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The desire to improve and modernize education through educational technology is met with a daunting wall, as educational technologies oftentimes reflect and exacerbate social inequities. This work explores the growth in United States’ educational inequity stemming from the interdependent relationships between education, the digital divide, and social inequities. Diving into three case studies, this paper addresses the privatization consequences that result from the disproportionate funding barriers that schools in marginalized communities face in purchasing Smart Boards, as well as the dangerous impacts of SMART Technologies’ techno-solutionist marketing in worsening educational inequities. In comparison, massive open online courses (MOOCs), which are designed with the goal of improving education equity, appear to circumvent the funding barriers that Smart Boards provide, but fail to address the more tailored educational needs of marginalized communities – ultimately landing at the same fate as that of Smart Boards in worsening educational inequities. Lastly, this paper investigates reading software related to improving education for students with reading issues and blind students. Massively popular and effective in helping these students be more engaged and independent in reading, reading software is overall successful in creating a positive push toward educational equity. However, individual reading software can easily fall to the same failures of Smart Boards and MOOCs in contributing to educational inequity. Although improving educational equity requires a holistic approach, from a technology design standpoint, the following recommendations are made: (a) develop educational technology with the goals of improving education quality and equity, (b) circumvent as many barriers as possible to technology access through technology design, (c) work with marginalized communities to truly understand their needs and create a technology they will use, and (d) continue work toward equitable educational technology. 

This work explores whether audio feedback style and user ability influences user techniques, performance, and preference in the interpretation of node graph data among sighted individuals and those who are blind or visually impaired. This study utilized a posttest-only basic randomized design comparing two treatments, in which participants listened to short audio clips describing a sequence of transitions occurring in a node graph. The results found that participants tend to use certain techniques and have corresponding preferences based on their ability. A correlation was also found between equivalently high feedback design performance and lack of overall feedback design preference. These results imply that universal technologies should consider avoiding utilizing design constraints that allow for only one optimal usage technique, especially if that technique is dependent on a user’s ability.