1998; Jonassen, 1999; Bereiter, 2002; Brown, 2005);
• Self, reflection and narration (Polanyi, 1967; Schon, 1983; Kolb, 1984; Perrenoud, 1996; Le Boterf, 2000; Gergen, 2001; Mezirow, 2003; Gruschka, 2005; Korthagen, 2006);
• Lifelong learning and professional competence construction(Samurçay e Pastré, 1995; Rabardel, 1995; Pastré,1997; Rogalski, 1997; Rey, 2003);
• Learning environment as cognitive domain(J.S. Brown, 2005, Jonassen, 2001);
• Artificial Intelligence and Intelligent Tutoring Systems (Newel, 1982; Clancey, 1993; VanLehn et al., 2005).
University of Macerata
Main elements for designMain elements for design• Fractal approach;• Enactive approach;• Significant e-tutor presence;• Central role of learning entities;• Flexible, non-neutral, three-dimensional online
learning environment.
University of Macerata
Fractal approachFractal approach• It allows, at design phase, to overcome restrictive
approaches and to set out for a situated design that is connected with the experience; this happens while keeping:– an internal coherence and a similar structure across the
various parts that soon become familiar to students;– autonomy of single levels that, even though they present
the same structure, consist of specific branches.
University of Macerata
Enactive approachEnactive approach• An approach where teacher-student-contest
relations allow for the creation of an environment, and the environment represent a snapshot of the community and its developed, shared knowledge;
• An environment that expresses relations developed between its components.
University of Macerata
Significant e-tutor presenceSignificant e-tutor presence• Each course is supervised by a professor and
managed by an online tutor possessing subject-matter and pedagogical competences; usual ratio e-tutor to students is 1/25;
• E-tutors’ tasks can be defined as follows:– Help and guidance: they operate on all subjects and
support students in cross-areas;– Subject-matter: they posses specific subject competences
as well as generic relational ones.
• E-tutors must attend a three-month training to gain relational competences focused on management of online student groups.
University of Macerata
E-tutors’ tasks, 1/2E-tutors’ tasks, 1/2• Student guidance and assistance;• Help students within specific subject-matter support
and guidance;• Constantly monitor student activities and progress;• Support teachers with course activity design;• Organise and develop study resources.
University of Macerata
E-tutors’ tasks, 2/2E-tutors’ tasks, 2/2• E-tutors are asked a great commitment towards:
– Student guidance and assistance in order to facilitate the creation of learning communities;
– Constant monitoring of student activities through the analysis of platform and specific activity logs.
• E-tutors enable the individualisation of learning paths and foster the creation of learning communities also through:– Interpretation of data from platform and activity logs;– Definition of different strategies that can be applied based
on multiple indicators.
University of Macerata
Learning entitiesLearning entities• A learning entity is represented by a single student as
well as a group or class; • In order to develop a community each module includes:
– A preliminary welcoming activity and continuous support allowing students’ positioning and personalisation of his learning paths;
– Collaborative activities that reveal the students’ personal experiences and allow to negotiate shared cognitive domains;
– Design activity and project work (in team).
– Personal reflection and awareness activities facilitating the creation of dynamic professional identities.
(diachronically)
University of Macerata
Three-dimensional modelThree-dimensional model
• The three macro dimensions:– Instructional dimension;– Collaborative and regulative dimension;– Personal and reflexive dimension.
• Each dimension is characterized by:– Different learning aims and objective typology;– Own activities and tools;– Specific monitoring & assessment tools.
University of Macerata
Online Learning EnvironmentOnline Learning Environment
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Group - Individual
1Instructional
Activities
2Collective and
regulative activities
3Reflective and
personal activities
Materials Materials
Materials
The conceptual artifacts (materials) are “Boundary Objects” connecting the three dimensions
University of Macerata
11stst – Instructional dimension – Instructional dimension
• Knowledge and skills acquisition;
• Media redundant materials; learning object; instructional delivery;
• Objective assessment (test).
University of Macerata
22ndnd – Collaborative and regulative – Collaborative and regulative dimensiondimension
• Knowledge building; problem-solving; activation of regolative processes;
• Activities such as knowledge sharing and negotiation, collaborative projects, case study, open-end problems; problem posing and decision making;
• Tools for qualitative analysis, Latent Semantic Analysis and Social Network Analysis.
University of Macerata
33rdrd – Personal dimension and e- – Personal dimension and e-PortfolioPortfolio
• Competence acquisition; identity awareness; reflection on own professional and personal identity;
• Personal selection and narration (blog); reflection tool; reflexive path; learning experience criss-crossings;
• e-Portfolio
University of Macerata
Online Learning EnvironmentOnline Learning Environment
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Community - Personal
Instructional Delivery, Test
1
Communityof Practice,
Knowledge 2Management
(elicitation, collaboration,regulation)
Personal LearningSpace,
ePortfolio(identity, trajectories,
learning, awareness)
Communities of PracticeIndividual in the Community
Tools for reflection and individual writing are predominant
Tools for research, organization and collaboration are predominant
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Individual and Informal education
Class and Form
al education
Reflection and Individual activities
are predominant
The attention to content and discipline
is predominant
3
University of Macerata
TechnologiesTechnologiesCoherence and processes of cross design between pedagogical and technological approaches
University of Macerata
TechnologiesTechnologiesCELFI uses different environments to suit different needs of online learning:1.Graduate courses: a custom-designed version of U-Portal jointly developed with the University of Udine. This infrastructure has been successfully used and regularly updated for four years.2.Post-grad courses: an in-house developed, ASP-based environment constantly undergoing modifications and improvements, used for the last four years also.3.Since last year other LMS platforms (Moodle, Dokeos, etc.) have been tested and experimented for minor or external courses
University of Macerata
Some examplesSome examples• Graduated, U-Portal based courses:
– Degree programmes in Educational Sciences http://celfi.unimc.it/sdf/(1)
• Post-graduated courses:– Master degree in “Educational Design”, attended by 196 teachers from
all across Italy (drop-outs: 2) during 2007-2008 http://zope.unimc.it/master/progetta(2)
– Master degree in “Open Distance Learning”, running since 2005 and attended by approx. 20 students every year http://celfi.unimc.it/odl/(3)
• Specialisation, Moodle-based courses:– Specialisation course for Online Tutors, attended by 70 grad students
during 2007-2008http://celfi.unimc.it/moodle(4)
– Specialisation course for the Ministry of Health attended by 1007 health-workershttp://www.eduiss.it/fad/(5)
University of Macerata
Different technologies, same Different technologies, same modelmodelWe keep the same pedagogical approach in each learning environment we deploy; for this reason every LMS includes:
– Personal page;– Modular structure, easily editable by teachers and tutors;– Dispositifs for negotiation featuring indented forums;– Dispositifs for collaborative writing;– Dispositifs for learning path reflection;– Dispositifs for the construction of maps and patchworks;– e-Portfolio for personal reflection, awareness and learning
path documentation.
University of Macerata
Personal page, blogPersonal page, blog
Self introduction
Personal blog
University of Macerata
Learning unit entry pageLearning unit entry page
Activity introduction
Study materials
Forum discussionSuggested activities
University of Macerata
Map, aggregation toolMap, aggregation toolSimply drag & drop study materials to create node elements into map and document personal learning paths showing the activities carried out.
University of Macerata
MultimediaMultimedia• The synchronization (the our evolution)
– http://flash1-bo1.unimc.it/streamings/masterODL/rossi/rossi_pres_mod1
– http://flash1-bo1.unimc.it/streamings/sp/AA0708/Gioia_SPE_05/
– http://flash1-bo1.unimc.it/streamings/bcn_expoel2008/presentation/
– http://flash1-bo1.unimc.it/streamings/smt/lesson2-demo
• The Multimedia author– http://celfi.unimc.it/progetta – http://celfi.unimc.it/lab07 pat altet
University of Macerata
e-Portfolioe-Portfolio
University of Macerata
Circular modelCircular model
Students’ deliveries
Evaluation
Teacher-added
materials
Students’ notes, comments, reflections
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Student activity monitoringStudent activity monitoringEvery activity / action is logged for group readings / writings.
SNA graphs are dynamically generated.
University of Macerata
ResultsResults• Increase of enrolments: 100% within last three years;• Increase of teacher involvement (30% - 70% dependent
on the faculty) with online learning and great impact of acquired knowledge on face-to-face teaching activity;
• Overall quality improvement through certification by EU-funded UNIQUe accreditation;
• Increase of incoming requests for the provision of Lifelong Learning by Italian Ministries (Health, Internal Affairs);
• Participation in European Initiatives involved with e-Learning (e.g. Streaming Media Training).
University of Macerata
Future challenges, 1/2Future challenges, 1/2• University’s 3-year development plan includes:
– Online students enrolment increase from 9% to 15%;– Increase e-Course offering and number of faculties involved
in online learning;– Improve overall teaching quality of online learning;– Enhance integration of ICT with face-to-face learning;– Expand participation in international project aimed at
technological and pedagogical research focused on e-Learning and Knowledge Management.
University of Macerata
Future challenges, 2/2Future challenges, 2/2• In order to achieve the University’s goals we have
identified three objectives:– Personalisation of LMS and individualisation of learning paths;– Improve competences of teachers and e-tutors;– Flexibility and autopoiesis of the learning environment.
Autopoiesis literally means "auto (self)-creation" (from the Greek: auto – αυτό for self- and poiesis – ποίησις for creation or production), and expresses a fundamental dialectic between structure and function. (Source: Wikipedia)
University of Macerata
I.L.E.I.L.E.Intelligent Intelligent LearningLearningEnvironmentEnvironmentIn 2007 a new learning envinronment project was initiated in order to improve quality of online learning while supporting professors and e-tutors in their day-to-day activities
University of Macerata
From today’s ITS…From today’s ITS…• Intelligent Tutoring System (ITS) models and
experiences:– Dick and Carey (1990);– Beck and Stern (1996);– ANDES, VanLehn (2005);– Baghera, Webber (2005);
• ITS systems are subject matter oriented e and foresee an very specialized subject specific, rigid interaction;
• Need for general purpose, subject matter independent implementation, aimed primarily as a professional support tool for professors and e-tutors. It should relief e-tutors from 1st level learning entity support activities.
University of Macerata
……to ILE to ILE • The Intelligent Learning Environment is based on a
pedagogical didactical domain;• Semantic indicators supply a mapping of addressed content,
issues discussed or elaborated;• Provide in real time a mapping of the elaborated activity, the
acquired knowhow of the learning entity (student, group or community);
• Supply a mapping of established relations in a given community;
• Suggests appropriate didactical strategies to professors and/or e-tutors to individualise and personalise given learning paths;
• Constant monitoring of learning entities (LE) (student, group or community).
University of Macerata
ILE CharacteristicsILE Characteristics• Communicate with a given LMS platform via Agents
according to predefined rules and actions;• Agents with “profile based subject matter“ expert
knowledge;• Relief e-tutors from 1st level “subject matter“ tutoring
activity;• Support students / work groups (LE) with 1st level, subject
matter tutoring;• Interpret the “tutoring role” according to:
– Knowledge / subject matter profile;– Pedagogical profile in conjunction with the LE profile ;
• ILE – AI engine input:– LMS tracking data;– LSA, or any type of interpretable system, external input;– Profiles;– Manual intervention from Experts, Tutors etc.
University of Macerata
ILE tutoring conceptILE tutoring conceptBase parameters for monitoring:• Profile of learning entities;• Advanced activity logging / tracking;• Use semiotic-semantic indicators for
interaction analysis;• Use of tagging and LSA;• Use indicators of the Social Network
Analysis (SNA).
Base of didactical knowhow:
•Wide range of models and learning dispositifs;•Models and dispositifs for collaborative knowledge construction;•Models and dispositifs for reflection and awareness of learning.
1st level student support: reduction of e-tutor load2nd level student support: relieve of e-tutor load
University of Macerata
Evaluation of LMS platform Evaluation of LMS platform for ILEfor ILERequested characteristic for the LMS:• Pedagogical flexibility;• Adequate tools for group activities;• State of the art usability and ease of use for authors;• Clear mapping of learning path structure based on XML;• Developed for scalability, portability, interoperability;• Open source/architecture for future or specific case oriented
extensions.
OLAT Version 6 from the University of Zurich was selected as LMS platform for the ILE Project
University of Macerata
ILE Architecture / ConceptILE Architecture / Concept
OLAT OLAT LMS - SystemLMS - System
Video ConferenceVideo ConferenceSubsystemSubsystem
OpenMeetingOpenMeeting
AI – ILEAI – ILESubsystemSubsystem
LMS AuthenticationLMS Authentication
AI AI Interaction AgentInteraction Agent
AI AI Tutor Tutor
InterfaceInterfaceAI AI
Knowledge BaseKnowledge Base
LMS DBLMS DB
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LMS – ILE LMS – ILE EnvironmentEnvironment
ILE AUTHORING ENVIRONMENT
OLAT LMS PLATFORM
DB OLAT 6
ILE Engine
LE / Student Agent
Knowledgebase Agent
Presentation Agent
Pedagogical Agent
Coach/Tutoring Admin.ILE Middleware
KnowledgeDB
ProfileDB
AIRules DB
E-ContentSimplified Authoring
toolset
AIML / UMLUtilities
AI ILEAuthoring
Offline simulationTest utilities
Global Architecture of the ILE PlatformGlobal Architecture of the ILE Platform
LMS – ILE EnvironmentLMS – ILE Environment
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LMS – ILE LMS – ILE EnvironmentEnvironment
OLAT Java based LMS performing functions like:• Student , Teacher, Authors administration• Group administration• E-Course administration• General access control• Global community functions like Forum,
Wiki, Blog• Extended tailored functions like e-Portfolio
etc.
AI coaching / tutoring Engine• Learning entity Agent (real-time
student / group profiler)• Curriculum Subagent (generating and
adapting learner curriculum)• Knowledge base Agent (subject matter
related)• Pedagogical profiler• Coach / Tutoring Subagent• Subject matter profiler• Presentation Agent (Dynamic session
initiator)• Pedagogical Agent• Coaching/Tutoring administrator Agent
Authoring Middleware• AIML / UML / SOAP utilities• AI ILE Authoring tools• Global Knowledgebase management
utilities• Standalone e-Course development
environment• AI simulation / Test utilities
ILE Components
LMS – ILE EnvironmentLMS – ILE Environment
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OLAT – ILE OLAT – ILE INTEGRATIONINTEGRATIONILE-AI Push/Pull
Servlet
ILE-AI LMS Communicator
AI - Engine
OLAT – ILE integrationOLAT – ILE integration
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LMS – ILE Design issuesLMS – ILE Design issues• Static Design Static Design strives for a
simple, elegant, efficient solution to a single situation.
Outside of that situation the design is useless
• AdaptationAdaptation strives to just survive in a constantly changing situation.
Adaptation is continuously making design decisions
Requirements
Design
Implement
Test
Water Fall Design Process Water Fall Design Process
ImplImpl
Adaptive Control Loop Adaptive Control Loop
ImplementationLoads
Capacity Cost
QoS
AdaptiveControl
Policy
Conditions Conditions
LMS – ILE design issuesLMS – ILE design issues
University of Macerata
Plug-ins
Blackboard (Method for inter Agent Communication)
Agent
Publish (Push) Subscribe (Pull)
Message Queue
AI – ILE “the Agent”AI – ILE “the Agent”
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componentcomponent
service
BBBB
BehaviorBehavior
effectereffecter coordinator
coordinatorsensorsensor
componentcomponent
service service
componentcomponent
librarylibrary
Agent
BBBB
BehaviorBehavior
effectereffecter
coordinator
coordinator sensorsensor
componentcomponent componentcomponent
serviceservice
librarylibrary
Agent
Abstracted Environment
Systemspecific
VariableBoundary
Cougaar Agent Reference Model FrameworkCougaar Agent Reference Model Framework
Infrastructure
Applicationdomainspecific
AI – ILE Agent FrameworkAI – ILE Agent Framework
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Sensor-BasedControl Loop
Model-BasedControl Loop
CognitiveControl Loop
Model PolicySituation
inference rules
days to minutes secs to msecs
NetworkNetwork DiskDisk
management plane data plane
Sensor/ ActivityProxy
Agents
Sensor/ ActivityProxy
Agents
Real-timeOptimizer
Agents
Real-timeOptimizer
Agents
processing statuscoordination
resource statuscoordination
resource trendscoordination
CognitiveLearnerAgents
CognitiveLearnerAgents
processing. trendscoordination
SituationPredictorAgents
SituationPredictorAgents
processing patterncoordination
resource patterncoordination
Sensor/ActivityProxy
Agents
Sensor/ActivityProxy
Agents
ProcessingUnits
CPUCPU
AI - Architectural Mapping AI - Architectural Mapping ConceptConcept
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Cougaar1. Agent societies2. Cougaar environment3. Agent coordination4. Transitioning of control
loops human to automation
architectural mapping
Application 1. Functional modules (oval shaped)2. Underlying distributed environment3. Sensor / Activity to control loop
coordination4. Evolving degree of human
involvement
AI - Architectural MappingAI - Architectural Mapping
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Agent AgentCoordination
Artifact(CA)
Agent AgentShared stateShared state
Defines rolesDefines roles
Role-playersRole-players
Coordination Artifacts (CA’s) – Are first-class entities in MAS– Define explicit roles for role-players (Profiles)– Offer shared state between the role-player & the CA– Coordinate behavior among role-players– Designed and implemented as distributed, scalable implementation
ILE – AI Environment ConceptILE – AI Environment Concept
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Summary ILE PlatformSummary ILE Platform• Considered as a “Intelligent Support Tool” for Tutors and
Learning Entities;• Act’s according to predefined profiles;• Relief Tutors from 1st level “ subject matter “ tutoring
activity;• Support students / work groups (LE) with 1st level subject
matter tutoring;• 1st level tutoring is proposed in “friendly suggestion
mode”, logged in the LE course activity log files;• Leaves Authors the “didactical Freedom”;• Allows a “tailored, adaptable learning path”;• Proposed ILE-AI actions are always confirmed and
initiated by the “human tutor”.
University of Macerata
Thank you!Thank you!Prof. Pier Giuseppe Rossi, director [email protected]
Ing. Attilio Pedrazzoli, PhD professor