A Player Model for Adaptive Gamification in Learning Environments

Monterrat, Baptiste; Desmarais, Michel C.; Lavoué, Élise; George, Sébastien

doi:10.1007/978-3-319-19773-9_30

Cited by 64 publications

(59 citation statements)

References 14 publications

(12 reference statements)

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“…Whereas matrix B can be directly obtained from the answers to the BrainHex questionnaire over the 7 traits of the gamer profile, matrix A must be derived by some other means. In a previous study, we compared an Amatrix given by experts and an A-matrix extracted empirically from users' preferences [53]. As the expert-derived A-matrix was more accurate, we shall base ourselves on it for the adaptation process.…”

Section: Estimating the A-matrixmentioning

confidence: 99%

Adaptive Gamification for Learning Environments

Lavoué

Monterrat²,

Desmarais

et al. 2019

IEEE Trans. Learning Technol.

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163

110

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In spite of their effectiveness, learning environments often fail to engage users and end up under-used. Many studies show that gamification of learning environments can enhance learners' motivation to use learning environments. However, learners react differently to specific game mechanics and little is known about how to adapt gaming features to learners' profiles. In this paper, we propose a process for adapting gaming features based on a player model. This model is inspired from existing player typologies and types of gamification elements. Our approach is implemented in a learning environment with five different gaming features, and evaluated with 266 participants. The main results of this study show that, amongst the most engaged learners (i.e. learners who use the environment the longest), those with adapted gaming features spend significantly more time in the learning environment. Furthermore, learners with features that are not adapted have a higher level of amotivation. These results support the relevance of adapting gaming features to enhance learners' engagement, and provide cues on means to implement adaptation mechanisms.

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Section: Estimating the A-matrixmentioning

confidence: 99%

Adaptive Gamification for Learning Environments

Lavoué

Monterrat²,

Desmarais

et al. 2019

IEEE Trans. Learning Technol.

Self Cite

163

110

View full text Add to dashboard Cite

show abstract

“…Studies: Half of the reviewed papers present studies that rely on an adaptive gamification system in an educational setting [18,19,20,25,28,30,31,34,35,36]. These papers provide valuable results about the impact of adaptive gamification on learner motivation and performance.…”

Section: Architecturesmentioning

confidence: 99%

“…Twelve of the papers reviewed [2,4,6,9,10,11,18,19,20,23,34,35] used the term "game element" to describe the low level implementations they use, such as points, levels, leaderboards, progress. Four papers from the same authors [25,28,29,30] use the term "game features" to present the same level of implementation. Knutas et al [21,22] use the terms "game like elements".…”

Section: Architecturesmentioning

confidence: 99%

“…Player types are archetypal reasons or motivations that explain why players play games. The papers reviewed used either the Bartle Player types [3] (used in two papers [6,23]), the Brainhex player satisfaction model [32] (used in three papers [25,28,36]), the Hexad player types [37] (used in one paper [31]), or the categories of players described by Ferro et al [14] (used in one paper [4]). These different categorisations of players types describe the reasons why players prefer different games.…”

Section: Information Used For Adaptation and Its Effect On Game Elementsmentioning

confidence: 99%

“…Long studies Seven of the reviewed studies lasted more than three weeks [18,25,28,30,31,34,35]. Four studies showed generally positive results [18,28,31,35]. Roosta et al [35] presented learners with a different game element based on their motivation type.…”

Section: Short Studiesmentioning

confidence: 99%

See 2 more Smart Citations

Adaptive Gamification in Education: A Literature Review of Current Trends and Developments

Hallifax

Serna

Marty

et al. 2019

Lecture Notes in Computer Science

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Gamification, the use of game elements in non-game settings, is more and more used in education to increase learner motivation, engagement, and performance. Recent research in the gamification field suggests that to be effective, the game elements should be tailored to learners. In this paper, we perform an in-depth literature review on adaptive gamification in education in order to provide a synthesis of current trends and developments in this field. Our literature review addresses 3 research questions: (1) What are the current kinds of contributions to the field? (2) What do the current contributions base their adaptation on, and what is the effect of this adaptation on the gamified system? (3) What is the impact of the adaptive gamification, and how is this impact measured? We also provide future research guidelines in the form of three needs that should be fulfilled for exploring this field.

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