Sanna Järvelä: AI should strengthen the learner’s own agency
Learning is a regenerative process
Professor Sanna Järvelä’s background is in learning sciences, a field of study which combines multidisciplinary knowledge to understand learning.
Within her field of study, the GenZ co-evolution theme has been brought through all the time. According to Järvelä, new, developing technologies can shed light on the complexities of learning processes, which are otherwise difficult to measure. In addition to that, Järvelä is also interested in how technologies can bring support at the different stages of learning, thus enriching human competences.
Topic wise, Järvelä and her research group are interested in phenomena such as computer supported collaborative learning, and more recently, using Artificial Intelligence (AI) to aid learning.
“The reason for my interest in learning is that I believe that learning is a necessary element of regeneration – the creation of something new. Learning in school helps pupils to absorb the essential skills needed later in life, but learning is also a continuous, lifelong process that happens outside of school as well,” Järvelä says.
Within the study of learning, Järvelä is not interested in what is learned, but rather how learning happens. According to Järvelä, learning is a process that involves intertwining cognitive, motivational and emotional aspects. Technologies, in turn, can be brought on the side to understand, support, and enrich this intricate process of learning.
Developing a new theory
Järvelä names the methodological work with LeaF Research Infrastructure as one of her team’s most significant accomplishments. LeaF is the University of Oulu’s research facility designed for carrying out multidisciplinary research specifically pertaining to learning and interaction.
In the LeaF facilities, Järvelä and her team have collected multimodal data. Measuring heart rate, electrodermal activity, tracking eye movements, as well as recording gestures and other embodiments have all together enabled her team to gather nuanced data to contribute to the study of learning processes. Järvelä explains that as learning involves complex metacognitive, social and emotional processes, the LeaF facilities have enabled her team to study phenomena which would otherwise be very difficult to measure.
These methodological advancements of learning research have led Järvelä to build the theory of socially shared regulation in learning (SSRL). In a nutshell, the theory concerns the role of the inter-group metacognitive processes in promoting learning and teamwork within the group. Examples of metacognitive processes include planning, monitoring and evaluating one’s learning aside from emotional and motivational aspects.
Järvelä’s team has been internationally recognised for making contributions to the study of the role of social aspects in self-regulation. Recently, their research has taken on a new direction – AI – as the CELLA center for living and learning with AI was established a year ago. At the CELLA center, Järvelä’s team and four other international learning laboratories are working together to investigate the role of AI in the study of regulation in learning.
AI should strengthen the learner’s agency
In Järvelä’s view, AI has potential in helping learners become aware of the parts of the learning process that are not necessarily visible to them. Detecting the different stages of learning and predicting how learning will develop creates insights into successful and unsuccessful learning processes. AI could help students to identify the essential areas whereby more practice is needed, and in some cases, AI could provide tutoring.
“The fact that AI could increase learners’ awareness of the areas where more practice is needed is valuable, because awareness usually leads to action,” Järvelä points out.
Of course, AI does not come without ethical dilemmas. At the moment, these dilemmas are mainly connected to the use of data and information security. But AI is developing fast, and it will certainly give rise to new ethical dilemmas along the way. Järvelä says that this is why research related to the co-evolution of humans and technologies is needed to bring solutions to these dilemmas.
“The most important goal with AI, overall, is to strengthen the learner’s own agency. We need to understand the basic human processes so that we are able to find the right ways in which technologies can truly bring value to us,” Järvelä says.
According to Järvelä, the future of AI in education is still unknown. The role of AI in teaching and learning is quite narrow at the moment, and it will continue to take shape in the future. The growing role of AI naturally raises concerns in societal discussions, but Järvelä believes that AI will only bring more appreciation to the qualities that are uniquely human.
“AI will never be able to cross that line to reach the qualities that are deeply human - like creativity, flexible thinking, emotions and empathy,” Järvelä says.
“I believe that those qualities will gain more appreciation in the future, as AI will be able to take care of the more routine tasks,” she continues.
As the future role of AI is still unknown and vague, Järvelä draws emphasis on the power of interdisciplinary research in helping to create future solutions together.
Järvelä thinks that the GenZ profiling theme has brought major advancements in interdisciplinary research, especially regarding the collaborations between human sciences and technology-centered fields of study.
“During the past few years, we have worked towards building practices that bring together human sciences and technology. Our efforts have brought researchers together, inspired new multidisciplinary projects, organised seminars, and really created an impact both within our university but also outside of it,” Järvelä explains.
“I cannot say that it has been easy, but we have learned a great deal. And GenZ has been one of the major driving forces behind all of this,” Järvelä explains.
As for herself, Järvelä is excited to begin working with a new profiling theme – Hybrid Intelligence (Profi7). Within this profiling theme, Järvelä is hoping to expand her understanding of human-AI interactions and collaboration.