Description: Much of technical scientific research has as an ultimate goal to develop technological devices that will be used by people. Either as services, or products that may end up being an integral part of peoples’ lives. In order to investigate if a given technology can be used in a given context, experiments with human subjects are indispensable. These types of experiments can be time consuming and expensive and if not properly designed and executed the results may not be reliable.
This course takes both a theoretical and practical approach to data collection from human subjects, in order to avoid mistakes and common pitfalls while improving the reliability of the results. From an understanding of cognitive and perceptual processes of human interaction with the environment, we will investigate implications of these processes in different data collection scenarios.
The following scenarios will be presented based on the research activities of the section:
- Evaluation of sound environments and interactive control (sound zones).
- Hearing aid aided performance ratings (BEAR).
- EEG differences between active and passive listening.
The course consist of lectures and practical work, where you will design and participate in experiments.
Prerequisites: Knowledge of basic data analysis models, such as CHI-square, T-tests, ANOVA is an advantage, but not strictly required. Programming in any language capable of making simple user interfaces.
Learning Objectives:
- Understand ethical and practical implications of using humans as test subjects.
- Understand and learn to work with rules and regulations for personal data (GDPR).
- Understand how to avoid common mistakes in the experimental design.
- Understand and know the importance of familiarisation and training.
- Understand and learn to apply methods for balancing levels of independent variables.
- Understand and be able to work with variability in subject responses.
- Be able to implement methods for data collection that can minimise subject bias.
- Be able to implement and work with difference judgements, rating scales and forced choice methods.
- Be able to derive scales based on human responses
Organizer: Associate Professor Rodrigo Ordoñez - rop@es.aau.dk
Lecturers: Associate Professor Rodrigo Ordoñez and Lars Bo Larsen
ECTS: 2.0
Time: 18-19 March and 15-16 April 2021
Place: Aalborg University
Zip code: 9220
City: Aalborg
Number of seats: 30
Deadline: 25 february 2021
Important information concerning PhD courses: We have over some time experienced problems with no-show for both project and general courses. It has now reached a point where we are forced to take action. Therefore, the Doctoral School has decided to introduce a no-show fee of DKK 3.000 for each course where the student does not show up. Cancellations are accepted no later than 2 weeks before start of the course. Registered illness is of course an acceptable reason for not showing up on those days. Furthermore, all courses open for registration approximately four months before start. This can hopefully also provide new students a chance to register for courses during the year. We look forward to your registrations.
- Teacher: Aleksandra Kaszowska
- Teacher: Lars Bo Larsen
- Teacher: Rodrigo Ordoñez