Getting started

To navigate the impact AI could have on your students achieving the learning goals you set out for them, it helps to first understand how to use these tools.

What is generative AI?

Generative AI tools create new content based on what they learn from their database(s). To make use of these tools, understanding how they work can improve how you and your students use them, or prompt them.

Some helpful terms to know before you get started with generative AI include:

Machine learning: a branch of artificial intelligence (AI) and computer science that focuses on using data and algorithms to enable AI to imitate the way that humans learn, gradually improving its accuracy (definition from IBM).
Deep learning: a subset of machine learning that uses multilayered neural networks, called deep neural networks, to simulate the complex decision-making power of the human brain (definition from IBM).
Algorithmic bias: Systematic and unfair discrimination embedded in algorithms, often resulting from skewed training data or flawed design, leading to biased outcomes that disproportionately affect certain groups or individuals.
Large language model (LLM): An AI system trained on vast amounts of text data to understand, generate, and predict human language, enabling sophisticated interactions and text-based tasks.
Natural language processing (NLP): A subfield of AI that uses machine learning to enable computers to understand, interpret, and communicate with human language.

How does it work?

We’ll explain ChatGPT as an example:

Though sometimes used interchangeably, ChatGPT and GPT are actually different pieces of technology. Built by the same research company, Open AI, the interactive chatbot app we know and use is ChatGPT. This chat platform is powered by GPT, a large language model. Large language model (or LLM) refers to the technology that drives natural language processing chatbots like ChatGPT, Bard, and Bing. LLMs “are trained on massive amounts of information scraped from the internet” and are designed to predict words based on likelihood, and cannot necessarily distinguish true information from predicted word sequences (Reidl 2023).

LLMs often “hallucinate” or offer information that isn’t true, nor can it be cited (Weise and Metz, 2023). But GPT models are continuously being improved. For example, while the industry standard is still GPT-3, newer versions such as GPT-4 will continue to be developed and improved (Alston 2024).

Accountability for the output of any tool resides with the owner. Therefore, while you might encourage students to use AI to explore ideas, they will need guidance on how to properly source and cite information. This means teaching them how to evaluate, verify, and identify sources on their own. The flowchart below illustrates the process of using AI in these situations.

Yes/no flow chart beginning with "Does it matter if the outpput is true?"

Flowchart adapted from the original created by: Aleksandr Tiulkanov (January 2023) in ChatGPTand Artificial Intelligence in Higher Education: Quick Start Guide. UNESCO.

Despite the tendency to hallucinate, text-based AI tools can still be extremely useful, if they’re prompted appropriately. “Prompting” in the context of AI refers to the specific language entered into a chatbot platform like ChatGPT. Also called “prompt engineering,” teaching students to skillfully craft input into an AI tool can help them learn how to ask useful questions of AI. (To explore more on prompt engineering, see Alby 2023, Chen 2023, and Saravia 2023.)

Prompting

At our current stage in AI’s development and capabilities, getting helpful results from LLMs comes down to effective prompting. Enhance your prompts by specifying the task, audience, and format, as demonstrated in the example below.

Specificity	Your input	AI output
Task only	Describe an assignment in which students set goals for the semester for a course.	300 words: In this assignment, you will explore the importance of goal setting in personal and professional development. You will analyze various strategies for setting and achieving goals, and evaluate their effectiveness in different contexts. Begin by defining the concept of goal setting. What does it entail, and why is it important in both personal and professional life? Discuss the characteristics of SMART goals (Specific, Measurable, Achievable, Relevant, Time-bound) and explain why they are considered effective for goal setting….[followed by 6 bullet points of considerations of varying relevance]
Task, audience, length, format of output	Design a goal setting assignment for students in a course and describe it in a single paragraph; goals should be submitted as a 3-5 point bulleted list.	82 words: In a concise paragraph, outline your personal and academic goals for the next few months. Consider what you hope to achieve both inside and outside the classroom, and be specific about your aspirations. Your goals should be realistic, measurable, and aligned with your values and aspirations. Once you have identified your goals, organize them into a 3-5 point bulleted list and submit them along with your reflection. This exercise will help you stay focused and motivated as you work towards your objectives.
Task, audience, format of output, length, context	Develop an assignment for college-age students. The writing should be one paragraph long and elicit a response of 3-5 points from students. It should encourage students to think critically about their personal and academic goals and ask them to set clear, achievable goals for the semester.	69 words: Reflect on your personal and academic aspirations, considering both short-term and long-term objectives. In a brief paragraph, articulate your reflections and outline 3-5 clear, achievable goals that you aim to accomplish throughout the semester. Your goals should be specific, measurable, and aligned with your values and aspirations. This exercise will empower you to stay focused, motivated, and accountable as you navigate the challenges and opportunities of the semester ahead.

Why use it?

AI tools can be used for a wide variety of teaching purposes, including idea generation, conducting literature reviews, drafting, revising, and designing. They can be helpful tools for fostering critical thinking about AI-generated content or to introduce students to research processes in your field. In other words, they can be used as a tool to support or augment the writing, researching, editing, revisiting, or designing processes as opposed to simply replacing them.

While AI has emerged as a transformative tool for learning activities, it can also serve as a personal assistant in many ways. For teachers and teaching assistants (TAs), AI can streamline administrative tasks and improve instructional strategies.

Jump to Using AI for more details.