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AI Literacy for Students

A student guide to AI literacy that will help you gain foundational knowledge of AI concepts, apply generative AI knowledge appropriately in an educational setting, and enable you to think critically about generative AI systems and tools

Potential and Limitations

Student speaking with chatbot in futuristic setting

Generative AI's Impact on Education

Abstract representation of AI enhancing education

Although we're still unpacking what kinds of impacts generative AI will have on education, we are starting to get a handle on it. Generative AI is available, easy to access, easy to use, and a powerful tool when used correctly. Students and educators alike are already using it and making an impact on their learning and teaching. It promises benefits like enhanced personalized learning, accelerated curriculum development, and real-time feedback; but it can also support drawbacks like cheating, plagiarism, and serving as a crutch to bypass critical thinking. The task to ensure we maximize its potential to elevate learning and minimize the potential to undermine it is one of the key challenges we face as educators.

This section outlines some examples of generative AI use in education, highlights pros and cons, and then considers its use from the perspective of a teacher and a student. Let's start with some examples of how generative AI can be used in education:


Personalized Learning Content

Generative AI can create tailored learning materials based on individual students' learning styles, preferences and performance, enhancing personalized education.

Applications:
  • Adaptive textbooks
  • Interactive modules
  • Customized practice exercises
Pros
  • Improve understanding
  • Improve retention
Cons
  • Quality of content will vary
  • Content would still need teacher oversight
  • Privacy concerns
  • Unequal accessibility

Content Creation

Educators can use generative AI to develop a wide array of content from textbooks to interactive modules. These AI systems can create content that is aligned with the curriculum, updated in real-time, and customized to cater to a diverse student population.

Applications:
  • AI generated lesson plans
  • Worksheets
  • Videos
  • Case studies
  • Scenarios
  • Problems and challenges
Pros
  • Save time
  • Easily customize content
  • Get immediate feedback
Cons
  • You still can't 100% trust that AI output - quality assurance checks needed

Personalized Tutor/Mentor/Coach

An AI chatbot can act as a virtual tutor/mentor/coach presenting content, checking for understanding, and providing prompts and coaching to support learning. Ethan and Lilach Mollick have created and tested a few comprehensive prompts that work reasonably well in ChatGPT (GPT-4) and Microsoft Copilot, but they are not quite as capable as you would hope. It is likely that an LLM used as a tutor would have to be specially trained to act as a good tutor. Khan Academy (Khanmigo), Google (Learn About) and others are working on such things, but their effectiveness is not yet proven.

Applications:
  • Directly support student learning at any time
Pros
  • Tutor would be tireless, always available, endlessly patient
Cons
  • General purpose AIs are not reliable for this
  • Fine-tuned chatbots not readily available
  • Still relatively unproven

Enhanced Student Work

If students are coached on effective and ethical use of generative AI, teachers can potentially set their quality expectations higher. For example, Ethan Mollick requires his entrepreneurship student to do at least one impossible task in their projects. Basically, what he means by this is that generative AI can help you code, create a website, design an app without you needing to know how to do that.

Applications:
  • More ambitious assignments
Pros
  • Higher quality of work from students
Cons
  • Privacy concerns
  • Generative AI training may take over other important aspects of class

Real-time Feedback

Generative AI is capable of providing immediate feedback on your writing, your coding, and even on your ideas..

Applications:
  • Students can check their own work
  • Marking assistance
Pros
  • Faster marking
  • Learners get feedback right away
Cons
  • Privacy concerns
  • Bias in AI could affect its feedback
  • Accuracy of marking

Language Translation

AI can instantly translate educational content (student or teacher generated) from and to many languages. General purpose chatbots are pretty good at this and specialized translators are even better.

Applications:
  • Translate educational content for English language learners
  • Translate student work into English
Pros
  • Supports inclusivity
  • Facilitates international collaboration
  • Aids comprehension
Cons
  • Translations might lack context and cultural sensitivity
  • Loss of meaning or nuance
Robots in style of Andy Warhol

Weighing the Benefits and Challenges of AI in Education

Abstract graphic representing balance in AI for education

The integration of AI in education brings both significant opportunities and notable challenges. Understanding this balance is key to harnessing AI's potential responsibly and effectively in learning environments.


The Hurdles: Challenges and Concerns

  1. Data Privacy Concerns: On the previous page, data privacy came up as an issue over and over again. Anytime that you enter something into a chatbot, you are "feeding the beast", i.e., giving the AI company even more data. Different AI companies will have different privacy policies, but the reality is you are sending them your (or your students') information and despite the policies, they have your data. AI companies are aware of these issues and are working on ways to support privacy-sensitive applications. One potential way to support privacy is to provide a private server for institutes. These are in the works, but currently require a large investment and/or a lot of specialized expertise.
     
  2. Equity and Access Issues: AI can seem magical and spellbinding but it is not universally accessible. Not only are some LLMs geographically locked down, but the best tools cost money. The digital divide is real, and the question lingers - how do we ensure that every learner, irrespective of their socio-economic status has equal access.
     
  3. Everything it Outputs is Made Up: This is a crucial point that's often overlooked - LLMs don't actually "know" anything in the way humans do. They create their responses by predicting what words should come next based on patterns in their training data. While these predictions can be remarkably accurate and useful, they're still essentially sophisticated guesses. This means that even when an AI sounds completely confident, it might be completely wrong, or worse, it might blend truth and fiction in ways that are hard to detect. This is particularly problematic in education where accuracy and reliability are paramount.
     
  4. Output May Not Be Reliable or Consistent: Ask an LLM the same question twice, and you'll likely get two different answers. While these answers might convey similar information, they can vary significantly in their details, depth, and sometimes even accuracy. This inconsistency can be particularly challenging in educational settings where we need dependable, standardized information. Bottom line: Every AI output needs human verification, and using this critical verification skill is essential.
  5. Overuse and Overreliance: When individuals depend too heavily on AI for tasks like writing, problem-solving, or creative ideation, there's a risk of diminishing their own critical thinking, analytical skills, and domain-specific expertise. Instead of developing a deep understanding or honing their abilities through practice, users might simply accept AI-generated outputs without sufficient scrutiny or personal engagement. This can lead to a passive learning approach, hinder the development of essential cognitive skills, and ultimately make individuals less capable when faced with novel situations or tasks where AI assistance is unavailable or inappropriate. Fostering a balance where AI serves as an assistant rather than a replacement is crucial to ensure that human intellect and creativity continue to flourish.
  6. The Need for New Pedagogical Approaches: The integration of AI into educational settings will require many teachers to re-examine their style and their approach to education. We are all going to have to think about how we provide content, how we do assessment, and how (or whether) we support our students to use AI as well.
     
  7. Other Ethical Considerations: The rise of generative AI gives rise to a number of other ethical considerations, many of which we should consider as we integrate generative AI into our teaching and learning practices.
    • LLMs can perpetuate and amplify existing biases because of the data they were trained on.
    • The data used for training may have come from sources the LLMs didn't have explicit rights to use. Should we consider not using an LLM because it may have violated intellectual property rights?
    • The servers used by LLMs for training and for running their neural networks use a lot of energy. Alphabet's CEO estimates that an LLM query could use as much as 10 times the energy of a standard Google search. Companies like Microsoft are looking at lower carbon footprint solutions (like solar or small scale nuclear reactors), but good solutions are not yet in use.
    • Generative AI will likely cause some level of job displacement. How should education adapt to mitigate this harm?
    • Social media already has a significant impact on our lives; affecting mental health and facilitating the spread of mis- and disinformation. Generative AI will enable a massive increase in the ability to create mis/disinformation. What role can we play in combating this?

The Upside: Benefits of AI in Education

  1. Personalized Learning Experiences: The ideal classroom is one where every student's unique learning style, pace, and need is catered to. AI has the potential to make this happen. It's not quite there yet, but if the pace of AI development over the last year or so is any indication, we are not far off. As a counter to this pro, we, as educators, really have to think deeply about what our role will be.
     
  2. Enhanced Efficiency for Educators: Grading takes ages and planning can be a grind. Generative AI can potentially take care of a lot of this grunt work, but we have to be careful. AI still makes stuff up and feeding student work into ChatGPT is probably a privacy violation.
     
  3. Ease of Generating Diverse Content: Generative AI makes it easy to take a base of content and modify it in ways that offer students multiple perspectives, make it more accessible for students with diverse needs, and adapt it to different languages.
     
  4. Idea Generator: Are generative AI tools actually creative? I don't know the answer to that, I do know that if you ask a chatbot for 50 unique ideas for a business related to shoe repair, it will give you 50 (or about 50, it's not always great at counting) ideas in less than 30 seconds. Now, most of those ideas will be not so great, but I'm sure a few will be worthy of some thought and there may be a diamond. Even if you don't use any of the ideas, you will probably be inspired for a new idea based on the ones the AI gives you. The best haiku I've ever written was 75% written by me, but 25% inspired by an idea that ChatGPT gave me.
     
  5. Personal Assistant or Sounding Board: I recently took a course on course design supported by AI. The course facilitator had created a number of comprehensive prompts that helped us create a learner profile, generate knowledge maps and learning outcomes, and then a storyboard for a course. One thing that we (all the students) remarked on was that, while the AI did not actually save us much time, the quality of work that we produced was much better than if we did it without the AI. Having the AI as an idea generator and then sounding board to bounce other ideas off of significantly improved our work.
     
  6. AI is Good at Giving Data-Driven Insights: Really, this is all AI does. It makes connections between the data that you train it with and then uses those connections to provide "insight" into any new data that you feed it. Image generators do this with pixels and LLMs do this with words. LLMs also do this with numbers and since data is really nothing more than a bunch of organized words and numbers LLMs are surprisingly good at analyzing spreadsheets, creating spreadsheets from raw data, and even highlighting links in data that you may have missed. ChatGPT Plus in Advanced Data Analysis mode is the best gen AI tool for doing this kind of thing.

Student Voices: Navigating AI in Education

Dreamy vision of student studying with futuristic AI interface
Abstract representation of student discussion

I came across an interesting comment from a student on a podcast by CBC's The Current about using generative AI like ChatGPT in education. This student was very motivated to learn but found some courses irrelevant. Due to a heavy course load, they focused on the courses they felt most relevant and used ChatGPT for the rest. Many students feel the same, especially when overwhelmed with work, and turn to ChatGPT for help. Cases like this show the willingness of students to use generative AI to cheat, but students also seem to understand the risks of doing so which they identified as not just academic penalties but also the learning they miss out on.


Perceived Benefits of GenAI

A survey by Cecilia Chan and Wenjie Hu of 339 students across six Hong Kong universities revealed that students find GenAI useful for:

Key Advantages Identified by Students:
  • Personalized and immediate learning support
  • Support with writing and brainstorming
  • Help with research and analysis
  • Support with visual and audio multimedia

Student Concerns and Apprehensions

The same study highlighted significant student concerns regarding the use of GenAI in education:

Primary Concerns Voiced:
  • Accuracy and transparency of AI-generated information
  • Privacy issues and data security
  • Potential loss of critical thinking and other essential skills
  • Job displacement or hiring challenges due to AI advancements
  • Exacerbation of socio-economic disparities
  • Ambiguity in institutional policies: navigating ethical use without academic dishonesty

Global Student Questions

These concerns are echoed by students globally, as discussed in forums like the AIxEducation conference. Students worldwide are grappling with a new set of critical questions:

Pressing Questions from Students:
  • How can I master these AI tools amidst an already demanding academic schedule?
  • How can I afford access to premium AI tools?
  • If I use AI for writing, does it compromise my authentic voice and learning?
  • How will educators address the digital divide regarding access to advanced AI tools?
  • Will AI ultimately devalue my hard-earned education and skills?

The AI tide is rolling in, with or without an invitation. Students are savvy; they see the potential of AI as both a powerful tool and a complex challenge. They are ready to engage, albeit with understandable trepidation about the evolving rules of this new academic landscape.


The Educator's Tightrope

Educators, too, find themselves in a delicate balancing act. They are tasked with a dual mandate: to deter the misuse of AI while simultaneously championing its educational benefits. As they navigate this complex terrain, the core challenge is to ensure that the fundamental essence of education—critical thinking, creativity, and genuine understanding—isn't lost amidst the growing capabilities of artificial intelligence.

Charismatic teacher surrounded by students

AI in the Classroom: Teacher Perspectives & Evolving Practices

Abstract representation of AI transforming education

When ChatGPT was first released in November 2022, many teachers had a moment of panic and thought that either "this is the end of education as we know it " or "this is the end of education as we know it ". Proponents like Ethan Mollick fully embraced ChatGPT and sought the best ways to use it in his classes. At the same time, school districts like the one in New York City banned ChatGPT outright because they didn't know how to deal with it at the time. Ethan Mollick's level of adoption is beyond what most of us know how to do and NYC school's reaction was an excessive knee-jerk reaction to the new technology that has since been reversed. Now that the initial reactions are behind us, many educators have put a lot of thought into how to best make use of LLMs like ChatGPT to support the education of our students. Institutes have added AI to their academic policies and most of these that I have read are permissive and generally put the choice of if and how to allow its use in the hands of the teachers and professors. Institutes have also released guidelines on how educators might use AI in their classes along with suggestions on how to adapt assignments to support its use.


Adapting to the New Landscape

It's clear that most teachers are going to need to change their practices somewhat, but the amount of change will vary from level to level and from topic to topic. Primary school teachers have likely changed their approach very little and instructors teaching exclusively hands-on topics probably haven't changed much either. On the other hand first year English and computer science professors have likely had to change their approach a lot - these are courses for which ChatGPT can probably help the most (write an essay, write some simple code), and first year courses (especially ones that students only take because they have to) are the courses in which students are most likely to look for outside "help". The value of the AI output for courses like this is high and so is the incentive.


The Path Forward: Thoughtful Integration

Most educators are finding a middle ground between full adoption and complete rejection, adapting their teaching methods thoughtfully rather than radically. The key is to focus on what matters most: developing students' critical thinking, creativity, and ability to evaluate information. In many ways, AI is pushing us to do what good teachers have always done - move beyond rote learning to deeper understanding. The challenge now isn't just teaching subject matter, but teaching students how to learn and think in a world where AI is a constant companion.

Unless otherwise stated, this page and AI Literacy for Students © 2025 by David Williams is licensed under Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International

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