Studying the learning model of smartphone feedback applications: the case of the step counter

  • A. Dijkstra
  • E. Kooy

Abstract

Background The Learning model of Smartphone Feedback Applications (LSFA) states that many users of feedback application, such as the Step Counter (SC), stop using the device because they learned enough about the feedback parameters, making feedback from the device unnecessary. The concept of learning about one’s steps was studied here. Methods Ten participants were asked to wear the (FitBit Zip) Step Counter for 10 weeks. Participant’s learning experiences were assessed weekly by a self-report on whether the participant’s perception of the own physical activity had changed because of the SC. In addition, secondary learning was tested in 3 monthly measurements. Findings The quantitative data are presented by individual, showing a variety of individual lines and curves with regard to learning. The data are qualitatively analyzed by looking for meaningful patterns over time. One pattern suggests no experience of learning at all during the ten weeks. Another pattern showed a high learning experience that stayed high during the ten weeks. A last pattern showed declined learning in the ten week interval. Discussion The data stress that learning as proposed by the LSFA may occur, but may depend on people’s fore knowledge and that the learning speed may vary and may at least take several weeks. The LSFA and the present data suggest that the SC might be embedded in a learning protocol (e.g., supported by the smartphone app) that directs and boosts learning to optimize the effects of its feedback.
Published
2017-12-31
Section
Oral presentations