Project description
The ABCs of Generative AI in education
In today’s classrooms, Generative AI (GenAI) is increasingly playing a bigger role, but how it fits alongside teachers is not always clear. Teachers and students are still determining how to use AI tools in effective and responsible ways. It is not clear when and how GenAI can meaningfully improve learning. Because of this, schools often find it hard to use AI in an appropriate and impactful way. Supported by the Marie Skłodowska-Curie Actions programme, the LEARNGENAI project brings together experts from different fields to explore how GenAI can support teaching and learning. The project will create practical tools and advice to help schools use AI wisely, making learning more personal and flexible for students as education moves into the AI age.
Objective
Recent advancements in AI, specifically Generative AI (GenAI), have started to significantly impact how teaching and learning occur and how the respective institutions operate. GenAI will have to function in learning spaces and contexts alongside other activities. Therefore, it is expected that instruction and GenAI will complement each other and stand by each other. Yet, there is a limited understanding of how teachers/learners and AI interact, understand, respect, and learn from each other. The purpose of LEARNGENAI is to examine how GenAI is used and under which circumstances it has the potential to improve teaching and learning. The aim is to identify the critical success factors in a range of contexts, and use these findings to promote research and practice. Following an interdisciplinary approach that bridges the domains of computer science, pedagogy and educational sciences, teacher education, learning analytics, and learning theory, along with recent advances in technological tools and AI-based methods, the present project will explore how GenAI is effectively leveraged in education and attempt to isolate key success factors. Therefore, the main focus of the project will be to identify various strategies for implementing GenAI in learning and the success factors to support hybrid learning, understand how information sources, technological infrastructure and human skills and knowledge are ethically coalesced to achieve desired ends, and develop GenAI prototype applications and assess their impact in learning. By empirically investigating these issues and developing a framework of best practices, the ultimate goal is to guide educational institutions in their transition into the artificial intelligence era and enable them to enhance student experiences through personalized learning opportunities.
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: The European Science Vocabulary.
This project's classification has been human-validated.
CORDIS classifies projects with EuroSciVoc, a multilingual taxonomy of fields of science, through a semi-automatic process based on NLP techniques. See: The European Science Vocabulary.
This project's classification has been human-validated.
Keywords
Project’s keywords as indicated by the project coordinator. Not to be confused with the EuroSciVoc taxonomy (Fields of science)
Project’s keywords as indicated by the project coordinator. Not to be confused with the EuroSciVoc taxonomy (Fields of science)
Programme(s)
Multi-annual funding programmes that define the EU’s priorities for research and innovation.
Multi-annual funding programmes that define the EU’s priorities for research and innovation.
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HORIZON.1.2 - Marie Skłodowska-Curie Actions (MSCA)
MAIN PROGRAMME
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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.
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.
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.
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.
HORIZON-TMA-MSCA-PF-EF - HORIZON TMA MSCA Postdoctoral Fellowships - European Fellowships
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Call for proposal
Procedure for inviting applicants to submit project proposals, with the aim of receiving EU funding.
Procedure for inviting applicants to submit project proposals, with the aim of receiving EU funding.
(opens in new window) HORIZON-MSCA-2024-PF-01
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Net EU financial contribution. The sum of money that the participant receives, deducted by the EU contribution to its linked third party. It considers the distribution of the EU financial contribution between direct beneficiaries of the project and other types of participants, like third-party participants.
7491 Trondheim
Norway
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.