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Zawartość zarchiwizowana w dniu 2024-06-18

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

Opis projektu


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.

Dziedzina nauki (EuroSciVoc)

Klasyfikacja projektów w serwisie CORDIS opiera się na wielojęzycznej taksonomii EuroSciVoc, obejmującej wszystkie dziedziny nauki, w oparciu o półautomatyczny proces bazujący na technikach przetwarzania języka naturalnego. Więcej informacji: Europejski Słownik Naukowy.

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Program(-y)

Wieloletnie programy finansowania, które określają priorytety Unii Europejskiej w obszarach badań naukowych i innowacji.

Temat(-y)

Zaproszenia do składania wniosków dzielą się na tematy. Każdy temat określa wybrany obszar lub wybrane zagadnienie, których powinny dotyczyć wnioski składane przez wnioskodawców. Opis tematu obejmuje jego szczegółowy zakres i oczekiwane oddziaływanie finansowanego projektu.

Zaproszenie do składania wniosków

Procedura zapraszania wnioskodawców do składania wniosków projektowych w celu uzyskania finansowania ze środków Unii Europejskiej.

FP7-ICT-2011-8
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System finansowania

Program finansowania (lub „rodzaj działania”) realizowany w ramach programu o wspólnych cechach. Określa zakres finansowania, stawkę zwrotu kosztów, szczegółowe kryteria oceny kwalifikowalności kosztów w celu ich finansowania oraz stosowanie uproszczonych form rozliczania kosztów, takich jak rozliczanie ryczałtowe.

CP - Collaborative project (generic)

Koordynator

STIFTUNG UNIVERSITAT HILDESHEIM
Wkład UE
€ 415 660,00
Adres
UNIVERSITATSPLATZ 1
31141 Hildesheim
Niemcy

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Region
Niedersachsen Hannover Hildesheim
Rodzaj działalności
Higher or Secondary Education Establishments
Linki
Koszt całkowity

Ogół kosztów poniesionych przez organizację w związku z uczestnictwem w projekcie. Obejmuje koszty bezpośrednie i pośrednie. Kwota stanowi część całkowitego budżetu projektu.

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