Adaptive Training Considerations for Use in Simulation-Based Systems

Landsberg, Carla R.; Buskirk, Wendi L. Van; Astwood, Randolph S.; Mercado, Alyssa D.; Aakre, Anthony J

doi:10.21236/ada535421

Cited by 15 publications

(3 citation statements)

References 44 publications

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“…A similar goal is desired in serious games, however, this incorporates the additional requirement of ensuring effective learning content delivery. DDA is explored in a serious games context to adapt the serious game to the needs of the learner and ultimately achieve better learning outcomes (Landsberg et al, 2010). Striking the right balance of challenge is critical to maximizing the chance of positive learning outcomes by both engaging the learner and helping achieve a Flow state (Hamari et al, 2016), or similar positive motivational or affective states.…”

Section: Introductionmentioning

confidence: 99%

How Hard Is It Really? Assessing Game-Task Difficulty Through Real-Time Measures of Performance and Cognitive Load

Seyderhelm

Blackmore

2023

Simulation & Gaming

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Background Serious and entertainment game designers strive to create engaging, immersive, and often, challenging games. This task involves modifying game mechanics or environments to create experiences with differing levels of challenge to meet player skill. The balance between different game mechanics or environments, and the differing levels of challenge they pose, is typically understood through iterative testing. Balance and challenge becomes increasingly important in serious games and simulation training as these games commonly need to be engaging and impart learning content. Overburdening players’ cognitive capacity with either too much gameplay challenge or learning content may reduce the educational effectiveness of the game. Aim. In this research, we develop a game-based driving simulation with different gameplay tasks to explore the impact of different types of challenges and game aesthetics on real-time cognitive load and task performance, which may inform serious game design. We also test the validity of a game-embedded real-time cognitive load measuring method. Method A total of 31 participants undertook the driving simulation experiment under three different aesthetic conditions using a within-subject experimental design. Cognitive load was measured using three different methods, and performance was measured via in-game metrics. Additionally, demographic and engagement surveys were also completed. Results Player performance and cognitive load respond differently to different types of challenge, and an appropriate level of game challenge can lower cognitive load. The embedded cognitive load measure was validated as an effective method for evaluating real-time cognitive load during gameplay. Conclusion The results demonstrate the validity of a dual measure approach for future adaptive serious games and simulation training environments combining performance and cognitive load. An easy to implement, and robust, in-game measure for cognitive load has been validated in real-world conditions. From these results, a system for dynamic difficulty adjustment is proposed tailored towards serious games and simulation.

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Section: Introductionmentioning

confidence: 99%

How Hard Is It Really? Assessing Game-Task Difficulty Through Real-Time Measures of Performance and Cognitive Load

Seyderhelm

Blackmore

2023

Simulation & Gaming

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“…Acquisition of psychomotor skills can be achieved by simulation training, a process through which actions are imitated and exercised in controlled environments with the intention of applying the skills to real-life scenarios [ 7 ]. However, simulator training time is still very expensive and in some cases is a rare commodity which must derive the most benefit possible with minimal use of special resources [ 8 , 9 , 10 ]. State-of-the-art innovative methods are applied to simulators in various fields in order to improve learning and training [ 11 , 12 , 13 ].…”

Section: Introductionmentioning

confidence: 99%

Stress-Adaptive Training: An Adaptive Psychomotor Training According to Stress Measured by Grip Force

Sahar

Wagner

Barel

et al. 2022

Sensors

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Current training methods show advances in simulation technologies; however, most of them fail to account for changes in the physical or mental state of the trainee. An innovative training method, adaptive to the trainee’s stress levels as measured by grip force, is described and inspected. It is compared with two standard training methods that ignore the trainee’s state, either leaving the task’s level of difficulty constant or increasing it over time. Fifty-two participants, divided into three test groups, performed a psychomotor training task. The performance level of the stress-adaptive group was higher than for both control groups, with a main effect of t = −2.12 (p = 0.039), while the training time was shorter than both control groups, with a main effect of t = 3.27 (p = 0.002). These results indicate that stress-adaptive training has the potential to improve training outcomes. Moreover, these results imply that grip force measurement has practical applications. Future studies may aid in the development of this training method and its outcomes.

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“…Adaptive training (AT) is training that adjusts relative to a learner's performance, aptitude, or learning preference (Landsberg, Van Buskirk, Astwood, Mercado, & Aakre, 2011). Several literature reviews have found that AT generally leads to positive learning outcomes (e.g., Durlach & Ray, 2011;Landsberg et al, 2011;McCarthy, 2008), but the AT literature lacks systematic empirical evidence to determine which AT techniques work best for which tasks and learners (Durlach & Ray, 2011;Vandewaetere, Desmet, & Clarebout, 2011). Therefore, the goal of the present experiment was to determine if similar AT techniques that were effective in one type of task would also be effective for a different task.…”

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confidence: 99%