Using AI for feedback, not ready

Billy Odell Tucker-Robinson Founder & Host — Banking With Billy Network • Intelligence Network • Data Science • AI Research • World News
Published: 2026-10-07T20:24:27.270Z • Permanent link

According to a recent study by researchers at Stanford University, the widespread adoption of artificial intelligence (AI) tools in educational settings has led to a concerning trend: students who rely heavily on AI for feedback are actually performing worse than those who don't use AI at all. This finding has significant implications for educators, policymakers, and tech companies that are developing AI-powered learning tools. Dr. Sara Goldin-Meadow, a leading expert on AI in education, noted that "the key issue here is not the technology itself, but how students choose to use it." Specifically, the study found that students who used AI instrumentally, relying on it to complete assignments or provide instant feedback, saw their grades decline by as much as 10%. In contrast, students who used AI more strategically, seeking feedback to improve their understanding of course material, saw their grades remain stable or even improve.

Meanwhile, the education technology industry has been racing to develop AI-powered tools that can provide personalized feedback to students. Companies like DreamBox and Khan Academy have already launched products that use AI to analyze student performance and provide tailored feedback. However, it appears that these tools may not be addressing the root problem. According to a spokesperson for DreamBox, "we're committed to providing high-quality feedback that helps students learn and grow, but we also recognize that AI is not a magic bullet." Instead, educators and policymakers are urging caution, emphasizing the need for a more nuanced approach to AI in education.

Despite the challenges, many experts believe that AI has the potential to revolutionize the way we learn. According to a report by the World Economic Forum, AI-powered learning tools could increase student outcomes by as much as 20% by 2025. However, this will require a fundamental shift in how we think about AI in education. Rather than relying on AI as a crutch, educators and policymakers must prioritize the development of AI-powered tools that are designed to support, rather than replace, human teachers and learning environments.

The implications of this study are far-reaching, with significant consequences for the education technology industry and the broader Data Sources domain. Companies like McGraw-Hill and Pearson, which dominate the market for educational software and assessments, may need to reevaluate their strategies in light of this finding. Research communities, too, will need to take a closer look at the role of AI in education, acknowledging both its potential benefits and limitations. In the short term, policymakers may need to consider new regulations or guidelines to ensure that AI-powered learning tools are developed and deployed responsibly.

Meanwhile, the broader implications of this study extend far beyond the education sector. As AI becomes increasingly ubiquitous in our lives, we need to ask ourselves whether we are using these technologies in a way that truly supports our goals and values. According to a report by the Brookings Institution, the future of work is likely to be shaped by AI, with many jobs becoming increasingly automated over the next decade. This raises important questions about the social safety net and the need for education and retraining programs.

This finding is not an isolated incident, but rather part of a larger pattern. The rise of AI in education is closely tied to broader trends in the tech industry, including the growing use of machine learning and natural language processing. According to a report by the MIT Initiative on the Digital Economy, the global AI market is projected to reach $190 billion by 2025. Meanwhile, the education technology industry has been increasingly dominated by large tech companies, including Google, Amazon, and Facebook.