Keynote speakers

Brain researcher Minna Huotilainen is professor of education at the University of Helsinki. She aims to bring the latest research findings in neuroscience to teaching, education and training. For her achievements in the popularisation of science, Huotilainen has been awarded the J.V. Snellman Award.

 

How can educational sciences benefit from brain research?

Methods used in brain research have become increasingly common, and the field is constantly producing new and interesting information on learning. How could such information be used in educational sciences? And what about practical instruction and education? Huotilainen’s address will provide examples of using music as a teaching tool and the effect of exercise on learning. In addition, her presentation will envision a future in which brain research is even more tuned in to the needs of education and teaching.

Akseli Huhtanen (MSocSc) specialises in lifelong learning. His background is in the teaching of philosophy, while his research activities focus on the philosophy of education and educational objectives. Huhtanen is one of the founders of the international Dare to Learn learning event, for which he has worked as head of programme and CEO. At Dare to Learn, Huhtanen’s particular focus was on designing learning experiences and on the psychology of learning. Currently, he is serving as an advisor to Dare to Learn and as an expert of learning to various communities. Alongside his work, Huhtanen has developed instruction methods based on philosophy for children at Filo, an association promoting the practice of philosophy among children, adolescents and various communities, as well as experience-based teaching methods in his ‘Philosophy of Forest’ courses.

 

Designing for Learning - Creating holistic learning experiences through deliberate design

"Taking the design approach towards learning puts the learner and her experience at the center - rather than the teacher or the subject matter. Design approach towards learning also enables the development of the environmental factors in addition to the teaching, resulting in a holistic learning experience.

The basic elements of a deliberate learning design process are:

  1. Analysis on what should be learned, 
  2. Goal-setting based on what is relevant for the audience
  3. Ideation of learning activities
  4. Choosing and planning the activities

An appropriate design for learning is based on research evidence. The aim of the design should be to enable the key psychological processes needed for learning: motivation, attention, memory and emotion.

The presentation aims to provide an overview of the available tools for designing an effective learning experience. The main question in the presentation is how to design learning according to what research tells us about the psychological foundations of learning?"

Samuli Siltanen, DSc (Tech), has served as professor of industrial mathematics at the University of Helsinki since 2009. Samuli received the J.V. Snellman Public Information Award in 2018 for his videos published on the YouTube channel ‘Samun tiedekanava’ (“Samu’s science channel”). In his teaching, Samuli highlights connections between mathematics, everyday life and practical applications, for example, in photography. Groupwork, measurements carried out by students themselves and coding are central aspects of his courses.

 

Connecting mathematics to everyday life

Mathematics can be theoretical and abstract, and not every student can find motivation for the hard work needed to learn math. However, there are aspects of everyday life where mathematics appears naturally. For example, digital photographs consist of numbers. Therefore, enhancing or filtering photos by modifying colors actually means modifying numbers. And numbers are obviously modified with mathematics! Instagram filters, Photoshop and other image processing tools use math that is usually hidden from the users but can be revealed in class. Another example is medical imaging, allowing doctors to see inside patients using X-ray measurements and mathematical computation. Students can measure their own data and team up to write the software to process it. After such practical and hands-on encounter with everyday math, students feel much more motivated for studying the theoretical background.