E-CER: AI in Education
EARLI CENTRE FOR EXCELLENCE IN RESEARCH (E-CER)
(a) Project Details
Project Title: "AI in Learning and Instruction? Challenges, Opportunities, Transformations (AILI)"
- Roger Säljö, University of Gothenburg (chair)
- Andreas Gegenfurtner, University of Augsburg
- Jimmy Jaldemark, Mid Sweden University
- Lars Svensson, University West
- Johan Lundin, University of Gothenburg and University West
- Ylva Lindberg, Jönköping University
- Maarten de Laat, University of South Australia
- Marcus Specht, Technical University of Delft
- Sanna Järvelä, University of Oulu
- Sabine Seufert, University of St. Gallen
(b) Project Description
Currently, Artificial intelligence (AI) emerges simultaneously as an opportunity and a challenge to established traditions of learning and instruction. Even if AI has existed since the 1950s, technological development is intense. New sophisticated applications, which recently existed only in laboratories, are now on the market and quickly adopted and widely used. This development raises interesting and challenging questions for learning and instruction, as well as for research in these areas. One interesting element of this development is the role of such resources in supporting learning and instruction in formal and informal settings. Another interesting feature is what these resources will imply for assessment and what authoring an essay or scholarly text means.
Even if the most recent debate concerns chat-bots, notably CHAT GPT, the field of AI in learning and instruction is much broader and includes, among others, areas such as deep learning, machine learning and learning analytics. AI has the potential to automate administrative, instructional and learning tasks and, by that, unlock time available for complex analysis and discussions of human experiences and understandings of the world. AI can identify the strengths and weaknesses of an individual and, at the next stage, enable tailored content and learning activities. Another critical strand of AI research that needs further scrutiny points to the democratic and ethical challenges. The network comprises researchers from six countries and builds on a transdisciplinary base at the intersection of learning, instruction and digital technologies.
The network will meet twice a year, and during these meetings:
- Disseminate research results from earlier work focusing on results, which will result in the creation of joint AI projects
- Synthesize and critically analyse research and claims/predictions in research about how AI will be consequential for learning and instruction
- Work towards joint research applications from national/international funding agencies (from the start of the E-CER).
- Work with joint projects, including collaboratively collecting, analysing and interpreting data and discussing publication strategies
- Support ongoing work among doctoral candidates