Evaluating Adaptive Feedback in an Educational Computer Game

Conati, Cristina; Manske, Micheline

doi:10.1007/978-3-642-04380-2_18

Cited by 42 publications

(22 citation statements)

References 14 publications

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“…While there is currently very little research on adaptation of gamification, considerable research has been devoted to adaptation in serious games (and learning games in particular). Most methods propose a way to adjust the level of difficulty, for example by adapting the help given to players [41], the training intensity [42], or the educational scenario [43]. Besides these contributions to the "serious aspect" of the game, some proposals focus on making games more entertaining, for example by adapting the circuit of a car racing game [44] or the width of the gaps in a platform game [45].…”

Section: Adaptation Of Games and Gamificationmentioning

confidence: 99%

Adaptive Gamification for Learning Environments

Lavoué

Monterrat²,

Desmarais

et al. 2019

IEEE Trans. Learning Technol.

173

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: Adaptation Of Games and Gamificationmentioning

confidence: 99%

Adaptive Gamification for Learning Environments

Lavoué

Monterrat²,

Desmarais

et al. 2019

IEEE Trans. Learning Technol.

173

110

View full text Add to dashboard Cite

show abstract

“…To support the results, the authors cite a warning from Charsky and Ressler (2011) to educators: "Do not dilute the potential effectiveness of games by taking away the one distinct attribute that gives them their advantage -play". Conati and Manske (2009) made similar findings in their study of feedback in a game that teaches factorisation to children. The game initially included a virtual agent helping players with timely interventions.…”

Section: Feedback Should Minimise Interruptions To the Gameplaymentioning

confidence: 57%

Specification and evaluation of an assessment engine for educational games: Integrating learning analytics and providing an assessment authoring tool

Chaudy

Connolly

2019

Entertainment Computing

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Educational games are highly engaging, motivating and they offer many advantages as a supplementary tool for education. However, the development of educational games is very complex, essentially because of its multidisciplinary aspect. Fully integrating assessment is challenging and the games created are too often distributed as blackboxes; unmodifiable by the teachers and not providing much insight about the gameplays. We propose an assessment engine, EngAGe, to overcome these issues. EngAGe is used by both developers and educators. It is designed to separate game and assessment. Developers use it to easily integrate assessment into educational games and teachers can then modify the assessment and visualise learning analytics via an online interface. This paper focuses on EngAGe's benefits for games developers. It presents a quantitative evaluation carried out with 36 developers (7 experienced and 29 students). Findings were very positive: every feature of the engine was rated useful and EngAGe received a usability score of 64 using the System Usability Scale. A Mann-Whitney U test showed a significant difference in usability (Z=-3.34, p<0.002) between novice developers (mean=56) and experienced developers (mean=71) but none in terms of usefulness. This paper concludes that developers can use EngAGe effectively to integrate assessment and learning analytics in educational games.

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“…We also use players' profiles in order to personalize comments and provide adaptive social feedback. The latter is widely used in pedagogical agents with great success [7][8][9][10][11]. Such agents are intended to boost learning experience and are incorporated into educational games.…”

Section: Related Workmentioning

confidence: 99%

“…As teaching and learning are both social activities, game agents need to be informed about players' social characteristics and use them to control the gameplay and come up with stimulating and engaging comments that will motivate the students to play and learn. The fact that agents with adaptive social feedback can be used to boost the overall gaming experience and improve the learning process is widely accepted, and a lot of scientific work has been done towards this direction [7][8][9][10][11].…”

Section: Introductionmentioning

confidence: 99%

A Framework for Adaptive Game Presenters with Emotions and Social Comments

Karuzaki

Savidis

2012

International Journal of Computer Games Technology

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More and more games today try to adjust their gameplay to fit individual players; however, little work has been carried out in the same direction towards game presenter characters. Game commentary should take into account players' personalities along with game progress in order to achieve social player-adapted comment delivery that boosts the overall gameplay, engages the players, and stimulates the audience. In our work, we discuss a framework for implementing artificial game presenter characters that are based on game actions and players' social profiles in order to deliver knowledgeable, socially oriented comments. Moreover, the presented framework supports emotional facial expressions for the presenters, allowing them to convey their emotions and thus be more expressive than the majority of the commentary systems today. We prove our concept by developing a presenter character for multiplayer tabletop board games which we further put under usability evaluation with 9 players. The results showed that game sessions with presenter characters are preferred over the plain version of the game and that the majority of the players enjoy personalized social-oriented comments expressed via multimedia and emotions.

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Evaluating Adaptive Feedback in an Educational Computer Game

Cited by 42 publications

References 14 publications

Adaptive Gamification for Learning Environments

Adaptive Gamification for Learning Environments

Specification and evaluation of an assessment engine for educational games: Integrating learning analytics and providing an assessment authoring tool

A Framework for Adaptive Game Presenters with Emotions and Social Comments

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