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Land of Learning

Working Environment

Land of learning

The European Master in Comparative Urban Studies, for the online teaching, uses the software Land Of Learning (hereinafter also referred to as LOL). It is a platform for the delivery and use of web-based online e-learning services.
Its distinctive feature is the introduction of an innovative concept of INTERACTIVE CHAT (referred to as CLASSROOM).
Indeed, thanks to this new approach, courses or lessons develop on an active learning processes that only partially reflects the actual performance of a traditional face-to-face university lesson.
In this virtual Classroom it is possible to ask questions to the scholar,, to comment the lecture, to clarify doubts.
At the end of a lesson, it is immediately possible to download the transcription of the lesson in RTF format. In this way the users may recover the missed lessons any time.
Another major peculiarity of the Classroom made available by LOL is the presence of a REALTIME BLACKBOARD (the BLACKBOARD) on which users may draw (including in a free-hand operation) any object (be it image or text). The rest of the students in the classroom view all that is written thereon in real time.
The teacher may decide to integrate the transcription of a lesson with the Blackboard's context (e.g. slides, formulas, diagrams etc.) in order to increase the efficiency of the didactics.
For more information on LOL, please browse http://www.landoflearning.it/en/

 


Monitoring and Evaluation

Along the normal activities of the Master, a working group will be responsible for the monitoring and the evaluation of the learning activites. The main aim of this working group is twofold, on one side  it is to develop innovative methodologies for online teaching and learning (Learning with fun and Visual search Engine) on the other it is to monitor the communication flows among the participants to the online teaching and to assess their effectiveness. The working group will also monitor the impact of the inventive methodologies developed, implemented during the online teaching.

The working group has four distinct sectors of activities:

PORTFOLIO AND E-URBS

Portfolio (and its more common digital version, e-Portfolio) is an educational methodology in use in many advanced universities in Northern Europe and in the United States. It was developed to face growing demand for personalization of curricula, competence-focused learning and goal-oriented education. For this reason it is mostly applied in advanced courses, especially master programs. With Portfolio, a student can critically decide his/her goals in attending one particular MA course and, on the basis of this, build an ordinate archive of the most relevant materials encountered during the course. Portfolio is, in sum, a frame for self-reflection and strategic planning that has been found to be very useful for student, to deeply exploit the potential of a program for their personal and professional development.

Given the nature of the methodology, it seems that optimal results can be obtained in a goal-oriented course, such as a master program. Therefore, Portfolio will be used in the E-Urbs program. The following are the main reasons to do adopt this methodology:

  • Portfolio can add both perceived and real value to the program, by making it a goal-focused experience.
  • Portfolio provides E-Urbs  with an additional focus on competences,  making  the program  a better tool for professionally-oriented students.
  • Thanks to analysis of self-reflection documents by tutors, Portfolio represents a permanent overview on students'  learning needs.
  • Portfolio helps the students in building a very useful knowledge base by archiving documents on the basis of his/her professional goals.
  • Portfolio can make E-Urbs students  more competitive in the job-market, because of better awareness of their personal professional identity and by coherent and focused gaining of their knowledge and competences.

E-Urbs students will have a digital repository and proper tutorship to develop their own e-Portofolio on the platform already used for online teaching ("Land of learning"). On the basis of the eportfolio’s methodology, integrated in E-urbs structure, the student will be able to make strategic decisions to achieve his/her goals, identify the competences he/she has to focus on, receive feedback from peers and tutors on the development of these competences in practice. Partner Universities, though selected tutorship and innovative software programs (see section “learning with fun”) will support the students in these achievements not just during the duration of the classes,  but also during the last period of the student’s traineeship, giving him/her the possibility of working with public and private institutions.

 

LEARNING WITH FUN
Spontaneous community of learning and problem solving in virtual environments using gaming paradigms

The main objective of this research wants to be the understanding of the autonomous mechanisms ruling spontaneous communities and to find a relation between the social efficiency of the created relations and the capacity of building a learning culture. It will be also interesting to study the connections and the dependencies that the created relations have with the technical and social rules at the base of the community itself.

The main deliverable of the analysis will be relational and behavioral models describing the interactions happening in creating and managing the learning community.

Using the data collected by the system, we will be able to:

  • study both in qualitative and quantitative terms the social interactions enabling the creation and the persistency of the learning community
  • verify that the principles normally applied to the virtual communities are applicable to the learning communities (membership, identity, rituals, shared knowledge, successes and failures sharing)
  • describe and analyze implying the teaching/learning mechanisms and how this is influenced by the didactics of the online teachers and tutors
  • describe how much the learning of a new member is generated by auto-education, how much by help requests, how much by a silent observation of interactions among players with more experience
  • measure the level of knowledge reached by the members through the use of knowledge indexes and scales.

 

Visual Search Engine

A visual search engine will be made available within the e-learning platform to support content-based indexing and retrieval of large sets of digital images. The visual search engine will be applied to the Visual lab in order to provide “query-by-example” capabilities: Search criteria can be directly based on the content of the target image files rather than on their classification and textual description.

A visual query consists of an image (to be taken as en example) and a similarity metric. The results returned by the visual search engine consist of an ordered set of images sorted by reverse order of their similarity with the query image. The first result returned by the engine is the most similar image contained in the database, according to the given similarity metric. Query images can be uploaded by the user or directly taken from the database. Heterogeneous queries can also be issued by combining visual queries with textual and categorical search criteria.

Similarity metrics can also be used to induce an automatic classification of the set of images, or to extract the distinguishing features of a subset of images.

All similarity metrics will be made available to the users. The effectiveness of the search-by-example engine can be adapted to users’ needs by allowing each user to choose the  best combination of similarity metrics to be used as search criteria.

Moreover, artificial intelligence techniques will be used to grant to the system the capability of automatically learn from a training set (i.e., from a set of images manually classified by the user) the best settings of the search/classification criteria.

Online Questionnaires

On-line questionnaires will be used throughout the project for monitoring and evaluating the learning process and the satisfaction of the stakeholders. A Land of Learning plugin called Questionnaire Management Tool (QMT) will be used to this purpose.

In particular the QMT will be used to prepare and deliver the following questionnaires.

  1. Learning curve questionnaire: A questionnaire covering all the topics of the master, prepared with the contribution of all instructors. Each instructor will be asked to prepare a thematic set of questions in his/her own field of expertise. Learning-curve questionnaires will be automatically generated and delivered by randomly taking questions from each set.
  2. Self-evaluation tests: Thematic self-evaluation tests prepared by tutors and instructors and made available to the students within the e-learning platform.
  3. Evaluation tests: Questionnaires possibly used by tutors and instructors to evaluate the preparation of their students at the end of a specific teaching activity.
  4. Customer satisfaction questionnaires: Questionnaires used to monitor the perceived sense of community, the satisfaction of the stakeholders and the suitability of the proposed methodology.
  5. Learning style classification: Questionnaires used to infer the learning style of each student.

 

A QMT tutorial will be organized during the intense face-to-face course. Reports on the results of each questionnaire will be prepared and made available to the Monitoring and Evaluation WG.


E-learning
lol

 

News

16/05/2007 - New application form for 2007/08 available online. - view

eu
This Virtual Campus project has been funded with support from the European Commission (project number: 2005-3870 /001-001 ELE ELEB12). This web site reflects the views only of the authors, and the Commission cannot be held responsible for any use which may be made of the information contained therein.

 


 

 

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