the device, 245 students were able to name two, and 208 students were able to name three books (not shown).<sup>14</sup> Most students found the eReader easy and convenient to use. About 63 percent of respondents had to charge their eReaders once or twice a week with 84 percent claiming that charging had little or no impact on their use. More than 75 percent had no problems with eReader features (e.g. marking text, weight of the device, difficulty of use). Around 89 percent claimed difficulty in reading had little or no impact on their use. Safety concerns about device use in public or breakage concerns were limited, however, nearly half of the students used their eReader only at home. Around 84 percent of the sample reported being comfortable with the device; 90 percent claim that their overall experience with the device was positive. Despite this, one-fourth of the respondents claimed that their use of the device was limited because they have a preference for textbooks (27 percent).

Information on eReader usage was also derived from direct extraction of usage statistics from the eReaders themselves. The eReaders used in the experiment (Kindle, version 3.2) allowed for limited extraction of usage data – such as books read/opened, highlights, and notes. Two strategies were followed. First, data were collected by transcribing information from the ‘menu’ of actual eReaders recovered from students at endline. Second, functioning devices were connected to the internet to extract usage data. The extent to which these data can be used for rigorous analysis, however, is constrained by the high rates of device breakage and unavailability. Device status at endline is reported in Table 3.

Around 88 percent of devices showed some sign of physical damage (51 percent of which was damage to the screen). Analyzing usage data from 86 functioning devices stored on the cloud, we find that average number of books read - in the 6-8 months duration of treatment - was 4.6. Only 6 percent of devices with extracted data showed no book read. There were no systematic differences across treatment groups in the average number of books read. Just over 85 percent of devices with extracted data had at least one highlight; 56 percent had at least one note.

# **5. Impacts of eReader treatment**

The results of estimating specifications (1) and (2) (described above) are presented in **Tables 5-9** . The first pair of columns in each table correspond to specification (1) with and without controls. Controls are drawn from a set of baseline student characteristics<sup>15</sup> as well as baseline student performance in reading and average school performance at baseline (de Ree et al. 2017). The coefficients of interest capture contrasts between adjacent treatments (T1 vs control, T2 vs T1, T3 vs T2). We then present results of estimating specification (2) where the overlapping treatment indicators are interacted with three student-level attributes: student having above median reading at baseline, student owned a paper textbook at baseline, student had aspirations for high level of education at baseline. All specifications cluster standard errors at the school level.

> 14 Oliver Twist was the most frequently cited book, followed by students’ English textbook, Five Little Friends, and students’ math textbook.

> 15 Age, educational attainment of mother and father, household wealth, access to electricity, mobile phones, and proxies for frequency of paper-textbook use.

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