Designing Appropriate Learning Technologies for School vs Home Settings in Tanzanian Rural Villages

Uchidiuno, Judith Odili; Yarzebinski, Evelyn; Madaio, Michael; Maheshwari, Nupur; Koedinger, Ken; Ogan, Amy

doi:10.1145/3209811.3209881

Cited by 23 publications

(10 citation statements)

References 19 publications

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“…HITW and OLPC reflected the culture of their designers. While HITW reflected a collective view of ownership and knowledge sharing that is common in India, OLPC ownership and its 1:1 model reflected an individualism perspective that tends to prevail in developed and Western countries [43]. The significant improvements achieved by both projects in their native context were challenged in other cultural settings such as the applications of HITW in UK, or Tanzania [39], [42], and OLPC implementations in RCC.…”

Section: Localizationmentioning

confidence: 99%

On Designing Blended Learning Environments for Resource-Challenged Communities

Lazem

2019

Int. J. Emerg. Technol. Learn.

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The growth of Information and Communication Technologies (ICT) adop-tion in emerging economies and more broadly Resource-Challenged Com-munities (RCC) motivates the exploration of Blended Learning (BL), a learning mode that mixes face-to-face and technology-mediated instruction. BL has the potential of broadening accessibility to quality learning anytime and anywhere. This article contributes a theoretical perspective for design-ing BL environments in RCC. It synthesizes findings from BL literature and lessons distilled from iconic educational technology projects in RCC to envision a pathway forward that consists of three design heuristics to ad-dress that the contextual challenges in RCC: localizing the problem, em-bracing the complex and nuanced use of technology, and balancing autono-my and scaffolding to support students.

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Section: Localizationmentioning

confidence: 99%

On Designing Blended Learning Environments for Resource-Challenged Communities

Lazem

2019

Int. J. Emerg. Technol. Learn.

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“…Though adding additional costs to the study budget, providing devices with mobile data may lead to more representative samples as well as better data quality. For example, several large-scale projects have successfully deployed mobile devices loaded with educational content in rural locations in the US and around the world, like small villages in Ethiopia (Breazeal et al, 2016;Uchidiuno et al, 2018). This tradeoff may be worth the cost, particularly for home-based intervention studies.…”

Section: Geographic Diversity Vs Digital Dividementioning

confidence: 99%

Implementing Remote Developmental Research: A Case Study of an RCT Language Intervention During COVID-19

Ozernov‐Palchik

Olson²,

Arechiga³

et al. 2021

Preprint

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Intervention studies with developmental samples are difficult to implement, in particular when targeting demographically diverse communities. Online studies have the potential to examine the efficacy of highly scalable interventions aimed at enhancing development, and to address some of the barriers faced by underrepresented communities for participating in developmental research. During the COVID-19 pandemic, we executed a fully remote randomized controlled trial (RCT) language intervention with third and fourth-grade students (N = 255; age range 8.19-10.72 years, mean = 9.41, SD = 0.52) from diverse backgrounds across the United States. Using this as a case study, we discuss both challenges and solutions to conducting an intensive online intervention through the various phases of the study, including recruitment, data collection, and fidelity of intervention implementation. We provide comprehensive suggestions and takeaways and conclude by summarizing some important tradeoffs for researchers interested in carrying out such studies.

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“…Several meta-analyses of educational interventions in Sub-Saharan West African contexts found that investments in instructional technology-specifically, adaptive instructional technologies-had the largest effect sizes for improving student learning outcomes, compared with funding nutritional and health interventions, reducing class sizes, or providing financial incentives for attendance [15,54]. Educational technologies have been deployed in many low-resource communities, using mobile devices in class [83], after school [35], across contexts [41,64,82], or using apps on e-readers [71] or tablets used in schools [62] or in both schools and home [81]. However, with few exceptions (e.g., [35,64]), these systems have been designed for smart devices [33,41,60,81,83], despite significantly fewer families in rural communities owning smartphones than low-cost feature phones [48,49].…”

Section: Educational Technology In Rural Householdsmentioning

confidence: 99%

“…Educational technologies have been deployed in many low-resource communities, using mobile devices in class [83], after school [35], across contexts [41,64,82], or using apps on e-readers [71] or tablets used in schools [62] or in both schools and home [81]. However, with few exceptions (e.g., [35,64]), these systems have been designed for smart devices [33,41,60,81,83], despite significantly fewer families in rural communities owning smartphones than low-cost feature phones [48,49]. Even in cases where families owned both smartphones and feature phones, as in Poon et al's work in Cameroon [64], they reported that parents preferred that children use feature phones.…”

Section: Educational Technology In Rural Householdsmentioning

confidence: 99%

“…Nevertheless, many family members were still able to provide explicit support for the feature phones, in ways that may not have been possible with less ubiquitous technologies (e.g., smartphones [41] or tablets [81], etc). Thus, designers of educational technology intended for low-resource contexts should consider which features-or interaction paradigms-of their systems may be widespread in their context and which may be less common (e.g., voice-based recorded messages).…”

Section: Designing For Digital Literacy Skill Acquisitionmentioning

confidence: 99%

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Collective Support and Independent Learning with a Voice-Based Literacy Technology in Rural Communities

Madaio

Yarzebinski

Kamath

et al. 2020

Proceedings of the 2020 CHI Conference on Human Factors in Computing Systems

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Access to literacy is critical to children's futures, but formal education may be insufficient for fostering early literacy, especially in low-resource contexts. Educational technologies used at home may be able to help, but it is unclear whether or how children (and families) will use such technologies at home in rural communities, particularly in low-literate families. In this paper, we investigate these questions with a voice-based literacy technology deployed with families in 8 rural communities in Côte d'Ivoire for 4 months. We use interviews and observations with 37 families to investigate motivations, methods, and barriers for rural families' engagement with a literacy technology accessible via feature phones. We contribute insights into how families view digital literacy as a learning goal, leverage networks of supporters, and over time, transition from explicit to implicit support for children's learning.

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Designing Appropriate Learning Technologies for School vs Home Settings in Tanzanian Rural Villages

Cited by 23 publications

References 19 publications

On Designing Blended Learning Environments for Resource-Challenged Communities

On Designing Blended Learning Environments for Resource-Challenged Communities

Implementing Remote Developmental Research: A Case Study of an RCT Language Intervention During COVID-19

Collective Support and Independent Learning with a Voice-Based Literacy Technology in Rural Communities

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