Socioeconomic status and rural–urban inequalities in AI access and academic performance for engineering students from the TVET

Abstract

This study investigates socioeconomic and rural–urban disparities in access to artificial intelligence (AI) among engineering students enrolled following the TVET path in Bangladesh. We further analyse how socioeconomic status (SES) and geographic location affect access to AI tools and their impact on academic performance. Using primary survey data from diploma engineering students, the study applies a probit model to evaluate AI access and a multivariable linear regression model to assess the influence of AI usage on academic outcomes. Results demonstrate that students from higher-SES backgrounds and especially those who come from urban backgrounds achieve academic performance levels 20% higher, likely due to increased access to technology and a more supportive educational environment. Conversely, students from lower-income and rural backgrounds experience restricted access and lower academic achievement. These findings underscore the necessity for targeted policy interventions, including subsidized access and improved rural digital infrastructure, to foster inclusive educational outcomes.