Rhizomatic Learning

I saw the term " rhizomatic learning" used in an article about digital pedagogy. I know about rhizomes because I am a gardener but the use of it for learning was new and not immediately clear.

As introduced by the philosophers Gilles Deleuze and Felix Guattari, the rhizome takes that botanical term that refers to a root structure that expands and connects in multiple directions. It creates a decentralized, horizontal structure. Applying it to learning, particularly in higher education, means that students navigate their learning based on the cognitive conflicts they encounter.

Rhizomatic learning encourages students to acquire knowledge through the interconnectedness of curricular content, prompting them to explore diverse perspectives and methods. This is not a traditional approach or path but one that can lead to a critical, reflective learning experience.

iris rhizomes
September is when I divide my iris rhizomes based on their nodes - a common networking term too.

Rhizomes help plants spread and survive in various conditions. Rhizomes often store nutrients and energy, allowing the plant to regrow if above-ground parts are damaged or destroyed. Unlike roots, rhizomes have nodes from which new shoots and roots can emerge. In my garden, I am most familiar with the types of iris plants that have rhizomes. Other examples are ginger and the part of ginger we use as a spice is a rhizome. Many species of bamboo spread via rhizomes, which can form dense clusters and cover large areas. Near water, you often find cattails (Typha spp.), a wetland plant that has rhizomes that anchor them in muddy soils and help them spread across wetlands.

Applying this concept to the principles of critical pedagogy and to generative AI could offer a new dimension to the relationship between learning situations and the digitization of learning processes. The rhizome, in this framework, symbolizes a non-hierarchical, decentralized network of ideas and knowledge, in contrast to traditional, linear models of learning.

The term is new to me but the idea is not completely new. I have used approaches that seem to fit into this framework.

Platforms like forums, social media, and MOOCs (Massive Open Online Courses) and Online Learning Communities often embody rhizomatic principles, where learners can pursue diverse interests and create their learning paths.

PBL (project-based learning) students explore real-world problems and collaborate on projects, allowing for a more flexible, student-driven approach to acquiring knowledge.

Inquiry-based learning is an approach that encourages students to ask questions, conduct research, and explore topics of interest, promoting a more decentralized and learner-directed way of learning.

Learning that can be described as Self-Directed Learning where individuals take charge of their own learning journeys, choosing what and how they learn based on their personal goals and interests, are engaging in rhizomatic learning.

AI in Online Learning

.online designingCoursera’s CEO, Jeff Maggioncalda, says leveraging AI in online learning is key to a more accessible, flexible education experience. Coursera is a major platform for free and paid, non-credit and credit learning opportunities. Remember MOOCs? The term isn't in as wide usage as it was a decade ago but Coursera was an early serious player in that space and still offers short-form training and master’s degrees from Ivy League institutions like the University of Pennsylvania.

While many in education have been worrying about how AI is and will impact teaching and learning, online providers and course designers have been more likely to embrace AI tools.

Generative AI is good at language translations and Coursera who now has 4,200 courses translated into 17 languages as AI has made the translations easier and more affordable. They have also experimented with using AI for a personalized learning companion (chatbot) named Coach where students can ask for help on a concept, to create practice problems, or summarize activities. It won’t give users the answer, especially during testing.

For course designers, it can create outlines, write learning objectives, and compile lessons into new courses.

Coursera works with partners who can make content available for free.

So You Want To Be An AI Prompt Engineer

AI prompt engineerWhen I was teaching in a high school, I used to tell students (and faculty) that we were not preparing them for jobs. I was sure many of our students would end up in jobs with titles that did not exist then. There is a song by The Byrds from the 1960s titled "So You Wanna Be a Rock 'n' Roll Star." In 2024, it could be "So You Want To Be An AI Prompt Engineer."

The role of AI prompt engineer attracted attention for its high-six-figure salaries when it emerged in early 2023. What does this job entail? The principal aim is to help a company integrate AI into its operations. Some people describe the job as more prompter than engineer.

There are already tools that work with apps like OpenAI’s ChatGPT platform that can automate the writing process using sets of built-in prompts. Does that mean that AI will replace AI prompt engineers already? For now, the prompter works to ensure that users get the desired results. They might also be the instructors for other employees on how to use generative AI tools. They become the AI support team. AI can automate "trivial" tasks and make more time for work that requires creative thinking.

What kind of training leads to getting this job? You might think a background in computer science, but probably a strong language and writing ability is more important. People who write in the corporate world might justifiably fear AI will take their jobs away. Being a prompter might be an alternative.

Still, I suspect that there is a good possibility that a prompter/engineer's job might be vulnerable as software becomes better at understanding users’ prompts.

If you are interested in being an AI prompt engineer, I posted last week about some free online courses offered by universities and tech companies that included three courses that relate to creating prompts for AI.

AI Applications and Prompt Engineering is an edX introductory course on prompt engineering that starts with the basics and ends with creating your applications.

Prompt Engineering for ChatGPT is a specific 6-module course from Vanderbilt University (through Coursera) that offers beginners a starting point for writing better prompts.

Another course on ChatGPT Prompt Engineering for Developers is offered by OpenAI in collab with DeepLearning and it is taught by Isa Fulford and Andrew Ng.  It covers best practices and includes hands-on practice. 

Learning AI - Free College-Level Courses

online student

If you are interested in taking some free AI courses offered by Google, Harvard, and others, here are 8 you might consider on a variety of approaches. For Coursera courses without the trial, go to the course you want to take and click 'Enroll for free', then 'Audit the course'. You'll need to create an account to take courses, but won't need to pay anything.

Google offers 5 different courses to learn generative AI from the ground up. Start with an Introduction to AI and finish having an understanding of AI as a whole.  https://lnkd.in/eW5k4DVz

Microsoft offers an AI course that covers the basics and more. Start with an introduction and continue learning about neural networks and deep learning.  https://lnkd.in/eKJ9qmEQ

Introduction to AI with Python from Harvard University (edX) is a full 7-week course to explore the concepts and algorithms of AI. It starts with the technologies behind AI and ends with knowledge of AI principles and machine learning libraries.  https://lnkd.in/g4Sbb3nQ

LLMOps are Large Language Model Ops offered by Google Cloud in collaboration with DeepLearning. Taught by Erwin Huizenga, it goes through the LLMOps pipeline of pre-processing training data and adapt a supervised tuning pipeline to train and deploy a custom LLM.

Big Data, Artificial Intelligence, and Ethics is a 4-module course offered by Coursera from the University of California - Davis that covers big data and introduces IBM's Watson as well as learning about big data opportunities and knowing the limitations of AI. I think the inclusion of ethics is an important element.

AI Applications and Prompt Engineering is an edX introductory course on prompt engineering that starts with the basics and ends with creating your applications.

Prompt Engineering for ChatGPT is a specific 6-module course from Vanderbilt University (through Coursera) that offers beginners a starting point for writing better prompts.

Another course on ChatGPT Prompt Engineering for Developers is offered by OpenAI in collab with DeepLearning and it is taught by Isa Fulford and Andrew Ng.  It covers best practices and includes hands-on practice.