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A three-step model for the gamification of training and automaticity acquisition
Journal of Computer Assisted Learning ( IF 5.1 ) Pub Date : 2021-02-21 , DOI: 10.1111/jcal.12539
Hossein Jamshidifarsani 1 , Paul Tamayo‐Serrano 1 , Samir Garbaya 2 , Theodore Lim 3
Affiliation  

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.

中文翻译:

训练和自动获取游戏化的三步模型

自动技能的训练设计具有广泛的应用领域,例如教育、身体和认知康复,以及运动、艺术和专业训练。技术辅助培训中使用的游戏化概念有可能增加对培训计划的积极性、参与度和依从性。目前,一般的游戏化学习模型,没有考虑到游戏元素的时间特异性进行自动习得训练。为了解决这个问题,对影响自动获取的关键训练属性进行了广泛的概述。然后,在此审查的基础上,提出了所提出模型的三个步骤。该模型的第一步,名为任务分析,有助于制定特定于任务的培训决策。第二步为自动化习得的三个阶段(快速学习、慢速学习和自动化)提供描述性和规定性方法。描述部分使用心理和表现相关的品质来描述每个阶段,而说明部分为每个阶段推荐适当的培训元素。在规定部分的基础上,在第三步中提出了一个游戏设计模型,该模型对游戏机制进行分类并将它们映射到自动获取的每个阶段。最后,为了验证这种方法,基于所提出的游戏化模型设计了一款手机游戏,并将其与控制设计进行了比较。这两种方法在 49 名参与者中进行了测试。结果表明,实验组有明显更好的参与度和更高的表现。此外,实验组在旨在评估自动性的多任务挑战中表现出明显更好的表现。本文的主要贡献是所提出的游戏设计模型,该模型在自动性获取过程中考虑了游戏元素的时间特异性。
更新日期:2021-02-21
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