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

TL;DR

This study adapts and evaluates a hope scale to measure educational aspirations among Afghan women learning programming during socio-political instability, finding it reliable and relevant for assessing aspiration-driven educational interventions.

Contribution

It introduces an adapted hope scale for measuring aspirations in unstable socio-political contexts and evaluates its reliability and relevance among Afghan female programming learners.

Findings

The adapted scale showed good reliability (Cronbach's alpha = 0.78).

Participants found the scale understandable and relevant.

Access to LLMs was associated with marginally higher scores on the Avenues subscale.

Abstract

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 {\alpha} = 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.