Related Work

In this section, we would like to provide a brief overview of existing (electronic) diary/ESM tools and their characteristics. We will focus especially on the kinds of research designs the tools support and the ways researchers and partici-pants can interact with them. The traditional physical form for recording infor-mation in a diary is pen and paper. Ideally, the paper would already be bound in a booklet in A4 or A5 size, so that participants would not have to look after sin-gle sheets of paper. The A5 size adds mobility; if people are asked to carry the diary with them, the A5 size has some advantages. Such a booklet should also contain an instructions page. Each page is assigned to one diary entry to facili-tate analysis. In the case of time-based designs with random intervals, as in ESM studies, an additional signaling device is needed. This augments the

pa-per diary with an electronic device such as a pager or alarm clock which notifies participants when a diary entry is due. While such a paper diary can be nicely integrated into the personal environment of participants, it does have certain drawbacks. First of all, it is often difficult to carry around, even at A5 size. Espe-cially for time-based designs at random intervals, this creates a problem, as the diary may not be at hand when needed. In addition, researchers have no guar-antee of when diary entries are actually completed; again, this is especially problematic in random-interval designs but also in general. If participants cannot be trusted to complete the entries at the given times or right after events, a re-call bias may be introduced, making interpretation of the diary data difficult.

However, it is true that paper diaries are relatively easy to set up and maintain and can be provided to almost everybody without a “technical” instruction.

ESP (Barrett & Barrett, 2001) was probably one of the first ESM tools on a mo-bile device (a Palm). In comparison to more recent tools, it had very basic func-tionality, focusing on time-based random schedules with questionnaire items as response types on the device. The configuration was possible through configu-ration files. As it is Open Source, ESP has had a long history of usage in stud-ies in a variety of fields, including the social sciences, psychology, and HCI.

Momento (Carter, Mankoff, & Heer, 2007) was one of the first tools that emerged specifically from the HCI area. It used the more modern Windows Mo-bile OS, which allowed it to be deployed on a variety of devices. The functionali-ty focused very much on questionnaire items and a reporting functionalifunctionali-ty that allowed participants to send text and images to the researcher via SMS/MMS.

The tool also provided a monitoring application that allowed researchers to vis-ualize and analyze data on the fly. Although it is also Open Source, the devel-opment of the tool seems to have stopped a few years back. MyExperience (Froehlich, Chen, Consolvo, Harrison, & Landay, 2007) and Xensor (Hofte, 2007) seek to make use of all of the sensing capabilities of modern smart phones in order to enhance ESM studies. They allow the combination of auto-matic logging of sensors to gain objective data as well as subjective ESM-like user responses. Both Xensor and MyExperience provide a very modular archi-tecture that allows easy integration of new events or sensors for developers.

MyExperience allows researchers to define events and conditions via XML. For

both systems, recorded data is automatically transferred to a server when an internet connection is available. While the presented tools mainly have focused on supporting ESM studies, others have taken the logging approach even fur-ther. Recon (Jensen, 2009) allows the application to attach to a host application (by source-code integration alone) with the goal of obtaining objective usage logs for evaluating the host application itself. EmotionSense (Rachuri, et al., 2010), a life-logging tool, is similar to SenseCam (Hodges, et al., 2006), except with the goal of researchers being able to automatically recognize emotions.

A few tools have also tried specifically to enhance the diary method, thereby focusing on the ability of the participant to record subjective data without being prompted (e.g., (Hammer, Leichtenstern, & André, 2010), (Jain, 2010), (Khan V.

J., Markopoulos, Eggen, Ijsselsteijn, & Ruyter, de, 2008)). ReconExp (Khan V.

J., Markopoulos, Eggen, Ijsselsteijn, & Ruyter, de, 2008) combines the diary approach with the day-reconstruction method to increase the validity of diary data by conducting tool-supported remote interviews with participants at the end of each day. InfoPal (Jain, 2010) provides a rich set of data-gathering possibili-ties and a graphical user interface on the mobile device that allows participants to create a multi-modal diary entry (e.g., text, voice, video), including combina-tions of modalities.

PocketBee differs from existing tools, as our goal from the beginning has been the combination of diary and ESM designs. This is reflected in the event archi-tecture and the design of the user interface on the mobile device and for the researcher. While other tools may be able to e.g. adapt a diary behavior through the “misuse” of questionnaire items, PocketBee has been designed to support this whole range of research designs natively, as we will illustrate in the follow-ing sections. Furthermore, we focused on the ease of use and learnability of the client user interface. We introduced the notion of Core Questions to help partic-ipants remember their data-gathering task. PocketBee is being developed for the Android OS and uses a client-server architecture. The mobile devices com-municate with the server via their data connectivity. The researcher can define and manage a study remotely; settings are automatically transmitted as an XML document to the mobile devices. These interpret the logic and are notified by a

push service of any changes the researcher may carry out. All material that has been uploaded from devices is accessible remotely in our web-based control center.

3.4.3 Event Architecture and Relationship to the Research Design