From the scorching heatwave in Thessaloniki to the hottest research trends in learning and instruction at EARLI2023 – The LET Perspective

As we journeyed through the scorching heatwave on the streets of Thessaloniki to immerse ourselves in the hottest topics and trends of EARLI2023, our entire conference experience can be aptly summarized in one word – HOT. We had 16 junior and senior researchers from the LET lab present, who showcased their latest findings on how humans learn. However, in this blog post, we'll shift our focus away from our own presentations (you can find them all in EARLI Book of Abstracts or some of them on X (Twitter) using #LETgoesEARLI2023, #LETresearch, and #LETpeople hashtags) to share our insights on the most blazing trends and themes that EARLI2023 unveiled for the broader education research community. So, fasten your seatbelts and join us on this exhilarating ride!
Five persons sitting and chatting on orange armchairs a camera in the middle and two large screens in the background.

EARLI2023's central theme was "Education as a Hope in Uncertain Times” which delved into how, amidst global challenges such as technological advancements, socioeconomic shifts, and the ever-looming specter of the COVID-19 pandemic, education must evolve. This theme has brought together over 2500 presentations and researchers from around the world and featured an array of research topics spanning from learning analytics to regulation of learning, and from well-being to climate change. We all came to Thessaloniki with one aim – to ignite hope in these uncertain times. From LET Lab perspective, what captured our attention the most were three areas: the complexity of collaborative learning, the role and place of emotion and motivation in it, and the growing presence and role of advanced AI in education.

The complexity of collaborative learning

Prof. Crina Damsa's keynote presentation (link to YouTube) introduced a comprehensive perspective on collaborative learning that encompasses collaboration in its entirety – the "ecological approach". It highlights the relational nature of collaborative interactions – each individual brings in their individual traits, knowledge, and experience which they express through verbal and non-verbal interactions with each other and with the surrounding environment and the task.

To capture productive interactions in their entirety, it is important to utilize diverse data channels and methodologies. At LET Lab, this raised the discussion on the defining nature of the collaborative task, a question that remains largely underexplored in our field, and prompted us to ponder how this approach could be generally translated into practical educational strategies to prepare young generations for both the present and the future.

Exploring Emotion and Motivation in Learning

The series of presentations and keynotes focused on emotion and motivation in learning have naturally piqued our interest. We observed that there is still a significant gap in understanding how motivation and emotion manifest in collaborative learning settings. While we know that motivation and emotion play pivotal roles in influencing our learning behaviours, the wealth of research presented at EARLI2023 revealed that there is much more ground to cover in this area.

Harnessing advanced AI for better learning support

Research on leveraging advanced AI methods to enhance our understanding of and support for learning is still in its infancy compared to other fields. Learning is undeniably complex, and this complexity was a recurring theme in several conference sessions. The discussion revolved around the need to test theory through operationalization and test multiple theories against each other, highlighting the challenges and opportunities in this burgeoning field.

What we do here matters

These thought-provoking themes, among many others, fuel our daily discussions and research. Although we are not magicians in any way and cannot close all the gaps in the existing research on learning, our work does contribute to the latest scientific discussions in the field.

Our Hybrid Intelligence project, led by Prof. Sanna Järvelä and Prof. Guoying Zhao, is dedicated to addressing some of these open questions. We aim to bridge the gaps in current data-driven AI by fostering mutual understanding and co-evolution between humans and machines through the development of a metaverse. Our approach emphasizes multidisciplinary collaboration and ethical considerations, with a specific focus on enhancing human-machine interactions, particularly in fields like education and nursing, to enhance overall well-being and quality of life.

If you wish to learn more about our research and initiatives, follow our X account (Twitter), but also, please do not hesitate to reach out to us. Stay tuned for our next blog post as we continue to explore and share about the ever-evolving world of human learning.

See the EARLI Book of Abstracs


Learning and Learning Process
University of Oulu

Kateryna Zabolotna is a doctoral researcher at the LET Lab. Her dissertation explores how socially shared regulation of learning and knowledge construction interplay and support one another in various collaborative learning contexts.

Picture of Ridwan Whitehead with sungalsses
Learning and Learning Process
Learning and Educational Technologies Research Lab
University of Oulu

Ridwan Whitehead is a doctoral researcher at the LET Lab. His research investigates socially shared regulation of learning focusing on non-verbal interactions.