Research Methods for HCI: Understanding People Using Interactive Technologies

This course will provide an introduction to methods used in Human-Computer Interaction (HCI) research. An equal focus will be given to both the quantitative and qualitative research traditions used to understand people and interactional contexts. We shall discuss these major philosophical traditions along with their contemporary framings (e.g., in-the-wild research and Interaction Science). By the end of the course attendees will have a detailed understanding of how to select and apply methods to address a range of problems that are of concern to contemporary HCI researchers

In-car distractions and automated driving: A preliminary simulator study

As vehicles with automated driving features become more common, drivers may become ever more tempted to engage in secondary in-car tasks. We report on the results of a driving simulator study that investigated whether the presence of an in-car video would make drivers more likely to switch on an automated driving system so that they can watch the video. Results show an increase in automated driving mode usage when a video was playing compared to when it was not playing. The presence of this in-car video also made participants slower at reacting to frequent red traffic lights, which the automated driving mode did not detect and were the responsibility of the driver to respond to. These results suggest that in-car distractions are a critical concern for the safe and responsible use of automated driving systems

Diminished Control in Crowdsourcing: An Investigation of Crowdworker Multitasking Behavior

Obtaining high-quality data from crowds can be difficult if contributors do not give tasks sufficient attention. Attention checks are often used to mitigate this problem, but, because the roots of inattention are poorly understood, checks often compel attentive contributors to complete unnecessary work. We investigated a potential source of inattentiveness during crowdwork: multitasking. We found that workers switched to other tasks every five minutes, on average. There were indications that increasing switch frequency negatively affected performance. To address this, we tested an intervention that encouraged workers to stay focused on our task after multitasking was detected. We found that our intervention reduced the frequency of task-switching. It also improves on existing attention checks because it does not place additional demands on workers who are already focused. Our approach shows that crowds can help to overcome some of the limitations of laboratory studies by affording access to naturalistic multitasking behavior

Higher-level Knowledge, Rational and Social Levels Constraints of the Common Model of the Mind

In his famous 1982 paper, Allen Newell [22, 23] introduced the notion of knowledge level to indicate a level of analysis, and prediction, of the rational behavior of a cognitive articial agent. This analysis concerns the investigation about the availability of the agent knowledge, in order to pursue its own goals, and is based on the so-called Rationality Principle (an assumption according to which "an agent will use the knowledge it has of its environment to achieve its goals" [22, p. 17]. By using the Newell's own words: "To treat a system at the knowledge level is to treat it as having some knowledge, some goals, and believing it will do whatever is within its power to attain its goals, in so far as its knowledge indicates" [22, p. 13]. In the last decades, the importance of the knowledge level has been historically and system- atically downsized by the research area in cognitive architectures (CAs), whose interests have been mainly focused on the analysis and the development of mechanisms and the processes governing human and (articial) cognition. The knowledge level in CAs, however, represents a crucial level of analysis for the development of such articial general systems and therefore deserves greater research attention [17]. In the following, we will discuss areas of broad agree- ment and outline the main problematic aspects that should be faced within a Common Model of Cognition [12]. Such aspects, departing from an analysis at the knowledge level, also clearly impact both lower (e.g. representational) and higher (e.g. social) levels

6th international workshop on pervasive eye tracking and mobile eye-based interaction

Previous work on eye tracking and eye-based human-computer interfaces mainly concentrated on making use of the eyes in traditional desktop settings. With the recent growth of interest in wearable computers, such as smartwatches, smart eyewears and low-cost mobile eye trackers, eye-based interaction techniques for mobile computing are becoming increasingly important. PETMEI 2016 focuses on the pervasive eye tracking paradigm as a trailblazer for mobile eye-based interaction to take eye tracking out into the wild, to mobile and pervasive settings. We want to stimulate and explore the creativity of these communities with respect to the implications, key research challenges, and new applications for pervasive eye tracking in ubiquitous computing. The long-term goal is to create a strong interdisciplinary research community linking these fields together and to establish the workshop as the premier forum for research on pervasive eye tracking

Voices in self-driving cars should be assertive to more quickly grab a distracted driver’s attention

Automated driving will mean that people can engage in other activities and an important concern will be how to alert the driver to critical events that require their intervention. This study evaluates how various levels of assertiveness of voice command in a semi-AV and different degrees of immersion of a non-driving task may affect people's attention on the road. In a simulated set-up, 20 participants were required to execute actions on the steering wheel when a voice command was given while playing a mobile game. Regardless of how immersed the driver was in the game, a more assertive voice resulted in faster reaction time to the instructions and was perceived as more urgent than a less assertive voice. Automotive systems should use an assertive voice to effectively grab people's attention. This is effective even when they are engaged in an immersive secondary task

Looking Up Information in Email: Feedback on Visit Durations Discourages Distractions

Data entry often involves looking up information from email. Task switching to email can be disruptive, and people can get distracted and forget to return to their primary task. In this paper, we investigate whether giving people feedback on how long they are away has any effect on the duration and number of their switches. An online experiment was conducted in which participants had to enter numeric codes into an online spreadsheet. They had to look up these codes in an email sent to their personal email upon starting the experiment. People who were shown how long they were away for made shorter switches, were faster to complete the task and made fewer data entry errors. This suggests feedback on switching duration may make people more aware of their switching behaviour, and assist users in maintaining focus on their main task