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MIC 2008, Roma Tommaso Leo E-learning for institutional and continuous education in technical-scientific domains UNIVERSITA’ POLITECNICA DELLE MARCHE Tommaso.

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Presentation on theme: "MIC 2008, Roma Tommaso Leo E-learning for institutional and continuous education in technical-scientific domains UNIVERSITA’ POLITECNICA DELLE MARCHE Tommaso."— Presentation transcript:

1 MIC 2008, Roma Tommaso Leo E-learning for institutional and continuous education in technical-scientific domains UNIVERSITA’ POLITECNICA DELLE MARCHE Tommaso Leo MIC-2008-Roma dipartimento di ingegneria informatica, gestionale e dell’automazione

2 MIC 2008, Roma Tommaso Leo 1 LIST OF TOPICS TECHNICAL SCIENTIFIC DOMAIN COMPLEX SYSTEMS MATERIAL KNOWLEDGE CHARACTERS OF THE MATERIAL KNOWLEDGE DOMAIN RELEVANT PEDAGOGICAL MODELS DIDACTIC DIMENSIONS OF TEACHING/LEARNING MK RELEVANT DIDACTIC VARIABLES DIDACTIC FUNCTIONALITIES REQUIRED TO A LCMS

3 MIC 2008, Roma Tommaso Leo 1. TECHNICAL SCIENTIFIC DOMAIN Engineering, in particular Electronic and Electrical Engineering, Control Engineering, Industrial Engineering. The key professional activity is aimed at designing and operating man- made systems that can be considered Complex Systems.

4 MIC 2008, Roma Tommaso Leo 2. COMPLEX SYSTEMS Attributes Descriptive attributes: - High number of components/subsystems; - Integration of different technologies - Integration of different methods - Interaction with human beings/living organisms - Operation dependent on the environment and initial conditions - Complex and articulated design procedures

5 MIC 2008, Roma Tommaso Leo 2. COMPLEX SYSTEMS Attributes Formal/conceptual attributes - High level of uncertainty/unpredictability - Behaviour and experiments are substantially not reproducible

6 MIC 2008, Roma Tommaso Leo 3. MATERIAL KNOWLEDGE Roughly speaking, it is the Knowledge relative to the real operation conditions of engineering complex systems.

7 MIC 2008, Roma Tommaso Leo Attributes - In general the owners are experts - In general it is implicit, even intuitive - In general it is empirical - To communicate MK is an ill defined problem-space - To be communicated, MK implies, at least Case-based reasoning Problem-driven reasoning 3. MATERIAL KNOWLEDGE

8 MIC 2008, Roma Tommaso Leo Suggestions “experiential paths” by means of social interaction between experts, novices and learning resources 3. MATERIAL KNOWLEDGE

9 MIC 2008, Roma Tommaso Leo Criteria to select the expert - long history of practice with the relevant problems, at least longer than the novice; - capability of autonomous operation in solving the relevant problems to set up the problem, to select the key elements for the solution, to find the proper coworkers - recognized high level of competence. 3. MATERIAL KNOWLEDGE

10 MIC 2008, Roma Tommaso Leo 4. CARACHTERS OF THE MATERIAL KNOWLEDGE DOMAIN A practical reference is the environment of a laboratory dealing with Automatic Control Systems, or a Radar settlement for Air Traffic Control.

11 MIC 2008, Roma Tommaso Leo PROGETTO TIGER Carla Falsetti David Fabri Sulmana Ramazzotti Tommaso Leo Cira 2005 UNIVERSITA’ POLITECNICA DELLE MARCHE Tommaso Leo

12 MIC 2008, Roma Tommaso Leo Schema a blocchi 7. TELELABORATORIO IMMERSIVO Tommaso Leo

13 MIC 2008, Roma Tommaso Leo 4. CARACHTERS OF THE MATERIAL KNOWLEDGE DOMAIN didactic resources we think about : - logical/formal resources, - resources allowing procedural skills learning, - resources preparing to synthesize heterogeneous competences, even acquired in different lateral contexts and Knowledge domains, - resources aimed to train for team working and/or team leading of heterogeneous components

14 MIC 2008, Roma Tommaso Leo 5. RELEVANT PEDAGOGICAL MODELS The adoption of number of different pedagogical models/ didactic approaches, properly combined in a suitable mix, is advisable.

15 MIC 2008, Roma Tommaso Leo 5. RELEVANT PEDAGOGICAL MODELS Pedagogical models/didactic approaches - didactic approaches able to facilitate memory retention, - pedagogical approaches deriving from constructionism, where reflection is dominant, - constructivism, where experiential dimension is prevalent, - pedagogical approaches where cooperative and collaborative work and social tagging is prevalent.

16 MIC 2008, Roma Tommaso Leo 6. DIDACTIC DIMENSIONS OF TEACHING/LEARNING MK The “ Didactic situation” has to be related to the knowledge domain to be learnt. In our case we can speak about problem solving for unstructured and ill posed problems, even if the problems are based on solid physics and mathematics ground.

17 MIC 2008, Roma Tommaso Leo 6. DIDACTIC DIMENSIONS OF TEACHING/LEARNING MK Dimensions of the teaching/learning process : - Topics and contents to be learnt ( “ what” dimension) - Didactic and pedagogical approaches (“ how” dimension) - Contents order and availability at the proper time (“ when” dimension) - Connections and relationships among and within the three dimensions above (“ the meanings network”), to attain a comprehensive understanding of the matter.

18 MIC 2008, Roma Tommaso Leo 6. DIDACTIC DIMENSIONS OF TEACHING/LEARNING MK Characters of dimensions can be organized w.r.t.: -Learning goals and learning evaluation ( “application” and “ evaluation” level of the Bloom taxonomy). -Learning goals vs. target users: application level for undergraduate students, evaluation level for second and tertiary level students and continuous education; -The need of embedding learning within the physical and perceivable world ( Immersivity, ability to handle physical artefacts and phenomena).

19 MIC 2008, Roma Tommaso Leo 7. RELEVANT DIDACTIC VARIABLES They are here, meant as “those allowing a modification in the learners’ behaviour”

20 MIC 2008, Roma Tommaso Leo 7. RELEVANT DIDACTIC VARIABLES In the “what” and “how” dimensions Didactic variables relevant for learning management/organisation -1/2 -a Syllabus i.e. a clear definition of contents and pedagogical modalities, specification of the input competence level, to allow the personalisation of the learning process. - clear definition and specification of the assessment modalities. - implementation of “adaptivity” of contents at the system side;

21 MIC 2008, Roma Tommaso Leo 7. RELEVANT DIDACTIC VARIABLES In the “what” and “how” dimensions Didactic variables relevant for learning management/organisation -2/2 - implementation of “adaptivity” at the learner model side; - automatic updating of the user profile; - proposing to the user a specific “learning experience”, coherent with his/her current profile and with the current availability of learning resources (both LO and learning artefacts).

22 MIC 2008, Roma Tommaso Leo 7. RELEVANT DIDACTIC VARIABLES In the “what” and “how” dimensions Didactic variables relevant for learning support -availability of learning resources aimed at experiential and collaborative learning. Depending on the knowledge domain and user target, the proper communication codes have to be defined.

23 MIC 2008, Roma Tommaso Leo 7. RELEVANT DIDACTIC VARIABLES In the “when” and “meanings network” dimensions Didactic variables relevant for the learning management/organisation -adaptivity of contents. Adaptivity is here meant as more or less detailed and more or less in depth presentation, according to the current needs of the user. -Adaptivity of the learning path to the learner needs and attitudes -E portfolio

24 MIC 2008, Roma Tommaso Leo 7. RELEVANT DIDACTIC VARIABLES In the “when” and “meanings network” dimensions Didactic variables relevant for learning support - number of assessment tools, mainly aimed to formative evaluation. In our case, tests, supervised problem-solving like, would be desirable.

25 MIC 2008, Roma Tommaso Leo 8. DIDACTIC FUNCTIONALITIES REQUIRED TO A LCMS Moodle seems particularly oriented to a structured path of learning. It would be useful to integrate into Moodle, or to add to Moodle some modules implementing the following functionalities

26 MIC 2008, Roma Tommaso Leo 8. DIDACTIC FUNCTIONALITIES REQUIRED TO A LCMS - Experiential and collaborative learning through Immersivity: Web services, allowing immersive telelaboratory experiences, - learning and knowledge development monitoring and evaluation: -to strengthen the tools already existing with the elaboration and integration of available data ; - adding automatic, or semi-automatic evaluation of the communicative interactions ; - Would it be advisable to add social network facilities to allow the environment to manage both formal and informal learning?

27 MIC 2008, Roma Tommaso Leo Credits and Aknowledgements - Graphic editing: Sulmana Ramazzotti Ph D -Many tanks are due for discussion and advice to -Prof. Kinshuk -Prof. Nian Shing Chen - My students of the PhD course in e.-learning

28 MIC 2008, Roma Tommaso Leo Thank you


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