Build_PC: Mobile Augmented Reality for Supporting PC Hardware Learning with Low Mental Workload

The use of emerging technologies such as Mobile Augmented Reality (MAR) in education has gained relevance, especially in technical areas such as PC hardware learning. However, a persistent problem is the cognitive load that these applications may impose on students, which could affect learning effectiveness and acceptance. This issue is crucial, as a high mental workload can lead to disengagement and lower knowledge retention. Previous studies have explored technological solutions for education, but in many cases failed to optimize cognitive load or generate a satisfactory learning environment. This study proposes a MAR application called Build_PC, designed for hands-on teaching of PC hardware. The NASA-TLX tool was used to evaluate the mental workload in 60 students, analyzing dimensions such as mental, physical, temporal, performance, effort and frustration level. The results show a low mental workload among students, suggesting that Build_PC achieves a balance between task complexity and interface usability. These findings have significant implications: the use of Build_PC in education enables effective, autonomous learning in a technologically advanced environment without imposing excessive mental workload. This supports MAR's potential as an effective and sustainable learning tool, particularly in contexts where access to physical laboratories is limited.

移动增强现实（Mobile Augmented Reality, MAR）等新兴技术在教育领域的应用价值日益凸显，尤其在PC硬件学习等技术类教学场景中更是如此。然而这类应用可能会给学习者带来认知负荷，这一长期存在的问题会对学习效果与接受度造成负面影响。该问题至关重要，因为过高的心理负荷会导致学习者注意力分散，进而降低知识留存水平。过往相关研究虽已探索了面向教育的技术解决方案，但多数情况下未能有效优化认知负荷，也无法构建令人满意的学习环境。本研究提出一款名为Build_PC的MAR应用，专为PC硬件实操教学场景设计。研究采用NASA-TLX量表对60名学生的心理负荷进行评估，分析维度涵盖心理需求、身体负荷、时间压力、绩效表现、努力程度与挫败感水平。评估结果显示学生的整体心理负荷处于较低水平，表明Build_PC实现了任务复杂度与界面易用性之间的平衡。本研究结论具有显著的实践意义：在教育场景中应用Build_PC，可让学习者在先进技术环境中开展高效自主学习，且不会带来过重的心理负荷。这一结果进一步印证了MAR作为高效且可持续学习工具的潜力，尤其在实体实验室资源匮乏的场景中优势更为突出。