用心理量表评估阿富汗女性编程学习者的教育希望，发现大模型或可拓宽求学路径。
Hope, Aspirations, and the Impact of LLMs on Female Programming Learners in Afghanistan
- 将希望量表改编为中文，用于测量阿富汗女性编程学习者的教育期望。
- 量表信度良好（α=0.78），有大模型访问者在实现路径感知上略高（p=0.056）。
- 适合研究冲突地区教育技术设计对学习者希望的影响，尤其关注女性群体。
在社会政治不稳定的背景下设计具有影响力的教育技术，需要深入了解学习者的教育期望。目前，衡量期望的可扩展指标有限。本研究将Snyder的希望量表进行改编、翻译，并在阿富汗系统性教育限制期间，对136名在线学习编程的女性进行了评估。改编后的量表表现出良好的可靠性（Cronbach's α = 0.78），参与者认为其内容清晰且相关。尽管总体期望得分在是否有大语言模型（LLMs）访问方面无显著差异，但有访问者在“途径”子量表上得分略高（p = .056），表明其更广泛地感知到实现教育目标的路径。这些发现支持该改编量表在社会政治不稳定环境中的适用性，也表明其可用于评估以期望为导向的教育技术设计效果。
原文摘要 · Abstract (English)
Designing impactful educational technologies in contexts of socio-political instability requires a nuanced understanding of educational aspirations. Currently, scalable metrics for measuring aspirations are limited. This study adapts, translates, and evaluates Snyder's Hope Scale as a metric for measuring aspirations among 136 women learning programming online during a period of systemic educational restrictions in Afghanistan. The adapted scale demonstrated good reliability (Cronbach's α = 0.78) and participants rated it as understandable and relevant. While overall aspiration-related scores did not differ significantly by access to Large Language Models (LLMs), those with access reported marginally higher scores on the Avenues subscale (p = .056), suggesting broader perceived pathways to achieving educational aspirations. These findings support the use of the adapted scale as a metric for aspirations in contexts of socio-political instability. More broadly, the adapted scale can be used to evaluate the impact of aspiration-driven design of educational technologies.
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