Toward Learning at Scale in Developing Countries

McReynolds, Andrew A.; Naderzad, Sheba P.; Goswami, Mononito; Mostow, Jack

doi:10.1145/3386527.3405920

Cited by 9 publications

(2 citation statements)

References 4 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…The onebillion app was also one of the finalists included in the Global Learning XPRIZE, evaluated in a field trial in Tanzania, alongside four other apps(⇡XPRIZE, 2019). The five apps demonstrated significant gains for learners in terms of a range of measures of literacy and numeracy; in this instance, average gains were equal across both genders(⇡McReynolds et al, 2020).The use of SMS for education has received renewed interest recently as a result of the Covid-19 pandemic and school closures. A body of research literature exists prior to the pandemic, but only a few examples provide rigorous the differences which girls may face, depending on their background characteristics.…”

mentioning

confidence: 95%

“…⇡Sayibu (2022) presents a short paper about how the MGCubed project.Data is also playing an increasingly important role in EdTech through training of AI algorithms and their use in personalised learning apps. As noted in the previous section, there is evidence that personalised learning apps can provide equitable impacts on outcomes(⇡McReynolds et al, 2020) or even close gaps for girls(⇡Pitchford et al, 2019). There is a critical risk of perpetuating gender divides and stereotypes through AI -as demonstrated by the amplification of biases within training data, and the typically feminised design of AI assistants(⇡West et al, 2019).…”

mentioning

confidence: 99%

See 1 more Smart Citation

Gender equality and edtech: what are the barriers and enablers to enhance equity in and through edtech?

2023

View full text Add to dashboard Cite

This background paper reviews the literature-based evidence, a set of household surveys and a series of practice-based interventions in relation to educational technologies (EdTech) and gender in the context of Low-and Middle-Income Countries (LMICs), with focused research in Kenya, Sierra Leone and Tanzania.We illustrate that the main categories of factors to consider to design EdTech interventions to support girls' education are the access, use and content of EdTech. We introduce a framework that summarises the findings of this background paper and that can be used to consider these evidence-based factors throughout EdTech interventions.To design inclusive EdTech interventions to support girls' education these factors need to be explored through gender, political economy and intersectional lenses.The evidence for EdTech to support girls' education tends to point to barriers and enablers that need to be considered to design inclusive and egalitarian EdTech interventions (these are summarised in the framework introduced in Page 44). For example, in relation to the access of EdTech, we found that a barrier to inclusive and equitable quality education for all was that girls tended to be less likely than boys to own or be able to access mobile devices in LMICs. We also found that an enabler to improve EdTech access was to use EdTech for nudging and changing inequitable beliefs, although this needs to be carefully considered within context.There are barriers that need to be considered for all EdTech interventions aiming at supporting girls' education in LMICs. These are barriers related to reaching the most marginalised girls with EdTech, for example by ignoring political economy factors or the need for additional support for marginalised children (e.g financial, health or social support); neglecting to collect gender data throughout EdTech intervention; and disregarding the role of contextual inequalities, intersectionality and gender norms in supporting egalitarian learning through EdTech. While these factors are challenges for all educational interventions to some extent, there is a particular risk that without careful consideration, EdTech interventions could exacerbate existing 'digital divides' and increase inequity.

show abstract

mentioning

confidence: 95%

mentioning

confidence: 99%