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Issue 1 - December 2012



December 2012

Issue 1

Welcome to the I-TUTOR project!


The Intelligent Tutoring for Lifelong Learning – I-TUTOR project aims at developing a multi-agent based 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.


Artificial Intelligence is a branch of computer science that focuses on the theory and development of computer systems able to perform tasks that normally require human intelligence, such as visual perception, speech recognition, decision-making, and translation between languages. In an appropriate educational setting, its application can boost interaction with learners, and improve the capacity of the learning system.



Teaching and tutoring in online education play a crucial role in supporting students and facilitating learning. Tasks teachers, trainers and tutors need to engage in include:

  • monitor, track and assess what the student does within the learning environment (i.e. pages and documents consulted/downloaded);
  • analyse students’ work;
  • manage knowledge sources by, for instance, building representations of knowledge through conceptual maps or taxonomies;
  • watch the network of formal and non-formal relationships as it develops within the class, fosters its strengthening and supports the inclusion of all individuals; and give formative evaluation and feedback.

With a small number of students this is relatively easy for tutors to do. However, for larger classes this quickly becomes unfeasible and there are dangers that the quality of the educational experience is seriously diminished. ICT can further support online teachers, trainers and tutors in assessing data to better individualize learning paths for students and enhance the learning experience.


The consortium aims to strengthen the integration and to foster the cooperation between educational and computer science disciplines to enhance the quality of distance education. The work includes:

  • Literature and case reviews of the educational use of artificial intelligence;
  • Design and development of the intelligent tutoring tool;
  • Rapid prototyping, users are active part of the development process;
  • Training of human tutors for piloting the developed tool.

The software is being developed in Java thus could be easily implemented and re-used in most of the common free platforms of eLearning. The pilots will be conducted using the LMS Moodle, and the concepts are directly applicable to the pedagogical use of online education.

collaborationPROJECT RESULTS

  • Literature review and case studies repertoire – already available!
  • Monitoring agent
  • Profiling agent
  • Alerting agent
  • Learning Design Agent
  • Visualisation agent
  • Chatbot – parts of it already available for testing!


The I-TUTOR Consortium is presenting the E-book “Intelligent tutoring system: an overview“

The report presents the outcomes of a large literature review and the implications of using intelligent tutoring systems in the European scenario. Topics include a historical excursus and a description of the ITS, from a pedagogical and didactical point of view; cognitive modeling (and classic modeling) used by informatics designers in the ITS construction; data mining in education, examining potentials and constraints in the use of data mining in education, summarizing the potential they have to offer meaningful support to stakeholders; literature review in order to summarise directions and research paths in the use of user-profiling, trying to define the main topics that should be considered in future research; and finally Instructional Design and the perspectives of the ITS research, dealing with the issue of educational design software.

Available to download for free.


The project is developing several agents that can be used in an AI tutoring system. At the moment as it is under development there is limited access to the different agents. However you are welcome to test the survey chatbot system. Although it still needs integration into Moodle, the code for running it is open sourced and available here.


Intelligent Tutoring Systems: New Challenges and Directions.

Video lecture by Cristina Conati, Department of Computer Science, University of British Columbia. Recorded in 2009. (appr. 60 min.)

About the lecture: „Can we devise educational systems that provide individualized instruction tailored to the needs of the individual learners, as many good teachers do? Intelligent Tutoring Systems is the interdisciplinary field that investigates this question by integrating research in Artificial Intelligence, Cognitive Science and Education. Successful intelligent tutoring systems have been deployed to support traditional problem solving activities by tailoring the instruction to the student's domain knowledge. In this talk, I will present a variety of projects that illustrate our efforts to extend the scope of intelligent tutors to both support novel forms of pedagogical interactions (e.g., example-based and exploration-based learning) and adapt to student's traits beyond knowledge (e.g., student's meta-cognitive abilities and affective states). I will discuss the challenges of this research, the results that we have achieved so far and future opportunities.”

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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