{"id":3295,"date":"2024-10-20T12:20:16","date_gmt":"2024-10-20T16:20:16","guid":{"rendered":"https:\/\/blog.richmond.edu\/schooltechnology\/?p=3295"},"modified":"2024-10-20T12:20:16","modified_gmt":"2024-10-20T16:20:16","slug":"the-traveling-teacher-blog-thoughts-on-my-problem-of-practice","status":"publish","type":"post","link":"https:\/\/blog.richmond.edu\/schooltechnology\/2024\/10\/20\/the-traveling-teacher-blog-thoughts-on-my-problem-of-practice\/","title":{"rendered":"The Traveling Teacher Blog! Thoughts on my problem of practice"},"content":{"rendered":"

Using AI in schools presents several challenges, including concerns about data privacy and security, the risk of exacerbating existing inequalities, and the potential for bias in AI algorithms that can perpetuate stereotypes or disadvantage, certain groups of students, to name but a few concerns. Some educators and stakeholders resist adopting AI technologies due to fear of change or skepticism about their effectiveness. Therefore, educators need adequate training and professional development to integrate AI tools effectively into their teaching.<\/span><\/p>\n

Firstly, protecting student privacy is paramount, and breaches can lead to significant risks. AI systems often require access to student data, raising concerns about how this information is collected, stored, and used. Coupled with this, not all schools have the same resources to implement AI technologies. Limited access to technology in school can create disparities in access to quality education, particularly in underfunded or rural areas where technology may be lacking.<\/span><\/p>\n

Notably, AI algorithms may perpetuate biases present in data, leading to unfair treatment of certain student groups. AI systems learn from historical data, and if this data contains biases, the algorithm will likely reproduce those biases. Ensuring that AI systems are equitable and fair is a significant challenge. In the article \u2018How will AI Impact Racial Disparities in Education?\u2019 Hoang Pham et al. (2024) contend that \u2018AI tools\u2026often rate racial minorities as less likely to succeed academically\u2019 (Pham et al., 2024, p.1), highlighting the need for transparency in AI systems. Educational stakeholders must understand how algorithms make decisions and ensure they are scrutinized for bias. Pham et al. (2024) also highlight findings from a case study conducted in Wisconsin, which found that the algorithm used predicted that the percentage of high school students who would not graduate on time was \u201842% higher for Black students than White students.\u2019 (Pham et al., 2024, p.1) Using AI to make predictions about academic success raises ethical questions about accountability and fairness. Decisions based on flawed data can have serious consequences for students’ futures.\u00a0<\/span><\/p>\n

\u00a0In addition to equity concerns, AI can provide insights based on data analysis, but these insights can be misinterpreted. AI specialists must train educators to understand and use AI outputs effectively to inform instruction.<\/span><\/p>\n

Furthermore, over-reliance on AI can decrease students’ critical thinking and problem-solving skills. For example, AI can provide quick answers and solutions, which might encourage superficial engagement with content. When students prioritize speed over depth, they may miss opportunities for deeper analysis and reflection.\u00a0\u00a0\u00a0<\/span><\/p>\n

The above concerns shape AI guidelines and policies in education. The ‘Guidelines for AI Integration throughout Education in the Commonwealth of Virginia’ document states, ‘Our education system must adapt to prepare a workforce that can leverage AI to its full potential while safeguarding against its risks.’ (Virginia Department of Education, 2023, p.1) Indeed, AI technologies can simulate real-world scenarios, allowing students to engage in hands-on learning. This practical application of knowledge helps bridge the gap between theory and practice, making education more relevant and engaging. Further, as AI becomes more prevalent in various industries, understanding its principles and applications will be crucial for students. Language used by the Virginia State Department suggests a de facto mandate for schools to integrate AI technology.\u00a0<\/span><\/p>\n

The guiding principles for AI use in schools in the state of Virginia are:<\/span><\/p>\n