AI and Computational Thinking in the Classroom
Computational thinking is an important topic for today’s students, particularly as technology improves to the point where people must find ways to work with it rather than ignore it. In learning to think computationally, students play a role in how these emerging technologies are used or created. Computational thinking may involve more than just code, but the underlying coded processes can be decoded through its methods.
AI is one such emerging technology. AI, or artificial intelligence, involves probabilistic decision making by machines. Basically, it is “learning” that is underlaid by sophisticated mathematics. The field has been steadily progressing over the years, but in the 2020s, progress has gotten very fast, particularly for generative AI.
ChatGPT is one of the most well-known generative AIs at present. It is an LLM, or large language model, that produces writing as its output. If you’re curious as to how it works, this explainer from Stephen Wolfram walks through the steps it takes to produce text. Basically, it is a series of choices informed by surrounding text.
Educators are taking notice of generative AI, leaving them wondering what AI’s role in the classroom should be. A filtered news search on Google will leave you with pages upon pages of explainers, blog posts and more. Those results, however, often don’t touch upon the ways that AI can connect with other problem-solving mindsets.
Sometimes, exploring two ideas through a single lens can be helpful. While it’s easy to flub a lesson that’s half-baked or too focused on keeping a lens in mind, when it works, it works. In this way, it’s worth considering how AI and computational thinking — two tech-related skills — might connect.
Computational thinking is, on a basic level, a problem-solving paradigm. Various concepts make up this thinking skill, ranging from deconstruction (breaking things down) to abstraction (viewing things from a big-picture scale). Computational thinking works well to help with coding, but its concepts can be applied to other fields — poetry, chemistry and more.
With generative AI, much discussion has centered on the idea of “prompt engineering” — finding ways to communicate with the AI interface to show the results desired. The skills to engineering a good prompt align particularly well with computational thinking. For example, in trying to articulate a style of writing, you must deconstruct its genre to pinpoint the rhetorical choices at play.
In early 2023, education as a whole is coming to terms with how tools like ChatGPT might be handled at the start of the fall school year, a few months away. In a sense, this seems like a dire task — the AI itself is rapidly changing from week to week, let alone month to month. While there are tools to try and check for AI writing, and schools looking to prohibit it, it might be better to embrace it in order to monitor its use.
Part of that embracing can be done by connecting AI to other skill sets, as with the suggestion to tie prompt engineering to computational thinking concepts. Additionally, with plugins, the knowledge-making options increase. Rather than using the AI simply for text generation, prompts with ChatGPT can begin to foster mathematical explorations or deeper searches.
Imagine the possibilities…
- A student could use an essay prompt to generate an essay, then offer prompts for revision to pinpoint changes to syntax, offering deconstruction when texts are read side by side.
- A student could search for exemplars of a certain type — particularly using a plugin to allow for a breadth of results — to use in abstraction, a “class” of sorts.
- A teacher could set parameters to create model texts or questions, which could present the idea of pattern-matching to students.
Educators that are leaning into the idea of adding AI to their lessons make both input and output vital parts of students’ learning. The AI is a peer of sorts, offering its take on specific prompts and giving text that can be explored and enriched by a human touch. A combined approach might end up being best!
If you’re considering AI’s role in your classroom, consider how it might work with computational thinking, deepening how students connect with data.
About the blogger:
Jesika Brooks
Jesika Brooks is an editor and bookworm with a Master of Library and Information Science degree. A lifelong learner herself, she has always been fascinated by the intersection of education and technology. She edits the Tech-Based Teaching blog (and always wants to hear from new voices!).
