BEGIN:VCALENDAR
VERSION:2.0
PRODID:-//Talks.cam//talks.cam.ac.uk//
X-WR-CALNAME:Talks.cam
BEGIN:VEVENT
SUMMARY:Exploring the data-driven world: Teaching AI and ML from a data-ce
 ntric perspective - Carsten Schulte\, Yannik Fleischer and Lukas Höper (P
 aderborn University)
DTSTART:20211005T160000Z
DTEND:20211005T173000Z
UID:TALK161554@talks.cam.ac.uk
CONTACT:102157
DESCRIPTION:The talk will raise the question of whether and how AI and ML 
 should be taught differently from other themes in the CS curriculum at sch
 ool. The tentative answer is that these topics require a paradigm shift fo
 r some teachers and that this shift has to do with the changed role of alg
 orithms\, of data\, and of the societal context. The talk will present thr
 ee small teaching examples from middle schools to illuminate the possible 
 differences in teaching. The first example draws upon the Matchbox compute
 r and successors like the sweet learning computer to teach the machine lea
 rning process\, the second is about enactive teaching of Decision Trees\, 
 and the third about analysing location data. (Note: please have a fruit\, 
 ideally an apple\, at hand during the presentation for some interactive el
 ements!)\n\nSpeakers:\n\nDr. Carsten Schulte is a professor of computing e
 ducation research at Paderborn University\, Germany. His work and research
  interests are the philosophy of computing education and empirical researc
 h into teaching-learning processes (including eye movement research). Sinc
 e 2017\, he has been working together with Didactics of Mathematics (Pader
 born University) in the ProDaBi project\, in which Data Science and Artifi
 cial Intelligence are prepared as teaching topics. He is also PI in the co
 llaborative research centre ‘Constructing Explainability’ on explainab
 le AI.\n\nYannik Fleischer is a PhD student in mathematics education resea
 rch at Paderborn University\, Germany. His main research interest is to de
 velop a concept to teach machine learning methods in school with a focus o
 n decision trees\, and to evaluate this by developing and examining teachi
 ng materials in practice. Since 2019\, he has been supervising year-long p
 roject courses on data science in upper secondary and developing\, impleme
 nting\, and evaluating teaching modules for different levels in secondary 
 school\, mainly about machine learning with decision trees.\n\nLukas Höpe
 r is a PhD student in computing education research at Paderborn University
 \, Germany. His main research interest is to develop the concept of data a
 wareness for computing education and evaluate this by developing and exami
 ning teaching materials in practice. Since 2020\, he has been working on d
 ata awareness in the ProDaBi project\, among other topics on AI and Data S
 cience in schools.
LOCATION:Venue to be confirmed
END:VEVENT
END:VCALENDAR