Mobile Learning During School Disruptions in Sub-Saharan Africa

Abstract

School closures due to teacher strikes or political unrest in low-resource contexts can adversely affect children’s educational outcomes and career opportunities. Phone-based educational technologies could help bridge these gaps in formal schooling, but it is unclear whether or how children and their families will use such systems during periods of disruption. We investigate two mobile learning technologies deployed in sub-Saharan Africa: a text-message-based application with lessons and quizzes adhering to the national curriculum in Kenya (N = 1.3 million), and a voice-based platform for supporting early literacy in Côte d’Ivoire (N = 236). We examine the usage and beliefs surrounding unexpected school closures in each context via system log data and interviews with families about their motivations and methods for learning during the disruption. We find that mobile learning is used as a supplement for formal and informal schooling during disruptions with equivalent or higher intensity, as parents feel responsible to ensure continuity in schooling.

A Scoping Study of Evaluation Practices for Responsible AI Tools: Steps Towards Effectiveness Evaluations

“…In our view, however, these challenges should not forestall consideration of how evaluation methods from other fields can be adapted for use in RAI tool evaluations. Indeed, research in educational contexts like schools is also subject to changing policies, state standards, students moving from an intervention to control group when enrolling in a new class or school, as well as exogenous shocks like teacher strikes, political violence, and school closures, among others [117]. Conversely, as AI technologies and development paradigms are increasingly incorporated into medical or education interventions, these domains are also starting to consider how to apply their familiar evaluation approaches to AI technologies [e.g., in healthcare, 134,170][e.g., in education, 36], and how to translate insights from RAI to their evaluation practices [e.g.…”

Learners and caregivers barriers and attitudes to SMS-based mobile learning in Kenya

“…The present study aligns primarily with the third category, as M-Shule is an SMS-based platform to deliver educational content to learners, but also with the second category to an extent, as caregiver support is also required for young learners to access and make use of mobile devices. Kizilcec et al (2021) present a study based on an analysis of platform usage data from a different SMS-based system, Shupavu291. Developed by Eneza Education, Shupavu291 delivers curriculum-linked educational materials and quizzes to learners, and allows questions to be submitted to teachers, via SMS (Kizilcec & Goldfarb, 2019).…”

“…The study sought insights into educational disruption and mobile learning through the analysis of usage data from a previous period of school closures in Kenya in 2017, relating to political unrest. It showed that use of the platform increased during periods of disruption, and there was slightly different user demand; for example, learners often make greater use of quizzes in the run-up to exams, but during disruption, there was more emphasis on accessing content (Kizilcec et al, 2021).…”

Education Data Science: Past, Present, Future

“…A second article, by René Kizilcec, Maximillian Chen, Kaja Jasińka, Michael Madalo, and Amy Ogan (Kizikcec et al, 2021; “Mobile Learning During School Disruptions in Sub-Saharan Africa”), also uses technology to acquire new data and new treatments. This work investigates how mobile learning technologies helped offset social disruptions to schooling for over 1.3 million students in sub-Saharan Africa.…”