Connecting dots of digital learning

Adaptivity in Learning Games and Simulations (#GBL)

Data-driven adaptivity in learning process is getting attention recently, but adaptivity in learning or entertainment games isn’t a new research interest. One good reading is this paper in IEEE TRANSACTIONS ON COMPUTATIONAL INTELLIGENCE AND AI IN GAMES: Adaptivity Challenges in Games and Simulations: a Survey.

Static game content and its pre-defined variations, based on low-resolution profiles, all lead to games and simulations that can be played in an impersonal, predictable and inflexible fashion and that can fail to appeal to broader audiences. For games with purposes other than entertainment, such as serious games and simulations, these problems can become more acute. Players who need to capture or practice a certain skill, all have different learning abilities and training needs.

In computer games and simulations, content is often rather static and rigid. As a result, its pre-scripted nature can lead to predictable and impersonal gameplay, while alienating unconventional players. Adaptivity in games has therefore been recently proposed to overcome these shortcomings and make games more challenging and appealing.

In this article we survey present research on game adaptivity, identifying and discussing the main challenges, and pointing out some of the most promising directions ahead. We first survey the purposes of adaptivity, as the principles that could steer an adaptation and generation engine. From this perspective, we proceed to thoroughly discuss adaptivity’s targets and methods.

Current advances and successes in this emerging field point to many yet unexplored research opportunities. Among them, we discuss the use of gameplay expectations, learning preferences and assessment data in the integrated adaptation of game worlds, scenarios and quests.

We conclude that, among other methods, procedural content generation and semantic modeling can powerfully combine to create off-line customized content and on-line adjustments to game worlds, scenarios and quests. These and other promising methods, deserving ample research efforts, can therefore be expected to significantly contribute towards making games and simulations even more unpredictable, effective and fun.

The paper surveyed adaptivity’s purposes, i.e. the generic principles that support player modeling and experience prediction and steer game adaptation methods.

A. Entertainment games

B. Serious games and simulations

C. Assessment in serious games and simulations

And then adaptive game components, off-line adaptivity, on-line adaptivity for different game genres are reviewed. Regarding the methods which can support adaptivity, some important advances have already been achieved with off-line and on-line techniques. For offline adaptivity, customized content generation seems the most promising method in terms of future research. For online adaptivity, on-line adjustment of game worlds and scenarios is likely to achieve better results.

Fig. 6 summarizes the challenges we discussed in this article and how they relate to each other. Gameplay expectations, learning preferences or assessment data can be used to guide both off-line customized generation and on-line adaptivity of integrated game worlds and scenarios.

adaptive learning

Adaptivity is already establishing itself as a rapidly maturing field regarding its purposes. Current advances also show that work is already being laid out to approach some still open issues. For both entertainment games and simulations, the main goal lies in materializing Magerko’s vision of adapting to match the player’s real motivations for playing. Player-centered game adaptivity is highly anticipated in both serious and entertainment games.

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