Lifelong Learning with a Digital Math Game: Performance and Basic Experience Differences Across Age

  • Simon GreiplEmail author
  • Korbinian Moeller
  • Kristian Kiili
  • Manuel Ninaus
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 11899)


Gaming is acknowledged as a natural way of learning and established as a mainstream activity. Nevertheless, gaming performance and subjective game experience were hardly examined across adult age groups for which the game was not intended to. In contrast to serious games as specific tools against a natural, age-related decline in cognitive performance, we evaluated performance and subjective experiences of the established math learning game Semideus across three age groups from 19 to 79. Observed decline in performance in terms of processing speed were not exclusively predicted by age, but also by gaming frequency. Strongest age-related drops of processing speed were found for the middle-aged group aged 35 to 59 years. On the other hand, more knowledge-dependent performance measures like the amount of correctly solved problems remained comparably stable. According to subjective ratings, the middle-aged group experienced the game as less fluent and automatic compared to the younger and older groups. Additionally, the elderly group of participants reported fewer negative attitudes towards technology than both younger groups. We conclude that, albeit performance differences with respect to processing speed, subjective gaming experience stayed on an overall high positive level. This further encourages the use of games for learning across age.


Game-based learning Life-long learning Reliability Applicability Number-line estimation User-experience Elderly 


  1. 1.
    Lenhart, A., Kahne, J., Middaugh, E., Macgill, A.R., Evans, C., Vitak, J.: Teens’ gaming experiences are diverse and include significant social interaction and civic engagement. Pew Internet & American Life Project (2008)Google Scholar
  2. 2.
  3. 3.
    Huizinga, J., Flitner, A.: Homo Ludens: vom Ursprung der Kultur im Spiel. Rowohlt Taschenbuch Verlag, Hamburg (2017)Google Scholar
  4. 4.
    Hainey, T., Connolly, T.M., Boyle, E.A., Wilson, A., Razak, A.: A systematic literature review of games-based learning empirical evidence in primary education. Comput. Educ. 102, 202–223 (2016). Scholar
  5. 5.
    Edwards, C.P.: Three approaches from Europe: Waldorf, Montessori, and Reggio Emilia. Early Child. Res. Pract. 4, n1 (2002)Google Scholar
  6. 6.
    Romero, M., Ouellet, H., Sawchuk, K.: Expanding the game design play and experience framework for game-based lifelong learning (gd-lll-pe). In: Romero, M., Sawchuk, K., Blat, J., Sayago, S., Ouellet, H. (eds.) Game-Based Learning Across the Lifespan. AGL, pp. 1–11. Springer, Cham (2017). Scholar
  7. 7.
    Ritterfeld, U., Cody, M.J., Vorderer, P. (eds.): Serious Games: Mechanisms and Effects. Routledge, New York (2009)Google Scholar
  8. 8.
    Greipl, S., Moeller, K., Ninaus, M.: Potential and limits of game-based learning. Int. J. Technol. Enhanced Learn. (in press)Google Scholar
  9. 9.
    Bonnechère, B., Jansen, B., Omelina, L., Van Sint Jan, S.: The use of commercial video games in rehabilitation: a systematic review. Int. J. Rehabil. Res. 39, 277–290 (2016). Scholar
  10. 10.
    Nguyen, H., et al.: Impact of Serious Games on Health and Well-being of Elderly: A Systematic Review, vol. 10Google Scholar
  11. 11.
    Rego, P., Moreira, P.M., Reis, L.P.: Serious games for rehabilitation: a survey and a classification towards a taxonomy. In: 5th Iberian Conference on Information Systems and Technologies, pp. 1–6 (2010)Google Scholar
  12. 12.
    Fisk, A.D., Czaja, S.J., Rogers, W.A., Charness, N., Czaja, S.J., Sharit, J.: Designing for Older Adults: Principles and Creative Human Factors Approaches, 2nd edn. CRC Press (2018).
  13. 13.
    Farage, M.A., Miller, K.W., Ajayi, F., Hutchins, D.: Design principles to accommodate older adults. Glob. J. Health Sci. 4 (2012).
  14. 14.
    Pallavicini, F., Ferrari, A., Mantovani, F.: Video games for well-being: a systematic review on the application of computer games for cognitive and emotional training in the adult population. Front. Psychol. 9 (2018).
  15. 15.
    Romero, M., Sawchuk, K., Blat, J., Sayago, S., Ouellet, H. (eds.): Game-Based Learning Across the Lifespan: Cross-Generational and Age-Oriented Topics. Springer, Cham (2017).
  16. 16.
    De Schutter, B., Roberts, A.R., Franks, K.: Miami six-o: lessons learned from an intergenerational game design workshop. In: Romero, M., Sawchuk, K., Blat, J., Sayago, S., Ouellet, H. (eds.) Game-Based Learning Across the Lifespan. AGL, pp. 13–27. Springer, Cham (2017). Scholar
  17. 17.
    De Schutter, B., Vanden Abeele, V.: Towards a gerontoludic manifesto. Anthropol. Aging 36, 112–120 (2015). Scholar
  18. 18.
    Lee, H., et al.: Examining cognitive function across the lifespan using a mobile application. Comput. Hum. Behav. 28, 1934–1946 (2012). Scholar
  19. 19.
    Bonnechère, B., Sholukha, V., Omelina, L., Van Vooren, M., Jansen, B., Van Sint Jan, S.: Suitability of functional evaluation embedded in serious game rehabilitation exercises to assess motor development across lifespan. Gait Posture 57, 35–39 (2017). Scholar
  20. 20.
    Teulier, C., Lee, D.K., Ulrich, B.D.: Early gait development in human infants: plasticity and clinical applications: early gait development. Dev. Psychobiol. 57, 447–458 (2015). Scholar
  21. 21.
    Trewartha, K.M., Garcia, A., Wolpert, D.M., Flanagan, J.R.: Fast but fleeting: adaptive motor learning processes associated with aging and cognitive decline. J. Neurosci. 34, 13411–13421 (2014). Scholar
  22. 22.
    Wittland, J., Brauner, P., Ziefle, M.: Serious games for cognitive training in ambient assisted living environments – a technology acceptance perspective. In: Abascal, J., Barbosa, S., Fetter, M., Gross, T., Palanque, P., Winckler, M. (eds.) INTERACT 2015. LNCS, vol. 9296, pp. 453–471. Springer, Cham (2015). Scholar
  23. 23.
    Beddington, J., Cooper, C.L.: The mental wealth of nations. Nature 455, 3 (2008)CrossRefGoogle Scholar
  24. 24.
    Siegler, R.S., Opfer, J.E.: The development of numerical estimation: evidence for multiple representations of numerical quantity. Psychol. Sci. 14, 237–243 (2003). Scholar
  25. 25.
    Geary, D.C., Hoard, M.K., Nugent, L., Byrd-Craven, J.: Development of number line representations in children with mathematical learning disability. Dev. Neuropsychol. 33, 277–299 (2008). Scholar
  26. 26.
    Cavanaugh, J.C., Blanchard-Fields, F.: Adult Development and Aging. Wadsworth/Thomson Learning, Belmont (2006)Google Scholar
  27. 27.
    Salthouse, T.A.: The Processing-Speed Theory of Adult Age Differences in Cognition, vol. 26Google Scholar
  28. 28.
    Perttula, A., Kiili, K., Lindstedt, A., Tuomi, P.: Flow experience in game based learning – a systematic literature review. Int. J. Serious Games 4 (2017).
  29. 29.
    Laugwitz, B., Schrepp, M., Held, T.: Konstruktion eines Fragebogens zur Messung der User Experience von Softwareprodukten. In: Heinecke, A.M., Paul, H. (eds.) Mensch und Computer 2006: Mensch und Computer im Strukturwandel, pp. 125–134. Oldenbourg Verlag, München (2006)Google Scholar
  30. 30.
    Giannopoulos, I., Kiefer, P., Raubal, M.: GazeNav: gaze-based pedestrian navigation. In: Proceedings of the 17th International Conference on Human-Computer Interaction with Mobile Devices and Services - MobileHCI 2015, pp. 337–346. ACM Press, Copenhagen (2015).
  31. 31.
    Czaja, S.J., Sharit, J.: Age differences in attitudes toward computers. J. Gerontol. B Psychol. Sci. Soc. Sci. 53B, P329–P340 (1998). Scholar
  32. 32.
    Eastman, J.K., Iyer, R.: The impact of cognitive age on Internet use of the elderly: an introduction to the public policy implications. Int. J. Consum. Stud. 29, 125–136 (2005). Scholar
  33. 33.
    Ninaus, M., Kiili, K., McMullen, J., Moeller, K.: Assessing fraction knowledge by a digital game. Comput. Hum. Behav. 70, 197–206 (2017). Scholar
  34. 34.
    Rheinberg, F., Vollmeyer, R., Engeser, S.: Die erfassung des flow-erlebens (2003)Google Scholar
  35. 35.
    Karrer, K., Glaser, C., Clemens, C., Bruder, C.: Technikaffinität erfassen–der Fragebogen TA-EG. Der Mensch im Mittelpunkt technischer Systeme. 8, 196–201 (2009)Google Scholar

Copyright information

© Springer Nature Switzerland AG 2019

Authors and Affiliations

  1. 1.Leibniz-Institut für WissensmedienTübingenGermany
  2. 2.Department of PsychologyEberhard-Karls UniversityTübingenGermany
  3. 3.TUT Game LabTampere University of TechnologyPoriFinland
  4. 4.LEAD Graduate School and Research NetworkUniversity of TübingenTübingenGermany

Personalised recommendations