Investigating Self-Reporting Behavior in Long-Term Studies


Abstract. Self-reporting techniques, such as data logging or a diary, are frequently used in long-term studies, but prone to subjects' forgetfulness and other sources of inaccuracy. We conducted a six-week self-reporting study on smartphone usage in order to investigate the accuracy of self-reported information, and used logged data as ground truth to compare the subjects' reports against. Subjects never recorded more than 70% and, depending on the requested reporting interval, down to less than 40% of actual app usages. They significantly overestimated how long they used apps. While subjects forgot self-reports when no automatic reminders were sent, a high reporting frequency was perceived as uncomfortable and burdensome. Most significantly, self-reporting even changed the actual app usage of users and hence can lead to deceptive measures if a study relies on no other data sources.
With this contribution, we provide empirical quantitative long-term data on the reliability of self-reported data collected with mobile devices. We aim to make researchers aware of the caveats of self-reporting and give recommendations for maximizing the reliability of results when conducting large-scale, long-term app usage studies.

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GymSkill: Mobile Exercise Skill Assessment to Support Personal Health and Fitness


Abstract. GymSkill, a personal trainer for the smartphone, is contributing to regular physical activity and a healthier lifestyle. GymSkill incorporates automated exercise skill assessment, allowing to track training success as well as the need for improvement. Precise and targeted feedback can increase satisfaction through more efficient training, thereby addressing the important and often neglected aspect of intrinsic motivation. In a fi rst 5-day study, users attested GymSkill the potential to reach training goals faster and to support maintaining long-term motivation. The video shows the app, its features, and the training.

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MobiDics - Improving University Education With A Mobile Didactics Toolbox


Abstract. MobiDics is a mobile didactic platform for smartphones and tablets, targeted at university teaching sta . It eases structuring courses and the targeted application of didactic techniques to support learning, in order to improve the quality of university education. MobiDics enables peer learning through cooperative experience sharing and academic exchange about successfully applied didactic techniques, creating a social network of teaching personnel. Young teachers benefi t from expert knowledge and multimedia-based example teaching scenarios. As a social mobile knowledge exchange system, MobiDics is intended to increase satisfaction in teaching and to improve the quality of university education.

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ROS on Android - Porting the Robot Operating System to the Android Platform


In this video, the integration of the Android platform with ROS (Robot Operating System) using rospy is shown. The video illustrates the communication using basic ROS topics as text and images and shows a light control scenario as example.

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Developing Intelligent Environments with the Robot Operating System (ROS)


This video illustrates the development and prototyping of intelligent environments using ROS.

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A Whiteboard Cleaning Robot - Robotic Assistants for Office Environments


This video illustrates the inclusion of robots in Intelligent Environments. A scenario using a whiteboard cleaning robot as robotic assistant in an augmented office is demonstrated.

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A Cognitive Cup as Example for Intelligent Objects supporting both Humans and Robots in Intelligent Environments


Cognitive Objects can support both humans and robots in intelligent environments. The video shows a cognitive cup that is usable like a normal cup, but augmented with sensors and communication abilities, which eases robotic interaction with the object.

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