Exploring the links between household chores, learning, and mathematics performance in Zambia

Tan, Mei; Li, Nan; Pirozzolo, Joseph W.; Bolden, David; Chamvu, Florence; Jere-Folotiya, Jacqueline; Kaani, Bestern; Kalima, Kalima; N’gandu, Sophie Kasonde; Serpell, Robert; Hart, Lesley; Chart, Hilary; Jarvin, Linda; Kwiatkowski, Jonna; Newman, Tina; Stemler, Steven E.; Thuma, Philip E.; Yrigollen, Carolyn M.; Grigorenko, Elena L.

doi:10.1007/s12144-022-03077-z

Cited by 2 publications

(3 citation statements)

References 49 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…A similar sociocultural framework is found in Sub-Saharan Africa, with girls more likely than boys to perform household chores during the week and during school hours (Agesa & Agesa, 2019;Tian, 2019) and across LMICs more generally . Accordingly, chores have been found to affect girls' learning outcomes more than boys in Sub-Saharan Africa (Tan et al, 2022). The chores further related to greater prevalence of stress-related challenges among girl learners in comparison with boys (Beattie et al, 2019).…”

Section: Gender Differences In Access To Online Learningmentioning

confidence: 98%

“…Learners in LMIC homes were even less able to compensate for lost access to learning resources than those in deprived parts of HICs (Al-Salman & Haider, 2021;Khlaif et al, 2021), making the loss of teacher support and school resources more damaging in LMICs than in HICs. COVID-19 exacerbated, too, the gender disparities in access to online learning, with girls more likely to report home-related obstacles to online learning than boys during the Pandemic (Jafree, 2021;Mathrani et al, 2021), especially among learners who had been accustomed to in-school learning as opposed to out-of-school (or informal) learning (Reich et al, 2013;Tan et al, 2022).…”

Section: The Role Of Covid-19 In Access To Online Learningmentioning

confidence: 99%

“…However, also according to the interaction analyses, access to online learning was reduced during COVID-19 among younger learners. This was somewhat surprising, as one might have expected home responsibilities to prohibit older, rather than younger, learners from access to online learning, since learner age is strongly correlated with chances of home responsibilities, and for these to diminish access to learning (Tan et al, 2022), especially in LMICs (Keane et al, 2020). Instead, COVID-19's increase of access to online learning with learner age points to the importance of meta-cognition in online learning (Alemayehu & Chen, 2021) and the way it normally increases with age (e.g., Bryce & Whitebread, 2012), which is supported by the data-led finding that, on its own, learner age increases with access to online learning.…”

Section: The Role Of Covid-19 In Access To Online Learning (Hypothesi...mentioning

confidence: 99%

See 2 more Smart Citations

Access to online learning: Machine learning analysis from a social justice perspective

McIntyre

2022

Educ Inf Technol

View full text Add to dashboard Cite

Access to education is the first step to benefiting from it. Although cumulative online learning experience is linked academic learning gains, between-country inequalities mean that large populations are prevented from accumulating such experience. Low-and-middle-income countries are affected by disadvantages in infrastructure such as internet access and uncontextualised learning content, and parents who are less available and less well-resourced than in high-income countries. COVID-19 has exacerbated the global inequalities, with girls affected more than boys in these regions. Therefore, the present research mined online learning data to identify features that are important for access to online learning. Data mining of 54,842,787 initial (random subsample n = 5000) data points from one online learning platform was conducted by partnering theory with data in model development. Following examination of a theory-led machine learning model, a data-led approach was taken to reach a final model. The final model was used to derive Shapley values for feature importance. As expected, country differences, gender, and COVID-19 were important features in access to online learning. The data-led model development resulted in additional insights not examined in the initial, theory-led model: namely, the importance of Math ability, year of birth, session difficulty level, month of birth, and time taken to complete a session.

show abstract

Section: Gender Differences In Access To Online Learningmentioning

confidence: 98%