Where Is My Time? Identifying Productive Time of Lifelong Learners for Effective Feedback Services

  • Bernardo Tabuenca
  • Marco Kalz
  • Dirk Börner
  • Stefaan Ternier
  • Marcus Specht
Part of the Communications in Computer and Information Science book series (CCIS, volume 439)


Lifelong learners are confronted with a broad range of activities they have to manage every day. In most cases they have to combine learning, working, family life and leisure activities throughout the day. Hence, learning activities from lifelong learners are disrupted. The difficulty to find a suitable time slot to learn during the day has been identified as the most frequent cause. In this scenario mobile technologies play an important role since they can keep track of the most suitable moments to accomplish specific learning activities in context. Sampling of learning preferences on mobile devices is a key benchmarks for lifelong learners to become aware on which learning task suits in which context, to set realistic goals and to set aside time to learn on a regular basis. The contribution of this manuscript is twofold: first, a classification framework for modelling lifelong learners’ preferences is presented based on a literature review; second, a mobile application for experience sampling is piloted aiming to identify which are the preferences from lifelong learners regarding when, how and where learning activities can be integrated.


lifelong learning experience sampling mobile learning selfregulated learning reflection 


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  1. 1.
    Eurostat, Lifelong learning statistics - Statistics Explained (2012) (June 5, 2013), (accessed June 3, 2013)
  2. 2.
    Kalz, M.: Lifelong learning and its support with new technologies. In: Smelser, N.J., Baltes, P.B. (eds.) International Encyclopedia of the Social and Behavioral Sciences. Pergamon, Oxford (in press)Google Scholar
  3. 3.
    Metzger, L.C., Cleach, O.: White-collar telework: Between an overload and learning a new organization of time. Sociologie du Travail, 433–450 (2004)Google Scholar
  4. 4.
    Tabuenca, B., Ternier, S., Specht, M.: Supporting lifelong learners to build personal learning ecologies in daily physical spaces. International Journal of Mobile Learning Organisation 7, 177–196 (2013)CrossRefGoogle Scholar
  5. 5.
    European Commission: Key competences for lifelong learning. An European reference framework (2007)Google Scholar
  6. 6.
    Tabuenca, B., Verpoorten, D., Ternier, S., Westera, W., Specht, M.: Fostering reflective practice with mobile technologies. In: Proceedings of the 2nd Workshop on Awareness and Reflection in Technology Enhanced Learning (2012)Google Scholar
  7. 7.
    Hattie, J., Timperley, H.: The Power of Feedback. Rev. Educ. Res. 77, 81–112 (2007)CrossRefGoogle Scholar
  8. 8.
    Leone, C., Richards, H.: Classwork and homework in early adolescence: The ecology of achievement. J. Youth Adolesc. 18, 1989 (1989) Google Scholar
  9. 9.
    Crocker, J., Karpinski, A., Quinn, D.M., Chase, S.K.: When Grades Determine Self-Worth: Consequences of Contingent Self-Worth for Male and Female Engineering and Psychology Majors. J. Pers. Soc. Psychol. 85, 507–516 (2003)CrossRefGoogle Scholar
  10. 10.
    Church, K., Cherubini, M., Oliver, N.: A large-scale study of daily information needs captured in situ. ACM Trans. Comput. Interact. 21, 1–46 (2014)CrossRefGoogle Scholar
  11. 11.
    Hektner, J., Schmidt, J., Csikszentmihalyi, M.: Experience sampling method: Measuring the quality of everyday life (2007)Google Scholar
  12. 12.
    Hormuth, S.: The sampling of experiences in situ. J. Pers. 54, 1986 (1986)Google Scholar
  13. 13.
    Consolvo, S., Walker, M.: Using the experience sampling method to evaluate ubicomp applications. IEEE Pervasive Comput. (2003)Google Scholar
  14. 14.
    De Jong, T., Specht, M., Koper, R.: A reference model for mobile social software for learning. Int. J. Contin. Eng. Educ. Life-Long Learn. 18, 118 (2008)Google Scholar
  15. 15.
    Specht, M.: Learning in a technology enhanced world (2009)Google Scholar
  16. 16.
    Nielsen, J., Clemmensen, T., Yssing, C.: Getting access to what goes on in people’s heads?: reflections on the think-aloud technique. In: NordiCHI, pp. 101–110 (2002)Google Scholar
  17. 17.
    Ternier, S., Klemke, R., Kalz, M., Specht, M.: ARLearn: augmented reality meets augmented virtuality. J. Univers. Comput. Sci. - Technol. Learn. across Phys. Virtual Spaces [Special Issue] 18, 2143–2164 (2012)Google Scholar
  18. 18.
    Gros, B., Barbera, E., Kirshner, P.: Time factor in e-learning: Impact literature review. eLearn Cent. Res. Pap. Ser., 16–31 (2010)Google Scholar
  19. 19.
    Livingstone, D., Stowe, S.: Work time and learning activities of the continuously employed: A longitudinal analysis, 1998-2004. J. Work. Learn. 19, 17–31 (2007)CrossRefGoogle Scholar
  20. 20.
    Intille, S.S., Rondoni, J., Kukla, C., Ancona, I., Bao, L.: A context-aware experience sampling tool. In: CHI 2003 Ext. Abstr. Hum. Factors Comput. Syst. - CHI 2003, p. 972 (2003)Google Scholar
  21. 21.
    Conner, T.: Experience Sampling and Ecological Momentary Assessment with Mobile Phones (2013)Google Scholar
  22. 22.
    Khan, V.J., Markopoulos, P.: Experience Sampling: A workbook about the method and the tools that support it, Eindhoven (2009)Google Scholar

Copyright information

© Springer International Publishing Switzerland 2014

Authors and Affiliations

  • Bernardo Tabuenca
    • 1
  • Marco Kalz
    • 1
  • Dirk Börner
    • 1
  • Stefaan Ternier
    • 1
  • Marcus Specht
    • 1
  1. 1.Welten Institute, Research Centre for Learning, Teaching and TechnologyOpen University of the NetherlandsHeerlenThe Netherlands

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