# Hope, Aspirations, and the Impact of LLMs on Female Programming Learners in Afghanistan

arXiv: https://arxiv.org/abs/2511.08630 · HTML: https://mlsanity.com/paper/2511.08630/

## Key facts

- Cited by 1 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 9 Nov 2025.

## Built on by (most cited first, 1 of 1)

- [Designing Safe and Accountable GenAI as a Learning Companion with Women Banned from Formal Education](https://mlsanity.com/paper/2604.07253/) (2026)

## Abstract (arXiv)

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.