背景:虽然基于游戏的学习已经证明了一些学习者的积极成果,其功效仍然可变。自适应支架可以通过优化认知负荷来改善训练期间的表现和自我调节。根据认知负荷理论,这项研究调查了基于交互跟踪数据的自适应支架是否会影响学习表现,自我调节,认知负荷,测试性能,参与医疗急救游戏。
方法:来自三所荷兰大学的62名医学生玩了六个游戏场景。他们在随机的双盲匹配对轭控制设计中接受了自适应或非自适应支架。在游戏过程中,我们测量了学习表现(准确性,速度,系统性),自我调节(自我监测,寻求帮助),和认知负荷。以2周和6-12周的间隔在现场情景评估中评估测试性能。在完成所有游戏场景后测量参与度。
结果:令人惊讶的是,结果揭示了使用适应性支架和非适应性支架的组之间没有明显的差异.这一发现归因于64.9%的场景中,非自适应脚手架和参与者的需求之间的意外对齐,导致巧合定制的脚手架。探索性分析表明,与非定制脚手架相比,量身定制的脚手架提高速度,自我调节减少,降低认知负荷。没有发现测试性能或参与度的差异。
结论:我们的结果表明,自适应支架可以通过优化认知负荷来增强学习。这些发现强调了GBL环境中适应性脚手架的潜力,培养更有针对性和更有效的学习体验。为了有效地利用这种潜力,研究人员,教育工作者,建议开发人员从设计自适应GBL或基于计算机的仿真体验开始合作。这种协作方法有助于建立可靠的性能指标,并使设计适合,最好是实时的,脚手架干预。未来的研究应该证实自适应支架对自我调节和学习的影响,在研究设计中注意避免意外定制脚手架。
背景:本研究在数据收集之前预先注册了开放科学中心。注册表可以在https://osf.io/7ztws/找到。
BACKGROUND: While game-based learning has demonstrated positive outcomes for some learners, its efficacy remains variable. Adaptive scaffolding may improve performance and self-regulation during training by optimizing cognitive load. Informed by cognitive load theory, this study investigates whether adaptive scaffolding based on interaction trace data influences learning performance, self-regulation, cognitive load, test performance, and engagement in a medical emergency game.
METHODS: Sixty-two medical students from three Dutch universities played six game scenarios. They received either adaptive or nonadaptive scaffolding in a randomized double-blinded matched pairs yoked control design. During gameplay, we measured learning performance (accuracy, speed, systematicity), self-regulation (self-monitoring, help-seeking), and cognitive load. Test performance was assessed in a live scenario assessment at 2- and 6-12-week intervals. Engagement was measured after completing all game scenarios.
RESULTS: Surprisingly, the results unveiled no discernible differences between the groups experiencing adaptive and nonadaptive scaffolding. This finding is attributed to the unexpected alignment between the nonadaptive scaffolding and the needs of the participants in 64.9% of the scenarios, resulting in coincidentally tailored scaffolding. Exploratory analyses suggest that, compared to nontailored scaffolding, tailored scaffolding improved speed, reduced self-regulation, and lowered cognitive load. No differences in test performance or engagement were found.
CONCLUSIONS: Our results suggest adaptive scaffolding may enhance learning by optimizing cognitive load. These findings underscore the potential of adaptive scaffolding within GBL environments, cultivating a more tailored and effective learning experience. To leverage this potential effectively, researchers, educators, and developers are recommended to collaborate from the outset of designing adaptive GBL or computer-based simulation experiences. This collaborative approach facilitates the establishment of reliable performance indicators and enables the design of suitable, preferably real-time, scaffolding interventions. Future research should confirm the effects of adaptive scaffolding on self-regulation and learning, taking care to avoid unintended tailored scaffolding in the research design.
BACKGROUND: This study was preregistered with the Center for Open Science prior to data collection. The registry may be found at https://osf.io/7ztws/ .