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Issue 2 - September 2013




September 2013

Issue 2

Intelligent Tutoring for Lifelong Learning – I-TUTOR project

The Intelligent Tutoring for Lifelong Learning – I-TUTOR project aims at developing a multi-agent based, user-friendly intelligent tutoring system to support online teachers, trainers, tutors and learners. The system is to be applied in open source learning environments, and will monitor, track, analyze and give formative assessment and feedback to students within the learning environment while giving input to tutors and teachers involved in distance learning to enhance their role during the process of teaching.The project is implemented by 7 partners in 4 EU countries (Greece, Hungary, Italy, and the UK)


Following up the development stage of the -TUTOR ITS, piloting is crucial in testing validity and identifying areas that need attention before the roll-out phase of the ITS application and prior to system-wide modifications. Therefore, a small scale piloting session has been launched in May 2013 for the first testing phase of the I-TUTOR plug-in prototype. This preliminary testing, which involves final users, both tutors/teachers and students in higher education, adult education and training, will allow to gather data to refine the plug-in toward its first release for publication.

The piloting sessions are taking place at the University of Macerata (Higher Education, Italy), at the Centre of Learning Innovation and Adult Learning of the University of Technology and Economics (Adult Education, Hungary) and at the ITEC Training Centre (VET training, Greece), involving about 80 students and 7 teachers/tutors.

Questionnaires and in-depth interviews will help developers and pedagogical partners to identify areas of improvement, and to enhance the plug-in: the first release for free download for Moodle users is expected for October 2013.

INVITATION TO I-TUTOR WORKSHOP: Artificial Intelligence and Learning: an Evolving Relationship

The I-TUTOR consortium, in cooperation with SIREM – Società Italiana di Ricerca sull'Educazione Mediale invites you to the I-TUTOR workshop at 13 November 2013 - University of Bari, Italy, In the frame of the SIREM conference

Online learning can significantly be supported by intelligent components, agents and systems, and dialogue between experts of learning and technology domains should be promoted and pursued, to enhance mutual understanding and the development of joint solutions.


collaborationThe call for papers aims at collecting experiences, cases, visions, approaches on artificial intelligence use in learning environments, having the following topics:

  • Intelligent Tutoring Systems
  • Profiling and clustering in Intelligent Tutoring Systems
  • AIED and social technologies
  • AIED between formal and informal learning
  • AIED and self-regulated learning


Abstract Submission Deadline: 19 Oct 2013

Final Paper Submission Deadline: 13 Nov 2013


Development issues: The alerting agent

What constitutes a situation where a user should be alerted? When would it be considered to be "rude" or annoying, and when would it be considered an "intervention"? It is a difficult balance to strike, and it is not an easy question. What indicators could be used? Or, is it at all possible to set indicators? Should the system be trained, e.g. through machine learning, to arrive at a sensible solution?






The I-TUTOR project team would like to show you the creative process behind the project work. We conducted short interviews with various contributors to offer you a unique view on the I-TUTOR development. Our first interview is with Dr. Karsten Lundquist from University of Reading, UK.

What is your role in the I-TUTOR project?

KarstenI am a Lecturer in Systems Engineering at the University of Reading (UoR), and I am the principle investigator from UoR within the I-TUTOR project. UoR has got several tasks within the project, however our primary work concentrates around the implementation of different tools. For instance we have made the statistical data mining aids and the chatbot system. We have also designed the website of the project.

What was your main interest in the project?

Personally I find it very interesting to investigating and designing AI tools within educational settings. Work has been done in the area, but not enough, and the possibilities of using these tools are plentiful. In the past many disregarded them because it is difficult to predict the benefits, but I think that a project like I-TUTOR allows us to look at this pragmatically. That is what is needed.

What did you find suprising, more complicated or easier than expected?

When developing data mining tools I always see myself as a "detective". I am investigating data to try and find common features or indeed outliers within the pool of data. We had some pools of data to begin with, however the structure of the data from the different pools were so significantly different that it was impossible to find commonalities. Educational data might be like that, due to the different styles of teaching/learning that happens in real life. Therefore many standard data mining tools could not be used to develop the I-TUTOR tools.

The pragmatic approach was then to create a tool that tutors and students can use to highlight the current situation that they find themselves in. This is what the statistical datamining tool aims to achieve. It was hard to get to that, because my personal hope was to utilise more AI techniques in this area.

What new questions arise while working on the project?

It would be interesting to investigate bigger educational data samples to see if the diversity is common across the sector, or if there are commonalities that could be identified at a higher level when investigating across the sector. However we are talking many data sources over several years. Such a project would have to be big, and involve many more partners than I-TUTOR has involved.

What do you think about the future of the results, what would you like to see as a continuation of the project?

I think that the pragmatic approach we have taken is a good approach that are producing tools that can be used in real educational settings. I am confident that they will be used. This in itself is a very good result. I would also like to see new research questions being addressed in future project. This is a fantastic research team, and it would be a shame not to continue the work that we have already achieved.


Development issues: Profiling

We are using clustering for two reasons. One, it is easy to understand for non-technical users. Two, it can work without any domain knowledge other than statistical knowledge. Furthermore we are only clustering on one dimension, e.g. number of chats or number or messages, not clustering on both chats and messages, however would it be fruitful to consider more dimensions?






Expert Insight: Eu Policies in Education and Training as well as Technology Enhanced Learning

Professor George Angelos Papadopoulos from the Department of Computer Science, University of Cyprus (Nicosia, Cyprus) is one of the external experts working on the I-TUTOR project. Part of his expert report on the e-book "Intelligent tutoring system: an overview" published by the project, he gave a valuable overview of some of the EU policies, related to education and training in general but also Technology Enhanced Learning in particular, which are relevant to the aims and scope of the I-TUTOR ITS.

He was kind enough to allow us to publish the relevant part, which you can download from our website.


What is AIED and why does Education need it?

Authors: Joshua Underwood and Rosemary Luckin, The London Knowledge Lab

A report for the UK's Teaching and Learning Research Programme Technology Enhanced Learning – Artificial Intelligence in Education Theme. May 2011.

Quote from the report: "Current research in AIED aims to develop more flexible systems that will increase access to effective, personalised and engaging, anytime, anywhere learning throughout lifetimes across the full range of knowledge domains and skills and employing varied pedagogic approaches. Realising this potential will certainly involve overcoming technical obstacles, but mainstreaming AIED into Education will also require much more. It will require the successful communication of the value of AIED research and systems. In particular, the role that AIED systems can play within the broader educational settings of their use and with respect to the other resources available to learners, such as teachers, peers and the physical features of the environment, must be more clearly explained. Cumming and McDougal (2000) suggested one key reason AIED had not been taken seriously in Education ten years ago was the use of insufficiently rich models of learning."



Gigliola Paviotti






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