BEGIN:VCALENDAR
VERSION:2.0
PRODID:-//Memento EPFL//
BEGIN:VEVENT
SUMMARY:IC Colloquium: Modeling and Individualizing Learning in Computer-B
 ased Environments
DTSTART:20190919T101500
DTEND:20190919T110000
DTSTAMP:20260406T194630Z
UID:a0d76570caa592265ce12dc47081d191631ef138eb82816c592e6eef
CATEGORIES:Conferences - Seminars
DESCRIPTION:By: Tanja Käser - Swiss Data Science Center\nDigital Vocation
 al Education & Training candidate\n\nAbstract:\nLearning technologies are 
 becoming increasingly important in today's education. This includes game-b
 ased learning and simulations\, which produce high volume output\, and MOO
 Cs (massive open online courses)\, which reach a broad and diverse audienc
 e at scale. With the increased digitization\, continued learning is becomi
 ng important for every profession and these types of learning environments
  have the potential to yield insights into how we can prepare students for
  our digital society. Given the very different backgrounds of the users of
  these educational systems\, for example in terms of age\, prior knowledge
 \, and learning speed\, adaptation to the specific needs of the individual
  user is a key factor for motivation and learning success.\nIn this talk\,
  I will present two of my contributions on modeling and predicting student
  learning in computer-based environments with the goal to enable individua
 lization. The first contribution introduces a new model and algorithm for 
 representing and predicting student knowledge. The new approach is efficie
 nt and has been demonstrated to outperform previous work regarding predict
 ion accuracy. The second contribution introduces models\, which are able t
 o not only take into account the accuracy of the user\, but also the inqui
 ry strategies of the user\, improving prediction of future learning. Furth
 ermore\, students can be clustered into groups with different strategies a
 nd targeted interventions can be designed based on these strategies.\nFina
 lly\, I will also describe lines of future research around strategies in o
 pen-ended learning environments and discuss its benefits for vocational ed
 ucation training.\n\nBio:\nTanja Käser is currently a senior data scient
 ist at the Swiss Data Science Center (SDSC). Before joining the SDSC\, she
  was as postdoctoral researcher at the Graduate School of Education at St
 anford University. Tanja also worked as a postdoctoral researcher at ET
 H Zurich and as a consultant for Disney Research Zurich and Dybuster AG.
  She received her PhD in Computer Science from ETH Zurich\; her thesis w
 as distinguished with the Fritz Kutter Award for the best Computer Science
  thesis at a Swiss university. Tanja works in the field of artificial int
 elligence in education and is especially interested in modeling and predi
 cting student thinking and learning to optimize and improve (computer-ba
 sed) learning.\n\n\n 
LOCATION:BC 420 https://plan.epfl.ch/?room==BC%20420
STATUS:CONFIRMED
END:VEVENT
END:VCALENDAR