An exploratory investigation into the factors related to EdTech use among Kenyan girls

This paper contributes to the scarce literature on factors affecting EdTech use in households. These factors were considered through exploratory mixed-methods analyses of cross-sectional data on Kenyan girls and caregivers, captured during the COVID-19 pandemic. Quantitative analysis of the child dataset (n = 544) suggested the importance of both structural factors—such as technology hardware availability—and non-structural factors—including caregiver permission. Findings were supported by a thematic analysis of interview data from girls' caregivers (n = 58), which emphasised the role they play in girls' use of EdTech. Interviews also highlighted numerous caregiver concerns with EdTech, related to the relevance and rigour of educational content, the possibility of children accessing age-inappropriate material and child health (especially eyesight). Policy makers could alleviate these concerns by providing guidance on EdTech use and clearly signalling their approval of verified initiatives.

Practitioner notes

What is already known about this topic

• EdTech can benefit girls' education, yet there are various barriers to it being used.
• Existing research shows clearly that EdTech use can be impeded by structural factors (eg, hardware ownership).
• However, we find insufficient empirical evidence on the role of non-structural or behavioural factors.

What this paper adds

• This paper addresses this gap, using a mixed-methods approach to explore the influence of 33 different measures (including non-structural factors) that could affect the number of hours girls spend using EdTech at home.
• Findings from a quantitative sample of girls (n = 544) and a qualitative sample of girls' caregivers (n = 58) highlighted the importance of non-structural factors, especially caregiver permission.
• The variable most strongly associated with girls' EdTech usage in our selected quantitative model concerned whether this was sanctioned by their caregivers.
• Our qualitative data suggested why caregiver permission to use EdTech might be withheld: caregivers emphasised perceived concerns about the risks and rigour of EdTech.

Implications for practice and/or policy

• Our findings suggest the viability of policy interventions that provide EdTech guidance to caregivers.
• Caregivers uncertain about EdTech could be reassured of the appropriateness of verified initiatives, while those already convinced might be aided in their attempts to support EdTech learning.
• Such guidance could provide a low-cost means of further exploiting the benefits that household EdTech learning can provide.

     

Performance Technology Skills in Business: Implications for Preparation

What to teach Performance Technologists should be derived out of an analysis of desired performance. Despite a general agreement on the definition of Performance Technology, desired performance currently varies in business and consulting organizations. This paper reports the results of a survey of 23 organizations regarding current performance of Performance Technologists and current preparation of people for the role. It suggests a three-stage model for preparing Performance Technologists.