In many complex time-critical tasks such as financial trading, cyber security monitoring, and patient monitoring in critical care, external interruptions and multiple-task situations disrupt the flow of tasks performed by operators leading to errors and accidents. There is an abundance of work reported on interruptions, which informs system designers and researchers on the potential cost of interruptions at different points within a task. However, a gap exists in our understanding of the relationship between interruption disruptiveness and the predictability of events that require an operator's response. To understand this better, we conducted an experiment involving 22 participants and a financial trading task. The experiment involved two levels of predictability (low and high) and two levels of task load (low and high). The experiment showed that task load had an overall negative effect on events. The results also showed that interruptions negatively affected responses to predictable events. However, we found that interruptions did not affect responses to unpredictable events. Overall, our research suggests that to leverage the role of predictability, the goal-activation model should be used to determine the impact of various design options about visual cues and predictable-trend durations. The research also reveals that unpredictable events may be cognitively different from predictable events when understanding the influence of interruptions on work, suggesting that interruption management tools may need to treat the situational context (predictable or unpredictable) differently, in providing a supportive workflow for the management of interruptions.

Modeling typing performance has values in both the theory and design practice of human-computer interaction. Previous models have simulated desktop keyboard transcription typing performance; however, as the increasing prevalence of smartphones, new models are needed to account for mobile phone touchscreen typing. In the current study, we built a model for mobile phone touchscreen typing in an integrated cognitive architecture and tested the model by comparing simulation results with human results. The results showed that the model could simulate and predict interkey time performance in both number typing (Experiment 1) and sentence typing (Experiment 2) tasks. The model produced results similar to the human data and captured the effects of digit/letter position and interkey distance on interkey time. The current work demonstrated the predictive power of the model without adjusting any parameters to fit human data. The results from this study provide new insights into the mechanism of mobile typing performance and support future work simulating and predicting detailed human performance in more complex mobile interaction tasks.

Heads-up displays (HUDs) are growing in popularity and utility, providing novel ways to interact with environments and other individuals. HUD interfaces must allow users to quickly view information without distracting them from their primary task. We test the use of an adaptive staircase as a method to investigate the glance legibility of two Google Glass heads-up display interfaces. Glance legibility refers to an interface’s legibility when viewed in short amounts of time (also known as glance-like conditions). We measure glance legibility by the minimum presentation time required to read an interface and respond correctly to a yes-no question. The applications of this research can help inform the design and evaluation of future heads-up display interfaces under glance-like conditions.

Despite the enthusiasm and initiatives for making programming accessible to students outside Computer Science (CS), unfortunately, there are still many unanswered questions about how we should be teaching programming to engineers, scientists, artists or other non-CS majors. We present an in-depth case study of first-year management engineering students enrolled in a required introductory programming course at a large North American university. Based on an inductive analysis of one-on-one interviews, surveys, and weekly observations, we provide insights into students' motivations, career goals, perceptions of programming, and reactions to the Java and Processing languages. One of our key findings is that between the traditional classification of non-programmers vs. programmers, there exists a category of conversational programmers who do not necessarily want to be professional programmers or even end-user programmers, but want to learn programming so that they can speak in the “programmer's language” and improve their perceived job marketability in the software industry.

Currently, there are very few guidelines on parameters needed to create an effective auditory display. Auditory displays can be intrusive and may not be used effectively if they are poorly designed. However, music is often in our environments as ambient noise and, instead of being intrusive, can be perceived as making the environment calmer and more productive. We present the initial steps of exploring the option of using music as a medium to develop an auditory display capable of conveying normal state information and warning information. An important feature that may impact the effectiveness of auditory warnings is perceived urgency: the impression of urgency that a sound evokes on a listener. To explore whether music could convey urgency as needed for auditory warnings, we evaluated four different musical phrases that varied in time and key signature as a method of measuring the effects of mode and tempo on perceived urgency. The effectiveness of the study was tested with twenty subjects split into a two by two factorial design: gender (male vs. female) and musical experience (experienced vs. non-experienced). The applications of this research can help develop concrete guidelines when designing effective auditory displays in order to improve users’ performance when dealing with complex interfaces.