Many subfields of computer science require ways of evaluating the product or service being developed, whether it is a traditional product, such as a computer game or a web browser,  or a completely new type of interface technology or social networking service. However, computer scientists are usually not well trained in practical details of running a study with human participants. How to avoid the placebo effect? How to randomize the subjects? What are independent and dependent variables? What is the difference between ANOVA and linear regression (answer, there is no difference).

This seminar aims to provide practical introduction to these matters. I have been involved in running various user studies for many years, and have gone through the many pitfalls and problems usually not mentioned in text books or more theoretical courses.

The seminar will be slightly different than the usual format as  we to go through the whole process of planning, implementing, running, analyzing and disseminating a HCI user study. Those who are interested can even try to get an actual scientific article published in some conference or a journal. However, doing that will require a lot of dedicated work, but also be rewarded with 5 credits, and of course the publication reference, which is extremely helpful if one is interested in an academic career.

We have all kinds of interesting devices here, such as eye trackers, depth cameras for gesture recognition, psychophysiological recording devices for EEG, ECG, EDA, EMG, haptic devices, touch screens etc. so there are a lot of options for high quality user studies to be conducted.

Note that this seminar will require quite a lot of effort from the participants, so if you are only interested in fulfilling the mandatory requirements for your degree, this seminar is not for you. However, if you are interested in pursuing an academic career, or developing HCI products or services, this seminar will provide a very unique opportunity to receive hands on experience in a subject that is usually learned by observing and being part of more experienced team of researchers.