Using Binary Logistic Regression to Predict Long-Term Effects of Early-Age Home Literacy Environment on Reading Motivation

Taoufik Boulhrir^1,

¹Department of English Studies, Discourse, Creativity, and Society, USMBA, Saiss-Fes, Morocco

Cite this paper:
Taoufik Boulhrir. Using Binary Logistic Regression to Predict Long-Term Effects of Early-Age Home Literacy Environment on Reading Motivation. American Journal of Educational Research. 2017; 5(8):858-862. doi: 10.12691/education-5-8-4

Abstract

Home literacy environment has ubiquitously been investigated against its impact on academic achievement and reading motivation. This study is an investigation of the long-lasting effects of home literacy environment on Moroccan students’ reading motivation. 178 students aged 14-24 were surveyed online to elicit their early-age home literacy experiences and to test them against the odds of their reading motivation. Using data gathered on such environments and experiences, a binary logistic regression inferential test was conducted to test if students who grow up in literacy-rich home environments are more likely to be motivated readers, and vice versa. The purpose of using this test in particular is to find out whether reading motivation can be predicted based on home literacy environment data. The accuracy of prediction of this test can be indicative of its potential to detect and diagnose reading motivation at various academic levels. As far as findings of this study are concerned the BLR test affirms that the odds of reading motivation being tied to HLE factors are significantly high. Using BLR to predict, diagnose, and intervene may help educators, parents, and curricula developers in considering HLE and early-age literacy experiences in policy making and curricula designs.

Keywords:
reading motivation home literacy environment binary logistic regression

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