Three Years Post-ChatGPT: It's Time to Stop Debating and Start Teaching

From Tool-Focus to AI Literacy: Teaching Competencies That Outlast the Technology

November 2022 feels like ancient history now. ChatGPT dropped, educators collectively panicked, wrote a thousand think pieces about academic integrity, and then... what? Three years later, our students are heavy users while many teachers are still trying to figure out where to start.

The question isn’t “Should students use generative AI?” anymore. They are. Right now. For homework, for essays, for research – sometimes well, often badly, and almost never with any real understanding of what’s happening under the hood. We can keep debating the philosophical implications and patiently answering the naysayers, or we can roll up our sleeves and figure this out together with our students.

That’s why, when Cornelsen (a major German educational publisher) asked me, I agreed to write a workbook, designed for classroom use. Not because I have all the answers – honestly, I’m learning alongside my students every day – but because educators need something practical to work with. A starting point. A framework that treats AI literacy as what it is: a fundamental competency for the 21st century, sitting right alongside reading, writing, and critical thinking.

The Unique Challenges in German-Speaking Education

Here’s something that makes AI education particularly challenging in Austria and the German-speaking world: it’s not straightforward to know as a teacher how to even approach generative AI. It starts with simple logistical questions that quickly become complicated.

Which AI can I actually use with my students?

For students under 14, the answer isn’t easy. Most major AI platforms require users to be at least 13 or even 18, which immediately creates barriers. Some solutions: tools like DuckDuckGo’s Duck AI or Mistral AI allow use without logging in, making them accessible for younger students without age verification concerns.

Then there are dedicated educational platforms like Fobizz or MagicSchool that allow teachers to create virtual learning environments with pre-approved AI tools specifically designed for classroom use - access via code only. Canva, with an educational license, provides AI tools within a school-safe framework. But knowing about these options requires time and research that many teachers simply don’t have.

Am I even allowed to use this?

Data protection regulations add another layer of complexity. GDPR compliance isn’t just bureaucracy – it’s about protecting our students’ data. Which tools are actually safe to use? What data are they collecting? These aren’t trivial questions when you’re responsible for minors’ digital safety.

My workbook acknowledges these practical realities. I’ve suggested tools that work without mandatory login (especially for the early exercises), and the guidance notes help teachers navigate the regulatory landscape we’re working within. Because before we can teach AI literacy, we need to clear these logistical hurdles.

The Challenge of Writing About AI

Let me be honest about something: any book written about generative AI is a snapshot in time, and probably an outdated one before the ink dries. New features drop every week. Models get updated. Tools that seemed cutting-edge three months ago are already old news.

So why write it at all?

Because teachers need help now. Not in another year when the technology “stabilizes” (spoiler: it won’t). Not when we’ve all become AI experts (we’re all learning). Right now, when students are using these tools daily and we’re scrambling to provide guidance.

The workbook focuses on transferable competencies – prompt literacy, critical evaluation, ethical awareness, transparent documentation – that will remain relevant regardless of which specific tools emerge next. I’m not teaching “how to use ChatGPT.” I’m teaching students (and hopefully helping teachers) develop thinking skills that apply to any AI system they encounter.

And here’s what I’ve discovered: when teachers guide students through structured AI literacy work, something wonderful happens. The teachers develop their own literacy too. It’s co-learning in the best sense – experimenting, evaluating, reflecting together.

Building AI Literacy as Core Competency

AI use in education right now is embedded but chaotic. Students are using AI tools constantly, but without framework or guidance. Teachers want to integrate AI meaningfully but feel overwhelmed and uncertain. We’re stuck in tool-focus mode (arguing about which chatbot to allow) instead of building actual competencies. We’re reacting instead of designing.

This workbook is fundamentally about AI literacy, not AI usage. There’s a crucial difference.

When we talk about literacy – whether it’s reading, digital, or media literacy – we’re talking about the ability to understand, apply, reflect on, and co-create with a medium. AI literacy follows this same pattern. It’s not about producing content with AI; it’s about understanding how AI works, when to use it, when not to, what its limitations are, and how to engage with it critically and ethically.

The workbook draws on emerging AI literacy frameworks that emphasize:

• Understanding: Knowing what AI is, how it functions, and its capabilities and limitations

• Applying: Using AI tools effectively and appropriately for specific tasks

• Reflecting: Critically evaluating AI outputs and one’s own AI usage practices

• Co-creating: Engaging with AI as a tool while maintaining human agency and creativity

These four dimensions – often referenced in competency frameworks being developed across Europe – structure the entire workbook. We’re not just teaching students to generate text or images. We’re helping them develop the critical capacities to engage thoughtfully with AI systems throughout their lives.

This approach moves us from uncertainty toward shared competency. Not by having all the answers, but by providing structure for the questions we’re all asking. It offers clear learning objectives, structured prompting procedures, and competency-based activities that work.

The materials are designed to be usable by teachers without special AI expertise. Because honestly? Most of us are figuring this out as we go. And that’s okay. The focus on fundamental literacy skills – rather than technical mastery – means teachers and students can genuinely learn together.

How to Use This Book (A Learning Journey for Everyone)

The workbook is divided into two parts, with literacy development as the through-line.

Part 1: Theoretical Foundations (Building Understanding Together)

Before students – or teachers – jump into using AI tools, we need shared understanding of fundamental questions:

• What is AI, really? (And what’s the difference between traditional and generative AI?)

• How does generative AI actually work?

• What can and can’t it do?

• What about data privacy and ethics?

• How do you write a good prompt?

• What are responsible practices for AI usage in school?

This foundation gives everyone – students and teachers alike – a common vocabulary and conceptual framework. Students explore AI manipulation, learn to identify deepfakes, understand the environmental costs of AI infrastructure, and investigate copyright concerns around training data. They complete a knowledge test to ensure foundational understanding before moving to hands-on work.

These theoretical foundations directly address the understanding dimension of AI literacy. Students aren’t just learning facts about AI – they’re building conceptual frameworks that will help them make sense of AI developments throughout their lives.

In my experience, teachers often work through these sections alongside students, and that’s perfect. We’re all developing our critical AI literacy together.

Part 2: Eight Practical Exercises (Applying, Reflecting, Co-creating)

This is where we activate the other three dimensions of AI literacy through practice. Each exercise follows a consistent structure that scaffolds learning for both students and teachers:

• Clear learning objectives aligned to literacy competencies

• Step-by-step activities with room for experimentation

• Comparison exercises (same prompt, different tools—what happens?)

• Structured reflection prompts emphasizing critical evaluation

• Portfolio integration documenting the learning journey

The eight core exercises span different contexts and subjects:

1. First AI Conversations – Learning to write effective prompts and comparing outputs across different chatbots

2. Languages and Speaking – Using AI for translation, pronunciation, and language support

3. Inventing Stories – Leveraging AI as creative partner while maintaining authorship

4. Smart Search with AI – Moving beyond traditional search to AI-assisted research

5. AI as Personal Explainer – Making complex concepts accessible through scaffolded AI assistance

6. Creating AI Art – Generating images while understanding prompt engineering and visual literacy

7. Visual Vocabulary Journey – Combining language learning with image generation

8. Literature Analysis Creatively Extended – Reimagining book covers, visualizing characters, exploring alternative plots

Plus bonus chapters on songwriting and podcasting with AI (available via webcode).

Each exercise activates multiple literacy dimensions simultaneously. When students compare outputs from different chatbots, they’re applying their prompting skills, reflecting on differences in responses, and understanding how different models produce varied results. When they create AI art, they’re co-creating with the tool while reflecting on what the AI gets right and wrong.

The Digital Portfolio Approach

I suggest that students build a digital AI learning portfolio throughout the course using accessible tools like Canva (with educational license), Book Creator, Padlet, OneNote, or Google Slides. Every exercise requires documentation: links to conversations, screenshots of prompts and results, reflections on what worked and what didn’t, tools used, dates, and transparent attribution.

This portfolio becomes evidence of literacy development – showing progression from initial uncertainty to more confident, critical engagement with AI tools. And it gives teachers concrete examples of what AI literacy looks like in practice across all four dimensions.

The Bigger Picture: AI Literacy as Lifelong Competency

This workbook represents a shift I’m trying to make in my own teaching – from tool-focus to competency-focus, from usage to literacy. I’m not teaching students to use specific platforms (those will change anyway). I’m helping them develop transferable literacy skills:

• Prompt literacy – Understanding how to communicate effectively with AI systems

• Critical evaluation – Assessing AI outputs for accuracy, bias, and usefulness

• Ethical awareness – Understanding implications and responsibilities of AI use

• Transparent documentation – Professional practices for citing and attributing AI assistance

• Creative partnership – Knowing when AI enhances work versus when it replaces thinking

These literacy competencies – understanding, applying, reflecting, and co-creating –should serve students regardless of which AI tools emerge next year or five years from now. And they help teachers navigate this landscape with more confidence too.

The goal isn’t to make students AI experts. It’s to help them become AI-literate citizens who can engage critically and creatively with these technologies throughout their lives—in school, in work, in civic participation, and in their personal lives.

For the AI Educator Community: Building Literacy Together

This workbook provides structure without claiming to be definitive. It addresses concerns while remaining practical. It focuses on building fundamental literacies rather than teaching tools. It’s comprehensive without being overwhelming.

For colleagues in German-speaking countries specifically: the guide addresses our unique regulatory context and suggests tools that work within our data protection frameworks. Because literacy development can’t happen if we can’t even figure out which tools we’re allowed to use.

Three Years In: What We’re Still Figuring Out

We’ve learned that banning AI doesn’t work. We’ve learned that hoping students will “just figure it out” doesn’t work either. We’re learning that AI literacy isn’t an add-on – it’s becoming as fundamental as digital literacy was fifteen years ago, or reading literacy before that.

We’re also learning that students are remarkably capable when given proper guidance. They can grasp complex ideas about bias in training data. They can develop sophisticated evaluation criteria for AI outputs. They can make thoughtful ethical decisions about when and how to use AI. They can become genuinely AI-literate.

But they need structure. Framework. Curriculum built on sound literacy principles. And frankly, so do we as teachers.

This workbook is a snapshot in time. Some exercises will need adaptation as AI capabilities evolve. But waiting for “the perfect curriculum” means another cohort of students navigates this landscape without developing genuine literacy.

So I’m offering what I’ve learned so far, knowing you’ll adapt it, improve it, and make it work for your context. That’s how we move forward –together, iteratively, learning from each other and from our students, building AI literacy one exercise at a time.

A Final Thought: The Teachers Learn Too

One unexpected benefit I’ve seen: when teachers guide students through structured AI literacy work, they develop their own competencies in the process. It’s not one-way instruction – it’s collaborative exploration. Teachers tell me they feel less intimidated by AI after working through these exercises alongside their students.

That’s maybe the most important thing this workbook does. It creates a framework for mutual literacy development. Teachers don’t need to be AI experts first. We can learn alongside our students, which honestly might be the most valuable lesson we model: how to approach new technology with curiosity, critical thinking, and willingness to experiment.

Because that’s the real AI literacy we all need—not mastery of specific tools, but the confidence and competencies to engage thoughtfully with whatever comes next.

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About the Book: “Künstliche Intelligenz kompetent nutzen” is available from Cornelsen Verlag (ISBN 978-3-589-17017-3). The workbook includes access to additional online materials and bonus chapters via webcode.

About the Author: Alicia Bankhofer is an English and ICT teacher in Vienna, Austria, working in secondary education. She serves as eLearning coordinator at her school and provides teacher training in AI literacy and media competency across Austria. She’s developing AI literacy alongside her students and the teachers she works with.