Project Socially Aware Computing

Course Objective

After having completed this course students are able to: Perform a study following a full research cycle: setting up an experiment (conceptualisation,formalisation), performing the experiment (simulation), analysing and interpreting its results (applying knowledge and understanding; making judgements); Apply and integrate knowledge about programming, modelling, statistics, conducting research and academic writing to actual societal challenges (applying knowledge and understanding; making judgements); Build a multi agent-based model in the modelling environment Netlogo (applying knowledge and understanding); Report the results of the project in written form (communication; lifelong learning skills)

Course Content

Within this course students learn to address a societal challenge involving social interaction by means of agent-based simulation. They learn to identify relevant concepts and relations, formalise these in a dedicated environment (Netlogo), conduct simulations to test different hypothetical scenarios and analyse their results.They do this by working individually on assignments and project in a chosen domain. They report their findings in written form.

Additional Information Teaching Methods

During a period of four weeks, students have 1 plenary lecture and 2 workgroup/project meetings per week. Each meeting lasts 2x45 minutes. Attendance is mandatory. This is a fulltime course in a short period. We expect the students to spend all available hours on their assignments and project.

Method of Assessment

Pass/fail individual assignments that need to be passed to start the project. Individual project report (95%) + self-reflection (5%). We only offer a resit for the project. If you fail the assignments you will have to take the course again next academic year. This course consists of individual assignments and an individual project. Students need to work on the assignments in class. Their work is checked by the teacher or TA. The meetings are mandatory. The students also work on their project in the mandatory meetings.

Recommended background knowledge

Knowledge on programming (Introduction to Python Programming) and statistics (Statistical Methods) is highly recommended.