Serious Games in Engineering: The Current State, Trends, and Future
Notice bibliographique
Résumé
Since its inception in the late 20 th Century, computer graphics have improved exponentially and is improving even further in new avenues.While arcade games were early adopters of computer graphics, it was really in the 1990s, with the advent of the personal computer, that video games really started to gain traction.The video gaming industry started humbly with an online community of recreational developers.However, the internet bubble saw companies investing heavily in this new medium for games.Today, the video gaming industry is worth closer to $150 billion USD of yearly revenue, with well established practices, trends and new genres [1].Furthermore, video games have delivered a wide variety of experiences, from interactive story telling, open world exploration, social games, puzzle games, virtual reality games, mobile games and so on.The present paper seeks to provide a direct comparison of trends in the video gaming industry, and how it could be translated to Serious Games in Engineering Education.To this aim, 28 relevant studies which have reported games for teaching engineering courses within the past decade were investigated.These studies were obtained after extensive Scopus search queries and filtered manually according to 8 research questions.Key questions we seek to investigate are what genre of games are being employed, disciplines most often targeted for gamification, assessment tools used to gather data on student learning within gamified settings, learning outcomes and attitudes towards game modules for students' engineering courses and as well as data analysis/collection methods.The results indicated that computer engineering and mechanical engineering disciplines were most used in serious games in engineering education.Unique concepts/topics were addressed is all the 28 articles reviewed.Questionnaire and pre-and post-tests were the most preferred data collected tools.20 out of 28 articles used convenience sampling as the sampling method and most articles used sample sizes less than 100.Most articles used descriptive analyses methods in analyzing the data.Simulation was reported as the most used game genres and web-based application game platforms was commonly used in serious games in engineering education.
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Comment cette classification a été obtenuedéplier
Prédiction distillée sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.
Scores Codex et Gemma par catégorie
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,000 | 0,000 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,000 | 0,001 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,001 | 0,001 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,000 | 0,000 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule tête enseignante, pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».