The COVID-19 pandemic has significantly exacerbated existing educational disparities in Georgia's K-12 system, particularly in terms of racial and ethnic achievement gaps. Utilizing machine learning methods, the study conducts a comprehensive analysis of student achievement rates across different demographics, regions, and subjects. The findings highlight a significant decline in proficiency in English and Math during the pandemic, with a noticeable contraction in score distribution and a greater impact on economically disadvantaged and Black students. Socio-economic status, as represented by the Directly Certified Percentage -- the percentage of students eligible for free lunch, emerges as the most crucial factor, with additional insights drawn from faculty resources such as teacher salaries and expenditure on instruction. The study also identifies disparities in achievement rates between urban and rural settings, as well as variations across counties, underscoring the influence of geographical and socio-economic factors. The data suggests that targeted interventions and resource allocation, particularly in schools with higher percentages of economically disadvantaged students, are essential for mitigating educational disparities.

Mr. Khan's vision of tutoring bots tapped into a decades-old Silicon Valley dream: automated teaching platforms that instantly customize lessons for each student. Proponents argue that developing such systems would help close achievement gaps in schools by delivering relevant, individualized instruction to children faster and more efficiently than human teachers ever could. In pursuit of such ideals, tech companies and philanthropists over the years have urged schools to purchase a laptop for each child, championed video tutorial platforms and financed learning apps that customize students' lessons. Some online math and literacy interventions have reported positive effects. But many education technology efforts have not proved to significantly close academic achievement gaps or improve student results like high school graduation rates.

Under enormous pressure to generate growth, today's C-suite is adopting technology that spawns new capabilities and applications. But many still struggle to scale innovation company-wide. It's creating what we call the innovation achievement gap--the difference between technology innovation investment and realized value. Value is difficult to capture in part because the conventional IT "stack"--spanning software applications, hardware, telecommunications, facilities and data centers--wasn't built for today's world of analytics, sensors, mobile computing, artificial intelligence applications, the Internet of Things (IoT), and billions of devices. Nor was it designed to adapt to the world of tomorrow, whatever that might be. But it's not the case that digital native companies are closing their value achievement gaps, while legacy companies aren't.

The achievement gap between students who come from different socio-economic backgrounds is a well-known and persistent problem in education. Disparities in achievements between high and low socio-economic groups are evident in children as young as age 3 years and seem to be a problem the world over. Despite pupils' overall attainment scores rising over the last decade or so, the gap between students from different socio-economic groups remains intractably present and widespread. Family finances play a big part amongst the various reasons for this disparity. Pupils from low socio-economic backgrounds (SEBs) are often only able to attend a few, if any of the extra-curricular activities enjoyed by their more affluent peers. Access to good schools for pupils from SEBs is often reduced as is their access to the educational and occupational aspirations which can impact children's academic achievement.

The folks who brought us the marshmallow test have some unlikely news: children today have more self-control than ever. That conclusion is based on more than 50 years of results from the iconic test, which allows a preschooler to eat one treat immediately or two if she can wait 10 minutes. The effort at delayed gratification is vastly funny but the results were found to have serious implications for children's future success. Led by psychologist Walter Mischel, who created the experiment -- one of the most famous in developmental psychology -- a research team found that children tested between 2002-2012 held out for two minutes longer on average than the original test-takers in the 1960s, and one minute longer than participants in the 1980s. A 4-year-old in the earliest group waited as long as a child between 2 ½ and 3 in the most recent tests, and 4-year-old test-takers in the 1980s waited as long as a child who was 3 ½ in the 2000s.