Course Content
Orientation, introduction to the course
1. Human-Robot Interaction (HRI)
2. Research Methods in Human-Robot Interaction
3. Smart Cities & HRI
The demand for city living is already high, and it appears that this trend will continue. According to the United Nations World Cities Report, by 2050, more than 70% of the world's population will be living and working in cities — one of many reports predicting that cities will play an important role in our future (UN-Habitat, 2022). Thus, as cities are growing in size and scope, it is shaped into complex urban landscape where things, data, and people interact with each other. Everything and everyone has become so connected that Wifi too often fails to meet digital needs, online orders don't arrive fast enough, traffic jams still clog the roads and environmental pollution still weighs on cities. New technologies, technical intelligence, and robots can contribute to the direction of finding solutions to ever-increasing problems and assist the evolution of the growing urban space.
Human-Robot Interaction
About Lesson

Research in human-robot interaction is mostly performed using behavioural experiments, similarly with human-computer interaction experiments. Therefore, we will collect data using true experiments, which, according to Lazar, Feng, and Hochheiser (Lazar, 2017), possess the following characteristics:

  • A true experiment is based on at least one testable research hypothesis and aims to validate it.
  • There are usually at least two conditions (a treatment condition and a control condition) or groups (a treatment group and a control group).
  • The dependent variables are normally measured through quantitative
  • measurements.
  • The results are analysed through various statistical significance tests.
  • A true experiment should be designed and conducted with the goal of removing potential biases.
  • A true experiment should be replicable with different participant samples, at different times, in different locations, and by different experimenters.

After collecting data, we use statistical analysis to present our data and evaluate the research hypotheses.


Lazar, J. , Feng, J. H., Hochheiser, H.  (2017), Research methods in human-computer interaction: Morgan Kaufmann, 2017.

Dix, A. (2020). Statistics for HCI: Making Sense of Quantitative Data. Morgan & Claypool Publishers.
Robertson, J., & Kaptein, M. (2016). An introduction to modern statistical methods in HCI (pp. 1-14). Springer International Publishing.
Larson-Hall, J. (2015). A guide to doing statistics in second language research using SPSS and R. Routledge.
Aldrich, J. O. (2018). Using IBM SPSS statistics: An interactive hands-on approach. Sage Publications.