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CATEGORIES:Computing Education Research
SUMMARY:Exploring the data-driven world: Teaching AI and M
 L from a data-centric perspective - Carsten Schult
 e\, Yannik Fleischer and Lukas Höper (Paderborn Un
 iversity)
DTSTART;TZID=Europe/London:20211005T170000
DTEND;TZID=Europe/London:20211005T183000
UID:TALK161554AThttp://talks.cam.ac.uk
URL:http://talks.cam.ac.uk/talk/index/161554
DESCRIPTION:The talk will raise the question of whether and ho
 w AI and ML should be taught differently from othe
 r themes in the CS curriculum at school. The tenta
 tive answer is that these topics require a paradig
 m shift for some teachers and that this shift has 
 to do with the changed role of algorithms\, of dat
 a\, and of the societal context. The talk will pre
 sent three small teaching examples from middle sch
 ools to illuminate the possible differences in tea
 ching. The first example draws upon the Matchbox c
 omputer and successors like the sweet learning com
 puter to teach the machine learning process\, the 
 second is about enactive teaching of Decision Tree
 s\, and the third about analysing location data. (
 Note: please have a fruit\, ideally an apple\, at 
 hand during the presentation for some interactive 
 elements!)\n\nSpeakers:\n\nDr. Carsten Schulte is 
 a professor of computing education research at Pad
 erborn University\, Germany. His work and research
  interests are the philosophy of computing educati
 on and empirical research into teaching-learning p
 rocesses (including eye movement research). Since 
 2017\, he has been working together with Didactics
  of Mathematics (Paderborn University) in the ProD
 aBi project\, in which Data Science and Artificial
  Intelligence are prepared as teaching topics. He 
 is also PI in the collaborative research centre ‘C
 onstructing Explainability’ on explainable AI.\n\n
 Yannik Fleischer is a PhD student in mathematics e
 ducation research at Paderborn University\, German
 y. His main research interest is to develop a conc
 ept to teach machine learning methods in school wi
 th a focus on decision trees\, and to evaluate thi
 s by developing and examining teaching materials i
 n practice. Since 2019\, he has been supervising y
 ear-long project courses on data science in upper 
 secondary and developing\, implementing\, and eval
 uating teaching modules for different levels in se
 condary school\, mainly about machine learning wit
 h decision trees.\n\nLukas Höper is a PhD student 
 in computing education research at Paderborn Unive
 rsity\, Germany. His main research interest is to 
 develop the concept of data awareness for computin
 g education and evaluate this by developing and ex
 amining teaching materials in practice. Since 2020
 \, he has been working on data awareness in the Pr
 oDaBi project\, among other topics on AI and Data 
 Science in schools.
LOCATION:Venue to be confirmed
CONTACT:
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