Performance in Educational Math Games: Is It a Question of Math Knowledge?

  • Marie MaertensEmail author
  • Mieke Vandewaetere
  • Frederik Cornillie
  • Piet Desmet
Part of the Advances in Game-Based Learning book series (AGBL)


In order to develop game-based learning environments (GBLEs) that accommodate to learners’ needs and individual differences, GBLEs can be enriched with learner models that describe learner profiles from which adaptive instruction can be offered during gameplay. Learner models can encompass several parameters or learner characteristics derived from measurements taken either prior to play (e.g., already available knowledge of the subject matter of which the GBLE is comprised) or during gameplay (i.e., learner behavior in the GBLE). This study makes a case for two skills which may be relevant from the perspective of adaptive gameplay, namely (1) the knowledge or skills with respect to the learning content and (2) the gaming skills. The current study investigates the joint inclusion of both gaming skills and domain knowledge creating learner profiles. In addition, this study sheds light on how performance during gameplay can be attributed to certain learner profiles. To investigate this, a commercially available 3D educational game for primary school children was offered to 53 children of the third grade. Learners’ behavior while playing in the GBLE was captured and logged. Prior to gameplay, math knowledge, and gaming skills were measured. Subsequently, learners’ in-game performance was measured. Results revealed that learners with high or low gaming skills can be distinguished into two learner profiles. More specific, learners with high gaming skills outperformed learners with low gaming skills in more complex mini-games. The findings of this study suggest that a learner’s gaming skills can be taken into account in developing learner profiles and hence in the design and development of GBLEs.


Math game GBLE Gaming skills Mathematic skills Learner models 



This study is based on a research project funded by iMinds Flanders, called Games@School (2012–2014).


  1. Baker, R. S., Habgood, J., Ainsworth, S. E., & Corbett, A. T. (2007). Modeling the acquisition of fluent skill in educational action games. In C. Conati, K. McCoy, & G. Paliouras (Eds.), User modelling 2007 (pp. 17–26). Corfu, Greece: Springer.CrossRefGoogle Scholar
  2. Graesser, A., Jackson, G., & McDaniel, B. (2007). AutoTutor holds conversations with learners that are responsive to their cognitive and emotional states. Educational Technology, 47, 19–22.Google Scholar
  3. Lopes, R., & Bidarra, R. (2011). Adaptivity challenges in games and simulations: A survey. IEEE Transactions on Computational Intelligence and AI in Games, 3(2), 85–99.CrossRefGoogle Scholar
  4. Maertens, M., Vandewaetere, M., Cornillie, F., & Desmet, P. (2014). From pen-and-paper content to educational math game content for children: A transfer with added difficulty. International Journal of Child-Computer Interaction, 2(2), 85–92. doi: 10.1016/j.ijcci.2014.04.001.CrossRefGoogle Scholar
  5. Park, O., & Lee, H. (2003). Adaptive instructional systems. In D. H. Jonassen (Ed.), Handbook of research on educational communications and technology (2nd ed., pp. 651–684). Bloomington, IN: The Associates for Educational Communications and Technology (AECT).Google Scholar
  6. Shute, V. J., Masduki, I., & Donmez, O. (2010). Conceptual framework for modeling, assessing and supporting competencies within game environments. Technology, Instruction, Cognition and Learning, 8(2), 137–161.Google Scholar
  7. Shute, V. J., & Zapata-Rivera, D. (2008). Adaptive technologies. In J. M. Spector, M. D. Merill, J. J. G. van Merriënboer, & M. Driscoll (Eds.), Handbook of research on educational communications and technology (3rd ed., pp. 277–294). Hillsdale, NY: Lawrence Erlbaum.Google Scholar
  8. Sweller, J. (2010). Element interactivity and intrinsic, extraneous, and germane cognitive load. Educational Psychology Review, 22, 123–138.CrossRefGoogle Scholar
  9. Vandercruysse, S., Maertens, M., & Elen, J. (2015). Description of the educational games ‘Monkey Tales: The museum of Anything’. In L. Verschaffel (Ed.), Research on serious games: Descriptions and findings. New York, NY: Springer.Google Scholar
  10. Vandewaetere, M., Desmet, P., & Clarebout, G. (2011). The value of learner characteristics in the development of computer-based adaptive learning environments. Computers in Human Behavior, 27, 118–130.CrossRefGoogle Scholar

Copyright information

© Springer International Publishing Switzerland 2015

Authors and Affiliations

  • Marie Maertens
    • 1
    • 2
    Email author
  • Mieke Vandewaetere
    • 1
    • 2
  • Frederik Cornillie
    • 1
  • Piet Desmet
    • 1
    • 3
  1. 1.ITEC—iMinds—KU Leuven—Kulak, Interactive TechnologiesKortrijkBelgium
  2. 2.Center for Instructional Psychology and Technology, KU LeuvenKortrijkBelgium
  3. 3.Franitalco, Research on French, Italian and Comparative Linguistics, KU LeuvenKortrijkBelgium

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