Abstract
In the digital inequality literature, the popular notion of a “digital divide” is frequently used to discuss digital inequality; however, this framework is overly simplistic and cannot adequately capture the complex nature of digital inequality. Some scholars have adopted a framework of digital capital to attempt a multidimensional approach to this social problem, but the literature lacks consistent empirical measurements. Using U.S. data from the Programme for International Student Assessment (PISA) 2018 Survey, I seek to propose, and validate, internally consistent principal components of digital capital among 15-year-old high school students in the US. I conduct a Principal Component Analysis (PCA), resulting in five principal components: Academic Digital Usage, Perceived Digital Autonomy, Perceived Digital Competence, Casual Digital Browsing, and Knowledge-Based Digital Leisure. I then examine Chronbach’s alpha coefficient for each component to assess reliability. Next, I conduct an Ordinary Least Squares (OLS) regression analysis to assess how the resulting factors might predict mathematics proficiency scores, as measured by PISA, after controlling for several key background variables. In the regression model, I also include three variables related to material digital access, which were not found to be a reliable component of digital capital. The regression results show statistically significant effects on mathematics proficiency scores for each proposed component of digital capital, except for perceived digital competence. Additionally, the results indicate that home computer access has a significant, positive effect on mathematics proficiency scores. This exploratory study offers a new direction toward empirical measurement for future research on digital capital and inequality.
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