A three‐step model for the gamification of training and automaticity acquisition

Abstract

Training design for automatic skills has a vast domain of application, such as education, physical and cognitive rehabilitation, as well as sports, arts and professional training. Gamification concept used in technology‐assisted training has the potential to increase motivation, engagement and adherence to the training programme. Currently, the general gamification models of learning, did not take into account the temporal specificity of the game elements for automaticity acquisition training. In order to address this problem, an extensive overview of the key training attributes that impact automaticity acquisition was carried out. Then, based on this review, the three steps of a proposed model were presented. The first step of this model, named Task Analytics, helps with task‐specific training decisions. The second step provides descriptive and prescriptive approaches for the three phases of automaticity acquisition (fast learning, slow learning and automatization). The descriptive part characterizes each phase using psychological and performance‐related qualities, while the prescriptive part recommends the appropriate training elements for each phase. Based on the prescriptive part, a game‐design model is proposed in the third step, which classifies the game mechanics and maps them onto each phase of automaticity acquisition. Finally, to validate this approach, a mobile game was designed based on the proposed gamification model, and it was compared to control design. The two approaches are tested with 49 participants. The results showed that the experimental group had a significantly better engagement and higher performance. Furthermore, the experimental group showed significantly better performance in a multitasking challenge designed to evaluate the automaticity. The main contribution of this article is the proposed game design model that takes into account the temporal specificity of game elements during the acquisition of automaticity.

A “Proof of Concept” Randomized Controlled Trial of a Video Game Requiring Emotional Regulation to Augment Anger Control Training

“…Not only does this mechanism allow for development of individualized skill, but it is also implicit, fast, and frequent during gameplay, facilitating automatic response learning. We propose that in combination, context-independence and repetition allow for far transfer effects ( 67 ). Future research would benefit the field by disentangling the relative contributions of context-independence and repetition.…”

Note-Taking: skill and habit of consecutive interpreters

“…Many authors were consulted as to define both concepts and determine their distinctive characteristics: Petrovski (1981), Clark (2000), González (2003), Osada (2004), Ormrod (2005), Clark et al (2007), Corona Martínez & Fonseca Hernández (2009), Ginoris et al (2009), Montes de Oca Recio & Machado Ramírez (2009), Lally et al (2010), Marina (2012), Shove (2009), Velázquez et al (2015), García Rodríguez (2017), Machín (2017), Sánchez (2017), Mulet González (2018), Douskos (2019), Jamshidifarsani et al (2021), Sánchez Cu (s.f. ).…”

“…Based on the automaticity acquisition model proposed by Jamshidifarsani et al (2021) skill and habit development can be linked to the transit from declarative knowledge or memory to procedural knowledge or memory and ultimately to automatization. This model describes the automaticity process in three phases: fast learning, slow learning and automatization.…”

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“…Sci. 2021, 11, 500 2 of 12 Different teaching methodologies integrate the technological devices in the educational environment such as the blended-learning [10][11][12] and gamification [13][14][15]. Blendedlearning, b-learning, combines face-to-face lessons in the classroom, required for any subject in university study plans, and virtual training teaching activities through learning platforms, while the gamification techniques try to create similar experiences to those experienced when playing games in order to motivate and engage users.…”