|Period:||period 1 (week 36 through 45, i.e., 2-9-2019 through 8-11-2019; retake week 1 (bachelor) / 2 (master))|
|Participants:||up till now 86 subscriptions|
|Schedule:||Official schedule representation can be found in MyTimetable|
|Teachers:||Dit is een oud rooster!
|Contents:||This course is about the design and evaluation of interactive systems that automatically adapt to users and their context. It discusses the layered design and evaluation of such systems. It shows how to build models of users, groups and context, and which characteristics may be useful to model (including for example preferences, ability, personality, affect, inter-personal relationships). It shows how adaptation algorithms can be inspired by user studies. It covers standard recommender system techniques such as content-based and collaborative filtering, as well as research topics such as person-to-person recommendation, task-to-person recommendation, and group recommendation. It also discusses explanations for adaptive interactive systems and usability issues (such as transparency, scrutability, trust, effectiveness, efficiency, satisfaction, diversity, serendipity, privacy and ethics). The course content will be presented in the context of various application domains, such as personalized behaviour change interventions, personalized news, and personalized e-commerce.|
|Literature:||The literature consists of scientific articles. A literature list is provided via Blackboard on a weekly basis. In addition, you will need to find articles related to your assignment topic.|
|Course form:||This course has two 2-hour slots a week. These will contain lectures as well as hands-on sessions in which the material of the course is applied to problems.|
This course is assessed via course work assignments only: three group ones (Assignments 1-3) and one individual one (Assignment 4).
A peer effort assessment will be used to allocate individual marks for group assignments.
To pass the course, the weighted average of the individual marks for group assignments (so after the effort assessment has been taken into account) has to be >=5.5 AND the mark for the individual evaluation assignment has to be >=5.5.
|Minimum effort to qualify for 2nd chance exam:||To be allowed to resit this course, the original course mark should be at least 4.|
Upon completion of this course, the student is able to: