Immersive virtual reality learning environments (VRLEs) have great potential but they do not guarantee effective or in-depth learning. Activating learners by including prompts, has been reported to increase learning in VR. Based on their promising effects in conventional settings, elaboration prompts should increase learning outcomes by activating learners to explain the learning content in their own words or to contrast it to prior knowledge. In our study, we investigated the effect of an elaboration prompt before entering the VRLE on learning robotics. Our between-subject study (prompt vs. no prompt) included N = 64 participants. We applied a multi-method approach (functional and structural) to measure mental models. We used a differentiated learning outcome measurement (knowledge, comprehension, and application) as a functional measurement. By using the structural assessment of knowledge technique, we deduce the structural accuracy of the developed mental model. We found an increase by the elaboration prompt on knowledge level but not on comprehension or application level. The interplay of pre-accuracy and prompt had a significant impact on structural accuracy after learning. Application level and structural accuracy after learning were positively correlated. Our multi-method approach delivered insights on different aspects of the developed mental model when prompting before entering the VRLE. For future research, further approaches to explore in-depth learning in VRLEs are recommended.

沉浸式虚拟现实学习环境（VRLE）具有巨大潜力，但不能保证有效或深入的学习。据报道，通过包含提示来激活学习者可以增加VR的学习。基于它们在常规环境中的有希望的效果，精心制作的提示应通过激活学习者以自己的语言解释学习内容或将其与先验知识进行对比的方式来提高学习成果。在我们的研究中，我们研究了进入VRLE之前精心制作提示对学习机器人的影响。我们的受试者间研究（提示与无提示）包括N =64名参与者。我们采用了一种多方法方法（功能方法和结构方法）来衡量心理模型。我们使用差异化学习成果度量（知识，理解和应用）作为功能度量。通过使用知识技术的结构评估，我们推断出所开发的心理模型的结构准确性。我们发现，在知识水平上的详细说明提示有所增加，但在理解或应用程序水平上却没有增加。预精度和提示之间的相互作用对学习后的结构准确性有重大影响。学习后的应用水平和结构准确性呈正相关。在进入VRLE之前进行提示时，我们的多方法方法提供了关于已开发心智模型不同方面的见解。为了将来的研究，