# Design and Applications of GLANCE: GLanceable Alarm Notification for a User Centered Experience
## 3 Results of the 1 st Macro-Phase: The GLANCE Project
### First Iteration: Dealing with Individual Alarms
#### 3.1.2 Evaluation and Learning  
The first (low-fidelity) prototype was realized as an animated PowerPoint display mock-up simulating an example sequence of single alarm notifications with different severity. Given the simplicity of the notifier up to this point, formative evaluation was conducted in a rather quick and inexpensive way to receive suggestions from domain experts on how to possibly improve the _glancability_ and _readability_ of the system, postponing a  
Figure 5: Mapping severity levels onto the attention-awareness graph.  
\begin{table}
\begin{tabular}{c c c} \hline \hline
**Attention Type** & **Notification Level** & **Transition 1** \\ \hline \hline \multirow{2}{*}{Inattention} & Change blind & \multirow{2}{*}{Slow motion, tiny updates} \\  & & (cleared, warning) & \\ \hline \multirow{2}{*}{Divided attention} & Make aware & \multirow{2}{*}{Discrete, abrupt updates} \\  & & (minor) & \\ \hline \multirow{2}{*}{Focused attention} & Interrupt & \multirow{2}{*}{Flashing, beeping} \\  & & (major) & \\ \hline \hline \end{tabular} \({}^{1}\) In case of usage on mobile devices, distinct auditory and haptic stimuli of increasing intensity are to be added.  
\end{table}
Table 5: Mapping severity levels to attention types/transition types of [38].  
more formal evaluation to the end of the 2 nd iteration. The evaluation group included one facilitator, one product expert, and two Technolabs people with the twofold role of evaluators and domain experts. The overall evaluation meeting included a 30\({}^{\prime}\) seminar on ambient and alerting displays (to make domain experts more familiar with the selected theoretical framework), a general presentation of the GLANCE model to the evaluators, and a cognitive walkthrough session [60,61].  
In order for the test to be as much as possible representative of an actual working situation (e.g., to check how typical background noise could interfere with the auditory stimuli of the notifier), the evaluation session took place in the real working setting and the notification sequence was built from a real alarm log generated by the optical fiber network investigated in the problem solving cycle, with notifications presented in an asynchronous way with no particular order as to severity levels. The facilitator walked through the example notification sequence to evaluate, for each notification, whether a real user would achieve the desired comprehension effect and would associate it to the correct reaction. Technolabs people were indeed very satisfied and surprised by GLANCE readability and did not detect any flaw neither in the abstract model nor in the mockup. In particular, they appreciated the glanceability of the coding technique and underlined the immediacy of the alarm information availability compared to solutions offered by commercial products based on a peripheral status bar with scarce visual cue distinction and, above all, on the necessity of user initiated actions for accessing the correct level of detail for incoming alarms.  
In addition, stimulated by this observation, after the walkthrough session a comparison between GLANCE and the Scope display [42] was analyzed with the domain experts, as to the different choice of the two approaches with respect to the immediate availability of the information associated to low and medium severity alarms (as to information about high severity notifications both approaches make it immediately available without explicit user request). Domain experts agreed with the GLANCE choice of making alarm information always available at an automatic severity-dependent LOD without explicit user's action in any case, and, concerning this stage of the project, judged GLANCE superior as to long-term comprehension of alarm information of any severity (though additional evaluation was still to be done in successive project steps).  
With reference to Table 1, the target objectives of the first iteration (PO1, RO1.1, and RO1.2, and then RO1 as well) were hence considered achieved.