Specification of Users' Cognitive Functions and Emotions to Promote Their Training Through Serious Games

Key insights

6 takeaways

01
The authors argue that the mining accident analysed in the case study identified a low perception of risk as a contributing factor, so perception was selected as the cognitive function to train.See it on page 13
02
The validation used four participants, a sample the authors describe as small because mining workers have limited time and travel to mine sites is difficult.See it on page 17
03
The authors state that in the validation, the cognitive test was suggested but not applied.See it on page 23
04
Under the model's level scale, a perception level is classed as low when the rank is less than or equal to 2, medium when it is above 2 and below 4, and high when it is 4 to 5.See it on page 9
05
The authors present the validation as successful, stating that the game allowed the desired cognitive functions to develop and that the emotions of interest appeared.See it on page 27
06
The authors state that the emotional states in the validation were detected by observation and not by expert judgement, and that the survey was applied after each session.See it on page 23

Summary

The authors present a cognitive-affective model for designing serious games that train cognitive functions and regulate emotions, with a case study in the mining sector. The model has a cognitive dimension, built on Diamond's executive functions framework and Ben-Sadoun and Alvarez's game-mechanics matching, and an affective dimension, drawn from affective computing and Russell's valence-arousal space. Basic and complex cognitive functions and six basic emotions are represented. The case study models a gas explosion in a virtual subway coal mine, built in Unreal Engine 4.27.2 for Oculus Meta Quest 2 and tested with four mine workers: two older adults and two young people, each with more than one year of mining experience. The authors describe the number of participants in the validation as small because miners have difficulty finding time to collaborate and travel to the mines is challenging. Validation combined the virtual serious game with competency questions answered in OCL. The authors state that the model's components were all collected in the game, and that all competency question checks returned true across the example models.

Specification of Users' Cognitive Functions and Emotions to Promote Their Training Through Serious Games

Specification of Users' Cognitive Functions and Emotions to Promote Their Training Through Serious Games

Key insights

Summary

Next steps

Games and companies in this document

Connections

More on Serious Games

Virtual Reality Check: Design Considerations for Reflection in VR Educational Escape Rooms

Effects of Different Game Mechanics on 2D Location Learning in a Serious Game

Fostering Computational Thinking in Children with ASD: A Tailored Digital Game Design Proposal

Wonder Town: Integrating Generative AI into a Bloom-Aligned Physics Learning Game

The Gift of the Tenth Month: Early Design of a Partner-Inclusive Prenatal Education Serious Game

Beyond Fun: Gamified Multidomain Reading Assessment for Children

Learning Mathematical Derivatives Through a Virtual Escape Room Application

Lectura Maestra: Gamified Reading Strategy in Undergraduate Business Education

Misión Korex: A Gamified System to Promote Physical Activity in Childhood Contexts

Designing an AI Roleplay System for Contextualized Career Guidance in Mexico

Extending The Project Win Game: Teaching Real Options and Moral AI Project Decision-making

Cuenta Cuentos: A Co-designed Board Game for Preserving the Language of the Comcaac