The two-year draft Ohio budget would mandate the board of trustees of the state’s public universities and two-year colleges to oversee an adjustment of the general education core to include four areas: “(1) civics, culture, and society; (2) artificial intelligence, STEM, and computational thinking; (3) entrepreneurship and the principles of innovation; and, (4) workforce readiness.”
The inclusion of artificial intelligence literacy as part of the general education curriculum is a welcome proposal.
For example, we need a general education course on making optimal queries, which is described as “prompt engineering” in the industry. The prompting skill will complement other transferable general education skills such as writing, critical thinking, and reasoning. Learning to ask good questions is a must for getting the most useful output from apps like ChatGPT, Claude and Gemini.
Generative Artificial Intelligence (GenAI) is very good at answering prompts and following instructions, but it cannot ask good questions itself. Even the so-called reasoning models are not actually thinking, but predicting the next token. How well we teach our students in thinking, reasoning, and asking questions will make them proficient users of GenAI tools as part of the future workforce.
A bipartisan task force of the U.S. Congress on the need for AI literacy in curriculum has called for investment and broadening of participation in the development of an AI-skilled workforce. In December, the Ohio Department of Education and Workforce released its AI in Education Strategy that makes AI literacy in K-12 curriculum a priority.
GenAI non-agentic and agentic tools are being deployed in government, businesses, industry, and universities. These agentic tools are GenAI systems designed to complete specific tasks autonomously. Our students need the transferable skills in GenAI to be fully prepared to join the workforce of the future.
The good news is that many universities are developing protocols for GenAI in teaching and learning. In a nationwide survey of university administrators, it was found that 69% had adopted policies on use of GenAI in teaching and learning.
Early adopters among faculty are already using GenAI apps such as ChatGPT, Gemini, or Claude to develop lesson plans and slides, develop quizzes, detect plagiarism, and analyze data.
Many of our students use apps for assignments, writing code, and analyzing data.
However, it must be recognized that GenAI may not produce equally good results in all disciplines. For example, in writing courses, the use of GenAI has raised ethical concerns about plagiarism and deficiencies in argumentation. The ability to string together original ideas, reason through, and critical thinking are essential to learning about the logical dependence of a claim and on recognizing evidence that backs the claim.
The use of GenAI for tutoring math to high school students leads to lower learning outcomes. That said, in an experimental study carried out at Harvard University, it was found that tutoring lower-level physics courses with assistance from a GenAI co-pilot was more efficient and productive.
Anup Kumar is a professor at Cleveland State University.
Yet, fighting against GenAI in teaching and learning is not the way forward. We need to accept that GenAI will become essential for the workforce in most fields, including education. The agentic use of GenAI co-pilots as teaching assistants or tutors will only grow as newer versions of platforms such as Blackboard and Canvas incorporate them as standard features.
One hopes the legislature, if it adopts these core curricular changes, will provide adequate funding to effectively implement them so they do not become one of many unfunded mandates. Incorporating GenAI in teaching and learning will require subscriptions, and hardware upgrades for agentic tools to access servers of external data centers.
Anup Kumar is a professor of communication at the Levin College of Public Affairs and Education at Cleveland State University.
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