| Autor: |
Hadley-Hulet, Aria, Ellis, Marc, Moore, Austin, Lehnardt, Emily, Longhurst, Max |
| Předmět: |
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| Zdroj: |
Science Teacher; 2024, Vol. 91 Issue 2, p29-34, 6p |
| Abstrakt: |
The purpose of this position paper is to describe a historical timeline of science education. Using historical documents and current science education research, the authors create an evolutionary description of science education changes over time and how these shifts could influence how Artificial Intelligence (AI) is used in science education. The focus is on how societal and educational catalyst events, spanning from the Industrial Revolution to the Next Generation Science Standards (NGSS) and the COVID-19 pandemic, influenced science education. Next, the authors suggest that teachers should meaningfully implement the use of AI in ways that focus on student-centered learning and restore the progress made by the K-12 Framework and NGSS. These include generating ideas about problems that students can solve in an interest area, analyzing large sets of real-world data, generating grade appropriate science readings to develop background knowledge, and using AI to grade unique student work to replace multiple-choice response exams. AI and science education may best be described by a Chat GPT response: "It's important to note that while AI can enhance science education, it should not replace human teachers. Instead, it should be used as a tool to augment and support their expertise, fostering a blended learning environment that combines the benefits of technology with human guidance and mentorship." [ABSTRACT FROM AUTHOR] |
| Databáze: |
Complementary Index |
| Externí odkaz: |
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