GenZ Talks seminar
Tellus Stage / remote connection
The fourth GenZ Talks seminar will be organized on May 5, 2022, 12–4 pm at Tellus Stage.
The theme of the seminar is "Co-evolution of intelligent technologies and humans transforming learning practices".
Research on the co-evolution of humans and technologies plays a critical role in explaining how people learn and how new human competencies can be increased for learning, living, and working in the 21st century. The technological advancements in the field of education provide novel opportunities to augment learning analytics with multimodal data for understanding learning and develop educational technologies. Yet, a critical approach is needed in technology adoption to ensure that humans are driving new technologies, not the other way around.
The fourth GenZ Talks seminar asks the following questions related to co-evolution of humans and technologies:
- What new capabilities are needed in an increasingly digital world?
- How can those capabilities be strengthened?
- What opportunities and risks intelligent technologies can bring to learning and education?
GenZ Talks is a series of events where top international and domestic researchers and experts in the GenZ research area discuss humanities and digitization. The event is aimed at researchers and other stakeholders interested in the digital future. The seminar will be organised as a hybrid event.
Register here by 28 April: https://link.webropol.com/ep/genztalks4
12:20 Opening of the seminar
Learning together in digital environments: Support for students and teachers during computer-supported collaborative learning: Nikol Rummel, Professor of Educational Psychology and Technology, Ruhr-University Bochum, Germany
Collaborative learning is increasingly recognized not only as an effective means to promote learning, but also as a useful and necessary skill in society. The pandemic has underscored the need to find ways to design for learning together in digital environments, and to understand how learning best happens in these environments. I will present some key results on intelligent support for student learning in computer supported collaborative learning (CSCL) environments. But even if CSCL environments offer some support for learners, teachers remain central for structuring and orchestrating the classroom activity and for offering essential higher-order support. In the second line of research I will report on, we investigate new ways of leveraging learning analytics (i.e. „digital traces“ of students’ activity) to inform and support teachers in CSCL settings. Finally, I will discuss current work with colleagues at CMU in Pittsburgh, where we have begun to explore human-AI co-orchestration of collaborative learning, i.e. how educational AI systems might effectively work together with human facilitators (e.g., teachers or peers) in orchestrating CSCL in the classroom.
AI Education for All - Do We Need It?: Ilkka Jormanainen, Dr., senior researcher, School of Computing, University of Eastern Finland
During the past two decades, numerous practical applications of artificial intelligence techniques have shown the potential of data-driven approaches in many computing fields. The rapid diffusion of machine learning and other AI methods in apps, services, and everyday gadgets has direct and significant implications on computing education at all levels. Since the mid-2010s a quickly growing number of research and development initiatives have explored how to teach artificial intelligence concepts also in K–12 computing education. However, as of now, the computing education research body of literature contains remarkably few studies of how people learn to train, test, improve, and deploy AI systems. This is especially true in the K–12 curriculum space. In this talk, we explore challenges, opportunities, and emerging trajectories in educational practice, theory, and technology related to teaching AI in K–12 education.
Multimodal Learning Analytics in Real-world Practice: A Bridge Too Far?: Mutlu Cukurova, Associate professor of learning technologies, University College London, UK
Multimodal Learning Analytics (MMLA) has gathered an increasingly significant amount of interest from the research communities of Learning Analytics and Artificial Intelligence in Education within the last decade. In this talk, I will argue that MMLA can be a dangerous idea. Similar to most dangerous ideas, MMLA has the potential to advance the learning analytics field and educational practice. However, dangerous ideas should be approached with great caution and our first intuition of whether they are advised to be taken forward, or not, require a close examination with research evidence. Here, I will present three different conceptualisations of MMLA with promising research findings for each, but also reflect upon some of the reasons behind their morally troubling nature driven by our recent real-world implementations. Each conceptualisation presented is likely to contribute to educational research and practice to different degrees, and might have a different likelihood of being denounced.
Interactive panel discussion
16:00 End of the seminar