Last week, Atlanta hosted the annual IEEE Symposium on Visual Languages and Human-Centric Computing (VL/HCC). This brought researchers in various fields of Computer Science, particularly those in human-computer interaction and software engineering. Established in 1984, the mission of the conference is to support the design, theory, application, and evaluation of computing technologies and languages for programming, modelling, and communicating, which are easier to learn, use, and understand by people.
Daniel Rough, a PhD student in SACHI attended this conference to present his research called “Jeeves”, a visual language to facilitate ESM application creation, which was accepted as a full paper. (You can find details of this paper via our publications page).
@danielrough gives an engaging talk on using blocks programming to facilitate mobile experience sampling #vlhcc15 pic.twitter.com/xwXgA0QpIj
— Brittany Johnson (@brittjayDLF) October 20, 2015
The Experience Sampling Method (ESM) captures participants’ thoughts and feelings in their everyday environments. Mobile and wearable technologies afford us opportunities to reach people using ESM in varying contexts. However, a lack of programming knowledge often hinders researchers in creating ESM applications. In practice, they rely on specialised tools for app creation. An initial review of these tools indicates that most are expensive commercial services, and none utilise the full potential of sensors for creating context-aware applications.
Inspired by successful visual languages in literature, the block-based notation enables researchers to visually construct ESM study specifications.
Its utility was demonstrated with a study to determine usability by end-users of varying programming knowledge, in which it was shown that the language and environment could be feasibly used by participants with no programming experience. In the more general domain of end-user development, the initial evaluation showed that visual programming is a feasible direction of research for enabling technology-supported studies by end-users from various backgrounds.
Thanks to Brittany Johnson for the images of Daniel during his talk.