About the project
AI-EXCAfL (Artificial Intelligence for Enhanced Cross-disciplinary Assessment for Learning) is an interdisciplinary research project that develops AI-based assessment technology (FAS) to support formative and summative assessment of student writing. The project explores how the technology can contribute to students' writing development and their ability to learn how to learn, as well as how teachers organise assessment for learning (AfL) with and without the use of AI. FAS provides automatic, individually tailored feedback across four subjects: English, Norwegian, Science, and Social Studies. The aim is to enhance the quality of education, develop AI competence among both teachers and students, and strengthen the research-based use of digital assessment methods in secondary schools. The project combines insights from pedagogy and technology and involves researchers, developers, teachers, and students in design-based interventions.
Project period
1.4.2025-31.3.2029
Project type
Collaborative and Knowledge-building Project
Objectives
AI-EXCAfL aims to develop and implement an AI-based assessment technology (FAS) that provides automatic, individually tailored feedback on student writing in four subjects: English, Norwegian, Science, and Social Studies. The project will:
Investigate how students use AI technology in writing processes and what impact this has on their learning.
Explore how teachers organise and adapt assessment for learning (AfL) with the support of AI, and which pedagogical practices promote students' writing and reflection.
Contribute to building knowledge on how AI can enhance students' ability to learn how to learn and support the development of teachers' professional digital competence, including AI literacy.
Develop new theory and methodology on how AI-based assessment can contribute to quality development in education.
The project combines pedagogical research and technological innovation through interdisciplinary collaboration and design-based interventions.
Funding
The project is funded by the Research Council of Norway.
Partners
University of South-Eastern Norway
Akademiet Norge AS
Bit for Bit AS
