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SUMMARY:ML education for K-12: emerging trajectories - Matti Tedre and Hen
 riikka Vartiainen (University of Eastern Finland)
DTSTART:20211102T170000Z
DTEND:20211102T183000Z
UID:TALK161557@talks.cam.ac.uk
CONTACT:102157
DESCRIPTION:Over the past decades\, practical applications of machine lear
 ning (ML) techniques have shown the potential of data-driven approaches in
  computing. ML education has been primarily piloted in computing curricula
  in higher education\, but increasingly in K-12 computing education\, too.
  However\, despite the central position of machine learning in the field o
 f modern computing\, the computing education research body of literature c
 ontains remarkably few studies of how people learn to train\, test\, impro
 ve\, and deploy machine learning systems. This is especially true of the K
 -12 curriculum space.\n\nThis talk will map the emerging trajectories in e
 ducational practice\, theory\, and technology related to teaching machine 
 learning in K-12 education. It will situate that research in the broader c
 ontext of computing education\, and describe what changes ML necessitates 
 in the classroom. The talk will outline the paradigm shift that will be re
 quired in order to successfully integrate machine learning into the broade
 r K-12 computing curricula. A crucial step is abandoning many tenets of ru
 le-based “classical” programming.\n\nSpeakers:\n\nDr. Matti Tedre is a
  professor of computer science\, especially computing education and the ph
 ilosophy of computer science\, at the University of Eastern Finland. His 2
 019 book “Computational Thinking” (The MIT Press\, with P.J. Denning) 
 presented a rich picture of computing’s disciplinary ways of thinking an
 d practicing\, and his 2014 book “Science of Computing” (Taylor & Fran
 cis / CRC Press) portrayed the conceptual and technical history of computi
 ng as a discipline.\n\nDr. Henriikka Vartiainen is a senior researcher and
  university lecturer at the University of Eastern Finland\, School of Appl
 ied Educational Science and Teacher Education. She has also worked as resp
 onsible researcher in several multidisciplinary projects focusing on\, for
  example\, technology education\, co-design in school context\, design-ori
 ented pedagogy\, and 21st skills. Currently\, her research focuses especia
 lly on learning Machine Learning through co-design as well as on the ways 
 to support children’s data agency. Her work on design-oriented pedagogy 
 has received The Doctoral Dissertation Award 2014 by The Finnish Education
 al Research Association (FERA) as well as Young Researcher Award of the UE
 F in 2015.
LOCATION:Venue to be confirmed
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