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Autor(en): Rzayev, Rufat
Titel: A tool for episodic memory reflection based on implicit diary entries
Sonstige Titel: Ein Tool für episodische Gedächtnisreflexion basierend auf impliziten Tagebucheinträgen
Erscheinungsdatum: 2016
Dokumentart: Abschlussarbeit (Master)
Seiten: 57
URI: http://nbn-resolving.de/urn:nbn:de:bsz:93-opus-ds-93437
http://elib.uni-stuttgart.de/handle/11682/9343
http://dx.doi.org/10.18419/opus-9326
Zusammenfassung: Paper or digital diaries are usually used by people to record their everyday life. Diary entries can be revisited at any time and hence help people to recall previous days. The information in diaries is mostly created explicitly. By manually capturing personal related information, it can be difficult for users to decide which information is important to record. Furthermore, it is difficult or impossible for persons to observe all their behaviors. Therefore, by manually recording diary entries, some valuable information can be left unrecorded. On the other hand, mobile devices, like smartphones and tablets, can automatically collect a variety of personal related information. In the last few years, many wearable devices have appeared on the market, that support automatically tracking of personal information including user’s sleep and movement behavior. Data collected using these devices can be used to augment the information in diaries. Reviewing diary entries, which can also be used as memory cues can facilitate people to recall previous events. In this work, we explored whether reflection on implicit recorded personal information affects recall. We built an Android application that implicitly collects personal related data and prompts users to reflect on them. Furthermore, the application provides users the opportunity to quiz themselves about the collected data. We conducted a study with 11 participants, and the application generated overall more than 7000 recordings. We found that reflection improves recall of implicitly recorded personal information. Furthermore, we reported the automatically captured information types that are effective to support the recall of previous days.
Enthalten in den Sammlungen:05 Fakultät Informatik, Elektrotechnik und Informationstechnik

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