Skip to main content
Go to the home page of the European Commission (opens in new window)
English English
CORDIS - EU research results
CORDIS
Content archived on 2024-06-18

Talk, Tutor, Explore, Learn: Intelligent Tutoring and Exploration for Robust Learning

Project description


Technology-enhanced learning
iTalk2Learn platform enables learners to communicate and interact more naturally via rich intuitive user interfaces leveraging direct manipulation and, in particular, natural language user interfaces.

iTalk2Learn project (The Intelligent Tutoring and Exploration for Robust Learning) project aims to facilitate robust learning by creating a platform for intelligent support that combines structured learning with exploratory learning activities and applies cognitive models of the learning behaviour of students in elementary education.

In the aftermath of the PISA studies, which identified weaknesses of students in many European countries, especially in mathematics, the education of children in the elementary school grades has received a lot of attention. Yet, most learning systems that have been developed for mathematics education have two significant limitations: first, they are usually constrained to text-based interactions and are thus hard to use by young learners (6 to 11-year-olds) who are still perfecting their basic literacy skills. Second, support is rarely tailored to the children’s needs in an adaptive fashion, even though depending on the current stage of the learning process, the support that children need varies between structured practice and more exploratory, conceptually-oriented learning.

Relying on state-of-the-art machine learning methods, iTalk2Learn intelligent components will be able to provide adaptive feedback — e.g. praise or hints —and suggest subsequent tasks. The platform will enable learners to communicate and interact more naturally via rich intuitive user interfaces leveraging direct manipulation and, in particular, natural language user interfaces. The pedagogical and technological outcomes of the project will be evaluated in two proven application scenarios in two European languages.The project proposes to perform interdisciplinary, cutting-edge research in a multidisciplinary team with members from fields as diverse as artificial intelligence/machine learning, user modelling, intelligent tutoring systems, and natural language processing, as well as educational psychology and mathematics education.

In the aftermath of the PISA studies, which identified weaknesses of students in many European countries, especially in mathematics, the education of children in the elementary school grades has received a lot of attention. Yet, most learning systems that have been developed for mathematics education have two significant limitations: first, they are usually constrained to text-based interactions and are thus hard to use by young learners (6 to 11-year-olds) who are still perfecting their basic literacy skills. Second, support is rarely tailored to the children's needs in an adaptive fashion, even though depending on the current stage of the learning process, the support that children need varies between structured practice and more exploratory, conceptually-oriented learning.
The Intelligent Tutoring and Exploration for Robust Learning project aims to facilitate robust learning by creating a platform for intelligent support that combines structured learning with exploratory learning activities and applies cognitive models of the learning behaviour of students in elementary education. Relying on state-of-the-art machine learning methods, intelligent components will be able to provide adaptive feedback -- e.g. praise or hints --and suggest subsequent tasks. The platform will enable learners to communicate and interact more naturally via rich intuitive user interfaces leveraging direct manipulation and, in particular, natural language user interfaces. The pedagogical and technological outcomes of the project will be evaluated in two proven application scenarios in two European languages.
The project proposes to perform interdisciplinary, cutting-edge research in a multidisciplinary team with members from fields as diverse as artificial intelligence/machine learning, user modelling, intelligent tutoring systems, and natural language processing, as well as educational psychology and mathematics education.

Fields of science (EuroSciVoc)

CORDIS classifies projects with EuroSciVoc, a multilingual taxonomy of fields of science, through a semi-automatic process based on NLP techniques. See: https://op.europa.eu/en/web/eu-vocabularies/euroscivoc.

You need to log in or register to use this function

Programme(s)

Multi-annual funding programmes that define the EU’s priorities for research and innovation.

Topic(s)

Calls for proposals are divided into topics. A topic defines a specific subject or area for which applicants can submit proposals. The description of a topic comprises its specific scope and the expected impact of the funded project.

Call for proposal

Procedure for inviting applicants to submit project proposals, with the aim of receiving EU funding.

FP7-ICT-2011-8
See other projects for this call

Funding Scheme

Funding scheme (or “Type of Action”) inside a programme with common features. It specifies: the scope of what is funded; the reimbursement rate; specific evaluation criteria to qualify for funding; and the use of simplified forms of costs like lump sums.

CP - Collaborative project (generic)

Coordinator

STIFTUNG UNIVERSITAT HILDESHEIM
EU contribution
€ 415 660,00
Address
UNIVERSITATSPLATZ 1
31141 Hildesheim
Germany

See on map

Region
Niedersachsen Hannover Hildesheim
Activity type
Higher or Secondary Education Establishments
Links
Total cost

The total costs incurred by this organisation to participate in the project, including direct and indirect costs. This amount is a subset of the overall project budget.

No data

Participants (7)

My booklet 0 0