A quest for meta-learning gains in a physics serious game

Westera et al. (2008, p. 421) rightly summarize this perceived tension: “Especially in higher education, the mental mode of learning which reflects profundity, reflection, concentration and perseverance seems to conflict with the mental mode of gaming which is commonly associated with amusement, fun and relaxation”. With structured reflection embedded in the flow of learning, Elektra breaks through the action-oriented paradigm and the pragmatism often associated with gaming.

The trailer of the game is available at: http://​player.​vimeo.​com/​video/​24224447?​title=​0&​amp;byline=​0&​amp;portrait=​0&​amp;color=​ff2e90. Technical documents can be found at, www.​elektra-project.​org, section “Download”.

A literature review and an empirical pre-study (23 participants) was carried out in order to identify the most relevant metric to express confidence on the slider (for an extensive discussion of this topic, see Castaigne 2007). Based on the different arguments, it was decided that the Confidence slider would be graduated with the values 0, 20, 40, 60, 80, and 100 % confidence.

The selection of the pedagogical endeavours of the game came on top of several work packages in the project: European curricula comparisons, breakdown of identified skills in various granularity levels, distribution of the retained skills in the entire game play. This work, with its difficulties and limitations, is described in Petit et al. (2007).

Any learning method has its shortcomings, but well-thought aggregates can combine their strengths. The diversification of learning methods and approaches is not only a matter of students’ motivation enhancement but also of epistemology (Moss 2002; Verpoorten et al. 2007). For this reason, learning games should more often be contextualised within a larger learning sequence and not conceived as stand-alone vectors of learning, as recommended by Quinn (2005, p. 14), “I do not believe that these engaging learning experiences of games will (or should be expected to), by themselves, lead to learning. I advocate discussion around the experience, and connecting learner actions to the underlying concept. As yet, computers are not quite capable of supporting such dialogue. Self-directed learners may be capable of facilitating their own reflection, but it’s not the way to bet (though I believe strongly that meta-learning, or learning to learn, is a key leverage point for the future). So although such gaming environments are not sufficient, they are necessary; we need engaging experiences to motivate learners to attend to the content, give them rich practice opportunities, and provide fodder for discussion and refinement of their understanding”. De Freitas (2006, p. 11) puts a similar emphasis on embedding learning games in larger instructional learning sequences. By curiosity, the young players of Elektra were asked whether they would prefer gaming before or after a lecture on light properties. Results gave a striking even proportion of “before” and “after” answers (Verpoorten et al. 2011, p. 281).