Using Generative AI to make language more accessible

Educators can use generative AI to transform dense, technical material into clear, easily understandable content. This improves students’ comprehension and makes the learning experience more inclusive to a wider audience. While students are growing in their knowledge of complex academic topics, sometimes academic terminology can be a barrier. Particularly early in the course, students may not yet be familiar with the jargon and language of your subject matter. In addition, you may have learners in your course with a wide range of educational and cultural backgrounds. Some of your students may be from countries outside of the United States, and English may not be their first language. By demystifying complex concepts, jargon, and metaphors with generative AI, educators are empowered to create more equitable and effective learning environments for our diverse array of learners.

For example, you can use the following example prompt to get started:

“Could you please rewrite the following text to an 8-10th-grade reading level (using Flesch-Kincaid Grade Level) and clarify any complex jargon: “[Your text]” Thank you!”

In this prompt, we are asking ChatGPT to rewrite text to an 8-10th-grade reading level on the Flesch-Kincaid Grade Scale. This is the reading level recommended for a general adult lay audience. Feel free to adjust this to fit your target audience.

Example: An Online Course on Neuroscience

Drafting

Now imagine that you are a renowned neuroscientist and a highly regarded faculty member at Michigan Medicine. You are interested in developing an online course that will bring neuroscience concepts to a lay audience. You are excited to get started, but as you begin to develop content, you quickly realize that your typical content is aimed at seasoned medical students and filled with jargon that may be daunting to those without prior knowledge. You realize that generative AI may be able to assist you in breaking down concepts into simpler terms.

You fill in the example prompt with some of the text from one of your old in-person presentations with key concepts that you would like to include in this online course:

“Could you please rewrite the following text to an 8-10th-grade reading level (using Flesch-Kincaid Grade Level) and clarify any complex jargon:

In our introductory exploration of neuroscience, we delve into the intricate workings of the central nervous system (CNS), focusing on the complex interplay between neurons and glial cells. We examine the fundamental principles of neuronal communication, emphasizing the role of neurotransmitters in synaptic transmission and the significance of action potentials in neural signaling. A detailed analysis of the brain’s functional anatomy is conducted, where we dissect the various lobes of the cerebral cortex, the limbic system, and the intricate circuitry of the basal ganglia, highlighting their contributions to cognitive and motor functions. Additionally, we explore the mechanisms underlying neuroplasticity, emphasizing the synaptic and non-synaptic changes that facilitate learning and memory. The course also delves into the pathophysiology of neurological disorders, exploring the etiology and progression of conditions like Alzheimer’s disease, Parkinson’s disease, and multiple sclerosis, and discusses the latest advancements in neuropharmacology and neuroimaging techniques.

Thank you!”

In response to your input, ChatGPT gives you the following output:

“In our first look at neuroscience, we study how the central nervous system (CNS) works. This includes understanding how neurons (brain cells) and glial cells (supporting cells) interact. We learn about how neurons talk to each other, focusing on neurotransmitters, which are chemicals that help send messages in the brain, and action potentials, which are electrical signals in neurons.

We also look closely at the brain’s structure. This includes studying the different parts of the brain, like the lobes of the cerebral cortex, the limbic system (which deals with emotions), and the basal ganglia (important for movement), and how they help us think and move.

The course also covers neuroplasticity, which is how the brain changes to help us learn and remember things. We look at both synaptic changes (changes at the connections between neurons) and non-synaptic changes (changes within the neurons themselves).

We also learn about neurological disorders like Alzheimer’s disease, Parkinson’s disease, and multiple sclerosis. We study what causes these diseases and how they progress. Finally, we discuss new developments in treating brain disorders and ways to look at the brain, like neuropharmacology (study of how drugs affect the brain) and neuroimaging (brain scanning techniques).”

In this example, ChatGPT keeps all of the main concepts intact while using simpler language, providing definitions of terminology used (rather than removing it entirely), and breaking the large paragraph into more digestible, smaller paragraphs or chunks.

Refining

As a content expert, it is important to read through the output and ensure that all key concepts remain intact. It is also up to you to determine whether the revisions are sufficient and appropriate for your audience. You may choose to ask for stylistic revisions as well. For example, ChatGPT wrote the text as though the course is currently happening. However, you plan on delivering this information at the beginning of the course to talk about what the learner will learn. This is your preference.

You can ask ChatGPT to revise with the following:

“The course hasn’t happened yet. Please rewrite this to account for that. For example, using the phrase “we will” throughout.”

ChatGPT will then go through and make the requested revisions to the text using the appropriate tense that you indicated in your input:

“In our upcoming exploration of neuroscience, we will delve into how the central nervous system (CNS) functions. This will involve understanding the interaction between neurons (brain cells) and glial cells (support cells). We will learn about neuronal communication, focusing on neurotransmitters, which are chemicals that help send messages in the brain, and action potentials, the electrical signals in neurons.

We will also closely examine the brain’s structure, studying different parts such as the lobes of the cerebral cortex, the limbic system (which deals with emotions), and the basal ganglia (important for movement), and understanding how they influence our thinking and movement.

The course will cover neuroplasticity, which is how the brain changes to facilitate learning and memory. We will observe both synaptic changes (alterations at the connections between neurons) and non-synaptic changes (alterations within the neurons themselves).

Additionally, we will explore neurological disorders, including Alzheimer’s disease, Parkinson’s disease, and multiple sclerosis. We will investigate the causes of these diseases and their progression. Finally, we will discuss the latest developments in treating brain disorders and methods for examining the brain, such as neuropharmacology (the study of how drugs affect the brain) and neuroimaging (brain scanning techniques).”

Continue to refine as needed. Consider feeding into the chat examples of your tone of voice so that the content is not only accessible for learners but also contains a human element. In addition, you can increase your expectation of language understanding as your students grow in their knowledge and your expectations of understanding increase.

Generative AI can be a valuable asset to instructors looking for assistance with creating various aspects of course design. For example, generative AI, such as ChatGPT, can be a valuable tool for educators in drafting learning objectives. Using GenAI in any setting is usually a process of drafting and then refining prompts until the desired result is achieved. In this article, we will outline some ways to generate and refine learning objectives for a course.

Learning objectives are concise statements that articulate what students are expected to learn or achieve in a course. They play a crucial role in guiding both teaching strategies and assessment methods, ensuring that educational experiences are focused and effective. Clear and well-defined learning objectives are essential for aligning educational activities with desired learning outcomes. By analyzing a vast array of educational content and pedagogical methods in its training data, AI can offer a wide range of learning objective recommendations, which educators can then build off of, using their knowledge as experts in the field.

Articles

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Generative AI for Course Design: The Basics

Learn more foundational information about Generative AI

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Learning objectives and outcomes

How to craft good learning objectives for instruction

Using your preferred GenAI tool, here is an example prompt that you can use to get started:

Please create learning objectives for a course on [topic], focusing on [big idea 1], [big idea 2], and [big idea 3]. The learning objectives are concise one word sentences beginning with an action verb. Please refer to Bloom’s Taxonomy if you get stuck. Thank you!

This example prompt can be modified to fit your needs. For example, you may choose to add more ideas and give additional context about the course. The more detail and context you provide in your input, the better the AI output will be. So please feel free to add in outlines, syllabi, or any other materials that may help your GenAI assistant better understand your vision.

Example: An Online Course on the Cold War

Drafting Objectives

Now that we have our example prompt, let’s see an example of it in action. Imagine you are an instructor for an introductory online course on the Cold War. You plan to use ChatGPT to generate some ideas on potential learning objectives to get you started and guide your curriculum creation. You already have some general ideas on what you want to cover: causes, major events, and overall impact. You fill in the prompt as so:

Please create learning objectives for an online introductory course on the Cold War, focusing on its causes, major events, and impact on international relations. The learning objectives are concise one word sentences beginning with an action verb. Please refer to Bloom’s Taxonomy if you get stuck. Thank you!

You press enter and ChatGPT provides you with the following learning objectives:

“Identify the primary causes of the Cold War.

Describe major events and turning points during the Cold War.

Explain the ideologies of the United States and the Soviet Union during the Cold War.

Analyze the impact of the Cold War on international relations.

Compare and contrast different perspectives on key Cold War incidents.

Evaluate the effectiveness of diplomatic strategies used during the Cold War.

Summarize the global consequences of the Cold War in the post-war era.

Discuss the role of nuclear weapons in Cold War policies and strategies.

Interpret historical documents and sources related to the Cold War.

Assess the influence of the Cold War on contemporary international politics.”

Refining

It is now up to you as the expert to determine which learning objectives are the most relevant and how you should go about revising them. For example, you may look at the list and notice that there are no learning objectives that ask the learners to create something with the knowledge they’ve acquired throughout the course (e.g., a final project). You return to ChatGPT and ask the following:

Please craft a learning objective that has learners create something relevant to the topic at hand.

In response, ChatGPT provides you with the following:

Design a multimedia presentation that illustrates the timeline of the Cold War, integrating key events, major political figures, and their impacts on international relations.

If you disagree with this suggestion, you can reply with “More?” to get additional ideas. ChatGPT will then provide you with a longer list:

“Develop a documentary script focusing on a specific aspect of the Cold War, such as the Cuban Missile Crisis or the Space Race, incorporating primary sources and historical analysis.

Construct a series of infographics that visually represent the economic, political, and social changes in different countries during the Cold War era.

Compose a series of fictional letters or diary entries from the perspective of individuals living in different countries during key moments of the Cold War, reflecting their experiences and viewpoints.

Create a podcast series that discusses the influence of the Cold War on modern international relations, including interviews with experts or simulations of discussions between historical figures.

Produce an interactive map or timeline that allows users to explore the progression of the Cold War, highlighting significant events, treaties, and shifts in alliances.

Formulate a role-playing game where players assume the roles of world leaders during the Cold War, making decisions that could change the course of history.

Design a virtual museum exhibit showcasing artifacts, propaganda, and media from the Cold War, with descriptive and analytical captions explaining their significance.”

You can repeat this process as often as you’d like – adjusting the prompt and adding additional context (e.g., outlines, key ideas, information about your teaching style) to get better responses. When formulating responses for you, ChatGPT looks at the entire chat log so it is recommended that you continue to add to the same chat for best results.

In our next article, we’ll explore how to use Generative AI to improve accessible language in your course.

Introduction

Education is undergoing a significant transformation as generative artificial intelligence continues to develop at a rapid pace. It is now easier than ever for educators to experiment with generative AI in their practice and see for themselves how generative AI can be leveraged during the course development process to brainstorm, synthesize, and draft everything from communications to students to learning objectives.

Generative AI: The Basics

Before experimenting with Generative AI (GenAI), it is helpful to have some high level foundational knowledge of how GenAI works. Essentially, GenAI functions using advanced machine learning algorithms, specifically neural networks, which emulate human brain processing. These networks are trained with large datasets, enabling them to learn language patterns, nuances, and structures. As a result, GenAI can produce contextually relevant and coherent content, a capability exemplified in tools like ChatGPT.

To better understand how GenAI tools like ChatGPT work, let’s look at a breakdown of the acronym “GPT”:

GPT stands for “Generative Pre-trained Transformer.” It is a type of artificial intelligence model designed for natural language processing tasks. “Generative” refers to its ability to generate text based on a combination of the data it was trained on and your inputs. It can compose sentences, answer questions, and create coherent and contextually relevant paragraphs.

The term “Pre-trained” indicates that the model has undergone extensive training on a vast dataset of text before it is fine-tuned for specific tasks. This pre-training enables the model to understand and generate human-like text.

Finally, “Transformer” is the name of the underlying architecture used by GPT. Transformers are a type of neural network architecture that has proven especially effective for tasks involving understanding and generating human language due to their ability to handle sequences of data, such as sentences, and their capacity for parallel processing, which speeds up the learning process.

The GPT series, developed by OpenAI, has seen several iterations, with each new version showing significant improvements in language understanding and generation capabilities. Many of these improvements are due to the model continuously training on user inputs. OpenAI has made it transparent that your data is being used to improve model performance and you can choose to opt out by following the steps that will be outlined in the upcoming articles on how to use GenAI tools for course design, learning objectives and more.

Does it matter which GenAI Tool I use?

Not really. Individuals may find preferences for one tool or another based on response speed or comfort with the interface. You may wish to use a tool that can opt out of using personal data for training purposes. Most of the GenAI tools are generally similar.

Next Steps and Considerations

In educational contexts, the incorporation of GenAI tools, such as ChatGPT, will potentially reshape our approach to content creation and improve efficiency for educators who often find themselves pressed for time. However, it is important to note the importance of acknowledging the technology’s limitations, such as potential biases, outdated information due to insufficient training data, and incorrect information – often referred to as “hallucinations.” It is vital that you always fact-check and revise GenAI outputs to maintain the integrity and high quality of your content.

In conclusion, by leveraging GenAI tools like ChatGPT, educators can navigate course design with greater ease and efficiency. From drafting learning objectives and engaging course titles to simplifying complex academic language and brainstorming assessments, GenAI has the potential to be an invaluable asset to your design work. However, it is critical to remember that these tools come with limitations, including potential biases and inaccuracies. By combining the strengths of GenAI with the expertise and critical oversight of educators, we can efficiently create new experiences for our learners.

Introduction

It is safe to say that by now, you have seen many articles/posts, opinions, and stories about ChatGPT—and the larger AI-Language Learning Models (LLMs)—in relation to higher education and teaching/learning in particular. These writings included several perspectives ranging from raising concerns to celebrating new opportunities and a mix of the former and the latter. Also, these writings continue to evolve and grow rapidly in number as new AI-powered LLMs continue to emerge and evolve (e.g., Google’s new AI LLMs: Bard).

The intent of this piece is not to add another article sharing tips or concerns about ChatGPT. That being said, this article (1) summarizes the major concerns about ChatGPT and (2) the ideas about its positive implications based on what it is published to date.

Concerns about ChatGPT

Faculty, scholars, and higher education leaders have raised several concerns about ChatGPT. These concerns stem from possible ways it can be used.

Using ChatGPT to cheat by asking it to write essays/answer open-ended questions in exams/discussion forums and homework assignments (December 19th, 2022 NPR Story) (December 6th, 2022 Atlantic Story) (January 16 New York Times Story).
Using ChatGPT to author scholarly works which conflict with the ethical standards of scientific inquiry. Several high-impact/profile journals have already formulated principles to guide authors on how to use LLMs AI tools and why it is not allowed to credit such tool as an author—any attribution of authorship carries with it accountability for the scholarly work, and no AI tool can take such responsibility (January 24th, 2023 Nature Editorial).
ChatGPT can threaten the privacy of students/faculty (and any other user). Its privacy policy states that data can be shared with third-party vendors, law enforcement, affiliates, and other users. Also, while one can delete their ChatGPT account, the prompts they entered into ChatGPT cannot be deleted. This setup threatens sensitive or controversial topics as this data cannot be removed (January 2023 Publication by Dr. Torrey Trust).
ChatGPT is not always trustworthy, as it can fabricate quotes and references. In an experiment conducted by Dr. Daniel Hickey at Indiana University Bloomington, Instructional Systems Technology department, “ChatGPT was able to write a marginally acceptable literature review paper, but fabricated some quotes and references. With more work such as including paper abstracts in the prompts, GPT is scarily good at referencing research literature, perhaps as well as a first-year graduate student.” (January 6th, 2023, Article by Dr. Daniel Hickey)

Excitement about ChatGPT

At the other end of the spectrum, there have been several ideas that express interest and excitement about ChatGPT in higher education. These ideas stem from how they can be used ethically and in a controlled manner.

Using ChatGPT to speed up the writing of drafts for several outlets (reports, abstracts, emails, conference proposals, press releases, recommendation letters, etc.) ChatGPT can produce elaborated writing that must be edited to remove any possible inconsistencies or inaccuracies (December 7th, 2022 Social Science Space story)
Using ChatGPT in the process of brainstorming ideas for curriculum design, lesson planning, and learning activities. The tool can provide some novel ideas or remind educators of some instructional techniques and strategies that they had heard about in the past (January 23rd, 2023, Article by Dr. David Wiley).
Using ChatGPT to provide students tutoring/scaffolds. The tool can act like a virtual tutor who does not simply give the answer to the student but rather scaffold them to reach the correct answers by themselves. (Sal Khan, founder/CEO of Khan Academy, Spring 2023 TED Talk)
Teaching with ChatGPT to train students on using AI tools and models, provide opportunities to exercise critical thinking skills, and improve their technological literacy (January 12th New York Times story).

Concluding Thoughts

There are major concerns about ChatGPT and the larger AI-powered Language Learning Models (LLMs) phenomenon. These concerns are legitimate and are opposed by notable ideas about the positive implications of AI-powered LLMs in higher education classrooms. As we aspire to make evidence-based educational and learning design decisions, one should carefully review the research that has been done on AI in relation to higher education up to this point and engage with the gaps as opportunities to expand knowledge and find new opportunities and risks.

Our University’s newly formed advisory committee on the applications of generative AI is a good example of how higher education institutions ought to recommend the use, evaluation, and development of emergent AI tools and services. Additionally, discussions about generative AI and its implications on education happening in public venues are necessary to strengthen the public-facing mission of the University, where input from educators, students, and members of the community is welcome.