Adaptive Serious Games Using Agent Organizations

Westra, Joost; Hasselt, Hado van; Dignum, Frank; Dignum, Virginia

doi:10.1007/978-3-642-11198-3_14

Cited by 21 publications

(10 citation statements)

References 6 publications

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“…These two ideas have been used to adjust task difficulty of serious games and learning environments, so that the user remains in ZPD or the flow channel when performing the task. Examples include intelligent learning environments that keep track of learners' performance and provide guidance to keep the learners in ZPD (2,(13)(14) , and serious games that are augmented with adaptation mechanisms that match task difficulty to user performance (15)(16)(17) . The second category has been influenced by selfdetermination theory (SDT), which has been applied to enhancing motivation in serious games and learning environments.…”

Section: Introductionmentioning

confidence: 99%

The effect of different difficulty adaptation strategies on enjoyment and performance in a serious game for memory training

Nagle¹,

Novak

Wolf³

et al. 2014

2014 IEEE 3nd International Conference on Serious Games and Applications for Health (SeGAH)

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Objective: The goal of this study was to evaluate two kinds of difficulty adaptation techniques in terms of enjoyment and performance in a simple memory training game: one based on difficultyperformance matching ("task-guided") and the other based on providing a high degree of control/choice ("user-guided"). Methods: Performance and enjoyment are both critical in making serious games effective. Therefore the adaptations were based on two different approaches that are used to sustain performance and enjoyment in serious games: 1) adapting task difficulty to match user performance by leveraging the theories of zone of proximal development and flow, thus maximizing performance that can then lead to increased enjoyment and 2) providing a high degree of control and choice by using constructs from self-determination theory, which maximizes enjoyment, that can potentially increase performance. 24 participants played a simple memory training serious game in a fully randomized, repeated measures design. The primary outcome measures were enjoyment and performance. Results: Enjoyment was significantly greater in user-guided (p < 0.05), whereas performance was significantly greater in taskguided (p < 0.05). Conclusion: The results suggest that a trade-off between maximizing performance and maximizing enjoyment could be achieved by combining the two approaches into a "hybrid" adaptation mode that gives users a high degree of control in setting difficulty, but also advises them about optimizing performance.Other titles: O efeito de diferentes adaptações de dificuldade em estratégias de diversão e performance em serious games para trieno de memória El efecto de diferentes adaptaciones de dificultades en estrategias de diversion y performance en serious games para entrenamiento de memoria ABSTRACTObjective: The goal of this study was to evaluate two kinds of difficulty adaptation techniques in terms of enjoyment and performance in a simple memory training game: one based on difficulty-performance matching ("task-guided") and the other based on providing a high degree of control/choice ("user-guided"). Methods: Performance and enjoyment are both critical in making serious games effective. Therefore the adaptations were based on two different approaches that are used to sustain performance and enjoyment in serious games: 1) adapting task difficulty to match user performance by leveraging the theories of zone of proximal development and flow, thus maximizing performance that can then lead to increased enjoyment and 2) providing a high degree of control and choice by using constructs from self-determination theory, which maximizes enjoyment, that can potentially increase performance. 24 participants played a simple memory training serious game in a fully randomized, repeated measures design. The primary outcome measures were enjoyment and performance. Results: Enjoyment was significantly greater in user-guided (p < 0.05), whereas performance was significantly greater in task-guided (p < 0.05). Conclusion: The results sug...

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Section: Introductionmentioning

confidence: 99%

The effect of different difficulty adaptation strategies on enjoyment and performance in a serious game for memory training

Nagle¹,

Novak

Wolf³

et al. 2014

2014 IEEE 3nd International Conference on Serious Games and Applications for Health (SeGAH)

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“…Peirce et al [7] propose a system for adapting non-playing characters (NPCs) behavior to enable a personalized learning experience. Westra et al [12] use agent organizations to adapt the behavior of game elements, during game-play, to the skill level of players. Results in adapting game content can be found on Togelius et al [10] work.…”

Section: Related Workmentioning

confidence: 99%

Scenario adaptivity in serious games

Lopes

2010

Proceedings of the Fifth International Conference on the Foundations of Digital Games

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Most current serious games suffer from system inflexibility, which is responsible for stereotyped training scenarios and predictable game-play. My goal is to support adaptivity in serious games by allowing virtual scenarios to dynamically adjust to what and how players should learn. Adaptivity should give players more effective gaming and learning experiences, if it is guided by their Instructors' knowledge about both players and learning goals. I expect to enable Instructors to create adaptive scenarios through specification of: what players have to learn, how they should learn it and, afterwards, what went missing. This work focuses on embedding this sort of knowledge into objects of the virtual scenario, through new semantic modeling methods. Meaningful information on what to learn will be solved into generating pre-game scenarios. How to learn knowledge will be used to create in-game adaptable objects and events. Assessments on what went missing will be solved to re-generate post-game (try again) scenarios.

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“…This allows the designer to make sure that the users are not exposed to tasks that are not suitable yet or would ruin the storyline. In previous work we have shown how to use agent organizations to specify the boundaries of the game [24], [25].…”

Section: B Agent Organizationsmentioning

confidence: 99%

“…In this example, this means that at least one agent prefer to check the left hallway but it puts a lot less burden on the designer to allow autonomy within the agents while making sure that certain critical criteria are always met. In previous work [25], [24] we proposed the use of multi-agent organizations to define a storyline (defining coordination restrictions on the agents) in such a way that there is room for adaptation while making sure that believability of the game is preserved. In this paper we show how the agents are implemented and show the coordinations of tasks and proof that it works in practice.…”

Section: Introductionmentioning

confidence: 99%

Keeping the trainee on track

Westra

Dignum

2010

Proceedings of the 2010 IEEE Conference on Computational Intelligence and Games

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Serious games and other training applications have the requirement that they should be suitable for trainees with different skill levels. Current approaches either use human experts or a completely centralized approach for this adaptation. Where agents are increasingly used in serious game implementations as a means to reduce complexity and increase believability, their use for adaptation can lead to situations in which the lack of coordination between the agents makes it practically impossible to follow the intended storyline of the game and select suitable difficulties for the trainee. In this paper we propose an architecture for game design that introduces a monitoring module to check the development of user skills and direct coordinated agent adaptation. Agents propose possible courses of action that are fitting their role and context, and the monitor module uses this information together with its evaluation of user level and storyline progress to determine the most suitable combination of proposals.

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Adaptive Serious Games Using Agent Organizations

Cited by 21 publications

References 6 publications

The effect of different difficulty adaptation strategies on enjoyment and performance in a serious game for memory training

The effect of different difficulty adaptation strategies on enjoyment and performance in a serious game for memory training

Scenario adaptivity in serious games

Keeping the trainee on track

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