Quick introduction to field experiments in usability and user experience

This entry tries to be a very short guide on how to perform field experiments for usability and user experience. Fields experiments is reported to have many advantages over laboratory experiments as can be read in the HCI literature [1]. What we try to obtain with field experiments is to overcome the complexity that real contexts represents and cannot be reproduced in a laboratory. As the literature also said, these experiments cannot be replaced by expert evaluations [1] because field experiments focus on the participants and the context: using real users in real context: the weather, user profiles, effectiveness of the locations-based systems, screen resolutions, keyboards… The only way to see how the user and the system performs is taking a ride and practice. As Nielsen [3] and Brewster [2] say, field experiments are always difficult to perform due to the problem that sufficient data must be acquired without interfering in the experiment neither conditioning the participants. Talking about mobile devices in general, its usability is an special concern because of the context and the environment the devices may be used. There are a lot of services or functionalities that depends on the context like location-based services and applications in outdoors which are difficult to simulate in a laboratory. So usability testing in the laboratory will be very limited and will never simulated a fully user case when testing usability in real context with real users.

Continue reading

The Pythonic Way

Python is a very powerful programming language that understands structural, functional and object oriented programming paradigms. New comers to Python from other languages tend to carry with them their mother (programming) tongue culture. Although they achieve the required task, they might have fallen in the trap of using Python the wrong way. In this post, we cover some efficient tricks to achieve tasks in Python; we call it the Pythonic way. Find an IPython Notebook for all tricks here on our GitHub repository.

Lists, Tuples, Dictionaries and Sets

Continue reading