Notes in the Margin - noticing the learning that matters

The rise of AI in education is a growing concern because students are using it to bypass critical thinking and genuine effort. If an end product can simply be generated by AI, its educational value is lost. The solution lies in shifting the focus from the final product to the process— focusing more on the learning journey and all of the mistakes, reflections and growth that happens along the way. If we shift our thinking to value the 'how' over the 'what,' we can create deeper, more authentic learning experiences.

Process over Product

I’m a firm believe in ‘process over product’ when it comes to assessment design. To combat plagiarism and avoid AI produced artefacts or ‘too easy’ copying and pasting, I try to design assessment that champion ‘notes in the margin’ rather than a shiny product at the end.

A quick anecdote

This week, I witnessed a student on the verge of giving up—frustrated by a lack of skill and a soured partnership. The assessment felt overwhelming, and the temptation to use AI for quick solutions was strong. Their belief that the final product mattered more than the learning journey was holding them back.

I reminded them that the real focus of the task is the thinking and problem-solving along the way. Through planning, drafting, making mistakes, and reflecting, students log their learning in a journal with prompts like: “What was hard?”, “What didn’t work at first?”, “What did I fix?”, and “What feedback did I receive?”. These notes capture the true essence of learning.

For this student, that shift in perspective was transformative. Their productive struggle and decision to take a new direction became a key part of their growth. While students may still submit a polished final product, the real value lies in the ‘notes in the margin’—the evidence of their process. If we can help students see that the journey matters more than the destination, we can equip them with the skills they need to become lifelong learners.

Notes in the margin

When I refer to notes in the margin I’m referring to the messy and sometimes incomplete jottings that happen during the thinking process. It might be annotation or quick notes or even question marks to show that a concept is not yet clear. Notes in the margin are personal and don’t need to be polished for presentation. They are a vital part of revealing the personal learning journey - so that even if information is sourced from ‘you know where’ - the notes reveal an element of processing and engaging with the text that is a record of engagement. Margin notes can include reflections, annotations, insights, or sketches that capture personal thinking

Drawing, sketching, scribbling, questioning, wondering, noticing, asking, clarifying - this are the verbs that matter.

The role of notes in the margin

As a counter to generative AI , personal and reflective notes in the margin are the shiny human thing.

I have noticed with interest that my best ideas are the ones that I have scribbled into the margins of printed drafts. Similarly, this blog is born out of a scrawly page of notes that I started this morning while I was cooking the family breakfast. Notes in the margin can provide a depth of understanding that a published text on its own may not fully show.

Similarly I recently printed a page of typed unit planning notes that I might have thought were finished had I not provided myself time for the valuable ‘jotting and scribbling’ stage where I could clarify sequences, question my timing and extend some of my thinking.

Practical strategies

A fantastic literacy activity is using comment codes to annotate texts where you can come up with your own acronyms to record the process of reading. ‘LUL - look up later’, "‘II” - interesting insight, ‘DTS’ - don’t think so, ‘NP - needs proof’ - you can come up with your own to match the voice in your head - but the act of making notes (rather than taking notes) is an important key to showing understanding through personal processing.

For teachers the most opportune moments to offer guidance to students is in formative feedback - steering a learner into the right direction before a high stakes outcome. This might be as comments in Google Docs or writing in additional comments in the margins of a student’s work as it is being drafted.

Some practical tips:

Use digital tools like annotation apps.
Incorporate peer review of notes.
Create a bingo board of reflective prompts
Keep a daily learning log
Include ‘today’s focus’ in learning reflections
Record, log and celebrate failures
Summarise content with quick bullet lists
Encourage a personal vernacular of comment codes
Model ‘scribble-thinking’ with note-taking
Draw diagrams
Model questioning and active reading
Peer-review - use margin notes as discussion prompts for collaborative clarifying activities

Notes in the margin help students to:

Clarify understanding

Record reflections

Ask questions

Justify thinking

Show resilience

Provide evidence of decision-making

Record a range of feedback

Create refined outcomes

Personalise learning

Strengthen metacognition

Take, Shake, Make Away

Using notes in the margin and focusing on reflective note making as a key part of assessment design can counteract plagiarism and AI misuse by emphasising originality and personal voice.

How might you incorporate a learning journal, process log or process over product component to assessment design?

And for your final notes (I will be using this activity to foster discussion about assessments this week;)

What is your big take away from this text?

What could you shake up as a result of reading this text?

What gaps might you make up as a result?

Thanks for reading the results of this morning scribbled notes.

Please leave a comment to share how you have shifted your assessment practice to process over product.

Finding your position on AI in education

OpenAI has recently produced a course called ‘Chat GPT Foundations for Educators’ which is designed to be a silver bullet to teach educators how to use AI. The course is the product of a partnership with Common Sense Media which is (usually) a reliable source of ‘common sense’ reviews. What they seem to be missing is how teachers can use AI effectively and purposefully. They are not really encouraging teachers to be co-designers, critical evaluators and engineers of content.

It basically falls short of practical (and not contradictory) use case scenarios and has omitted a lot of big picture questioning about the ‘why’ behind the use of AI. The current debate appears to be an assumption that teachers should choose between AI or the highway. But maybe this yes/no binary thinking is the real problem.

AI shouldn’t be an ‘all in’ or ‘all out’ or Yes/No debate. It is much more complicated than that.

If there were a fork in the road that was ‘AI or the highway’, choosing the highway (non AI) is (still) just fine. If you haven’t read about the OpenAI foundation course you can find a useful critique of it here: How does OpenAI Imagine K-12 Education by Erik Salvaggio.

Here are some of the key points of critique:

it assumes that teachers are passive producers of content
it posits that productivity is more important than effective pedagogy
it does not teach critical AI literacy
it does not target pedagogy
it is not a best practice example of UDL in action (no closed captioning)
it assumes that administrative tasks can all be automated
it does not seem to value the agency of teacher-owned creative processes in course design
it overstates the predictive capabilities of AI
and my addition:
it assumes that teachers need to be ‘all or nothing’ consumers

OpenAI seems to champion itself as a heroic solution to all of the problems that teachers have. It does not really dig into any additional problems that using AI blindly also produce.

If you stand with AI - then you obviously must use it for everything and save so much time and create so many more resources and power up your productivity to the point that even writing your own meeting agenda can be outsourced. But - quantity does not beat quality. And producing does not equate to creating.

When I was at Elam School of Fine Arts, my professor said to me (when I was churning out bad art at a rate of knots): ‘There’s enough sh*t in the world. Why contribute to it?” And I think this is golden advice that can be applied to finding your own position on AI in education.

An easy ‘out’ is to stand on the opposite road with those who say No. You might stand in solidarity with teachers who see AI as a flash in the pan that is best avoided. These teachers might be summed up as the ‘pen and paper warriors’ who want to make sure that text books are used instead of laptops. If you avoid technology, then you also do avoid a lot of the ‘bad’ things - but you also run the risk of stealing learning opportunities away from students who also need to learn critical AI literacy. Teachers have a duty to empower students to understand, question, and navigate AI responsibly. This isn't just about using the tools to enhance their own productivity but helping students to critique and control their own uses to be critical creators of the future.

If you want to start using AI in the classroom it is ok to do so cautiously. In fact, it is best to use any tool with your pedagogue hat on and ask all of the questions like ‘where is the science’, ‘how does this enhance learner experience’, ‘how does this increase critical thinking’, ‘how might this offer more agency’, ‘how might this remove barriers to learning’ etc. And if it doesn’t align to your lens of what education should be and needs to be in the future, then don’t use it. Or more simply put, if you are adding to the sh*t in the world, don’t.

AI, when used purposefully, has the power to enhance, augment and improve learning - but you have to become an active architect of learning and do so.

So what next? Thinking and Linking:

Prioritise Critical Literacy: Read up on AI’s limitations, biases, and ethical implications. Foster a culture of inquiry rather than blind adoption. Read widely or at least dip your toes in: 12 Best Blogs on AI
Focus on Inclusivity: Accessibility should be a baseline, not an afterthought. All training materials must meet diverse needs to ensure equitable learning and expand rather than restrict learning accessibility. Use AI to expand not restrict.
Balance Efficiency with Depth: Productivity should not come at the expense of the thoughtful, creative processes integral to teaching. AI should enhance, not overshadow, pedagogical engagement.
Collaborate and Innovate: Join a community of practice to join in the critical conversation (this AI Forum is really worthwhile. It has fortnightly recorded webinars and emailed transcripts for an easy win for those of us who might be time poor). Even if you don’t join a community of practice, you might share innovations, successes, and challenges with AI in education with your colleagues in-house.
Critique your Use: Think about process over product, learner agency and the experience for the learners above all. How is augmenting and enhancing learner experience? How is it supporting more critical thinking? Ask ethical questions: How does this tool support diverse learners in my classroom? What biases might the AI outputs carry, and how can I address them? Are the benefits worth the potential trade-offs in creativity or critical thinking? My work-in-progress rubric is below.
Become an engineer not a consumer: There are SO MANY new AI tools on the market right now with Chat GPT being just one drop in a vast ocean. Popular educational solutions like MagicSchool.AI can create educational consumables in seconds, but the outputs might not be of true benefit to students’ experience. Consider how you might engineer your own more purposeful solutions rather than accepting ready-made products that might push passivity or feed another tech company’s coffers.
Explore Innovation: For some interesting use cases for how to innovate with AI in the classroom check out Harvards’s AI Pedagogy Project (this was also mentioned in the first blog link).
Put Pedagogy over Product: AI tools are only as effective as the intentionality behind their use. Targeting strategies like flipped classrooms, differentiation, UDL or gamified learning means that you can apply AI to pedagogical frameworks purposefully.

Ai in the classroom rubric for self assessment level 1 to 4 work in progress by katrina ward — I created this rubric (work in progress) based on the ITL Microsoft Partners in learning rubrics. There are more categories in the rubric - but this is the first page as an example.

AI might not be a silver bullet or a magic solution, but neither is it a storm to be feared.

It’s not really an “AI or the highway” scenario, forcing a binary choice of ‘this or that.’ AI is simply a tool, and like any tool, its value lies entirely in how we use it. By asking critical questions, exploring practical use cases, and fostering collaboration, we can move beyond the ‘yes or no’ debate. Instead, we can become thoughtful, critical users who forge our own purposeful path forward—together.

I added this as a provocation - does the SAMR rubric work when considering AI? SAMR rubric by Puentedura adapted for AI use.

Thoughts? Questions? Leave a comment to share your thoughts.

AI and Policy: A FLOW Guide

If you want to keep up with AI, you can’t. At least that’s what it feels like. That is the truth I’ve been struggling to come to grips with as I navigate the ethics of AI use in classrooms and workplaces and observe the exponential growth of AI tools for teachers and workers. There are new developments every second. And then there are considerations so far beyond the basics of intellectual property and data sharing… so let’s get stuck in. Read on to learn about some key considerations for policy writing as well as A FLOW model for testing and reflecting once it is written.

I recently presented a workshop on AI tools in the classroom grounded with a whakatauki as well as a metaphor. I used the ocean as a metaphor because, even if we feel well-informed at the moment, it is more than likely that we’re just paddling in the breakers because the flow on effects of our use of AI is vast and deep - like an ocean. It is a wicked problem.

My choice of whakatauki is also fitting - Kia mate ururoa, kei mate wheke - to fight like a shark rather than give in like an octopus. My challenge to all users of AI is to consider the why before diving right on in. Resist the status quo and resist doing something just because it is easier. Consider the repercussions and thrash about before you make a decision. Thrash to push for better learning experiences. Thrash for better pedagogy and androgogy. Thrash to strive for a better learning experience for all learners - and don’t accept the models that are just because they are. Just because it might be fast, doesn’t mean it is good.

So many AI tools packaged for educational purposes sadly perpetuate 20th Century knowledge models and do not ‘push the envelope’. My hope is that, with more knowledge of how AI models are programmed and more knowledge of biases and preferences as well as the ‘why of AI’, that those who work in education and training will work harder to make AI do something more responsible. ethical and transformative. Potentially writing useful policy is the first step in designing clear guidelines.

What should you include in an AI policy?

AI is evolving so rapidly that it is important for schools and workplaces to ride the wave. We need to be informed about which AI tools are fit for purpose and need to be able to approve specific tools, outcomes and systems. For this, we need to have clear objectives about when the use of AI is appropriate and be able to give recommendations for how and why information can be appropriately shared.

At this stage, it is useful to consider some user stories of when and how AI might be used and also to explore scenarios with a ‘black hat’ in order to consider the long term implications.

Set boundaries and design systems:

What boundaries need to be put in place about data sharing? (No names, no confidential information, no data shared without permission)

What are the expectations of the institution or organisation? (AI can be used for ideation assistance or proof-reading but not for any published content)

Who are the people who might oversee governance of AI? (And how might it be monitored?)

Consider the legal implications:

What disclosure regulations need to be in place for data sharing?

How can you safeguard against discrimination and bias?

What are the internal processes for data breaches?

Who is liable for data breaches or authenticity queries?

What industry-specific regulations can you draw on?

What are the terms of the AI tool/s that is/are being used?

How is intellectual property safe-guarded?

What are your internal systems for governance and monitoring?

What happens if there is a breach?

Managing Risk:

What permissions and guidelines need to be established to indicate which tools are approved and how they are used?

What risk assessments need to be undertaken against specific scenarios?

What are the regulations against outputs? Must they be reviewed by humans before publication?

How will issues or incidents be documented and reviewed?

Ethics:

AI does not come without an environmental footprint - how might you mitigate your use of AI against your Sustainable Development Goals?

How can you monitor your increased environmental impact?

How might you offset your carbon footprint?

How might you make users more aware of both technical and environmental considerations?

How might you ensure the privacy of information shared?

Training:

A lot of organisations are presenting AI tools as if they are a quick win without unpacking legal, ethical and environmental considerations. How might you ensure that staff are informed and able to make informed decisions about whether their use of AI is appropriate, necessary or effective?

A FLOW model:

The following acronym could be useful for beginning your deep dive into AI.

A - Anticipate - explore some user stories or scenarios to predict different uses of AI without guidance. Use these scenarios to design policy and training to meet the needs of your participants.

F - Facilitate - facilitate a training session on the responsible and ethical uses of AI and design a workplace scenario for a test/launch activity.

L - Launch - provide a tool and some prompts and a desired output that relates to your context for employees to explore.

O - Observe - look for anomalies in the uses of AI and adapt policy accordingly. Allow questioning and exploration alongside staff as they navigate ‘the deep’.

W - Weigh - consider how effective parameters and policy are and consider the success of input vs output in terms of how the tools were used and what the outcomes were.

Repeat with a new cycle to iteratively design a flexing policy that is capable of riding the AI wave.

So what do you think? Writing AI policy and using AI is about so much more than time saving. We need to consider legal implication of data sharing and collection, governance and guidelines about purpose vs product, environmental implications, intellectual property considerations, disclosure regulations, risk assessments, best practice evolutions and more.

Some additional thinking prompts:

How can we recognise and address bias in LLM training?

How can we push for more inclusive data sets for training?

What are our processes for consent?

What might our incident protocols be if the use of AI leads to negative outcomes?

Who should be involved in feedback loops about the use of AI?

How can AI be used to ensure equitable outcomes?

I recently read that creating an AI generated image uses the same amount of energy as charging a cell phone. This made me second-guess my use of AI as the carbon footprint aspect had not been front and centre for me - and knowing this has changed my usage as I want to be a more conscious consumer and my values align strongly with sustainability and the SDGs.

The key takeaway is that we need to be critical and aware of our use of AI so that we can actively contribute to a culture of proactive accountability and sustainability.

What do you think? Did I leave anything out?

References: Create your AI Policy, Clayden Law, e-book, 2024.

Visual Learning and Metaphor in the Classroom

This term I’ve been playing with visual learning and metaphor as a way to anchor students’ understanding about a new Achievement Standard in English (1.2 - Demonstrate understanding of specific aspects of studied texts). After exploring and explaining a ‘boat and anchor’ metaphor in class with quick sketches on the whiteboard, I took the time to draw it up as a published whiteboard on Canva so that students could ‘connect the dots’ and revise the key requirements of the task more easily.

Breaking things down into pictures is a way to reduce cognitive load and is also a way for students to connect with their learning beyond written instructions. Using images to support learning is a way to offer both scaffolding as well as differentiated learning opportunities. Using pictures to support words (or visuals to work alongside verbals) aligns with Dual Coding Theory which you can read more about here. The main principle is that retention and memory is enhanced by offering pictures as well as words. Applying a UDL lens, pictographic representations are also useful supports for students with dyslexia, dyscalculia and autism and can make learning more ‘universally’ engaging.

Application of metaphor

The boat metaphor I used in this instance was a way to discuss the importance of tying an observation about aspects of a text to the author’s purpose, to the theme and to draw attention to the fact that the ‘treasure’ of this learning is exploring a personal response. This was a useful mataphor because it helped students to understand that naming a technique and giving an example of it is like pushing a boat out onto the water - it will float away if it is not anchored to anything. The examples need to be linked together (like a chain), the boat needs to be anchored to the author’s purpose (why is it there in the first place) - but also that the ‘real treasure’ is our own responses and thinking about the ideas or themes in the text.

I used the metaphor of a boat and anchor ‘chain’ as a way to explain that examples need to be linked together for their writing to be convincing. If students zoom into the chain, they can see that it is also likened to a venn diagram in order to show diagrammatically that the connection between aspects and how they work together is where the magic happens. By recreating the anchor metaphor in Canva, I was also able to add explainer post its at each section of the image for students to zoom in and out to - depending on how much support they needed. In this way the visual whiteboard works as a differentiated learning tool too.

VIsual learning is away to present complex information in a more memorable way. My interest has been in whether or not this way of presenting learning is ‘actually helpful’ or if it is a waste of time. As it turns out, verbal feedback from the students indicates that it ‘is really helpful’ and I have noticed that they are able to talk about ‘anchoring’ their ideas to the author’s purpose. It also has served as a way for students to know that the ‘treasure’ is the most important part and that they need to explore different ways of connecting to a text in order to have a justified personal response. From a numbers standpoint, when I look at ‘click through’ analytics or observe how many students are ‘in the board’ each lesson (and out of class time), this has been a quick indication that presenting learning visually is something that the students are keen to engage with.

Targeting asynchronous delivery

I ended up extending the whiteboard canvas in Canva to summarise the other key documents that are already loaded to the Learning Management System. Where information was new, I added a ‘NEW’ sticker and drew their attention to it in class and on the class stream (live feed) to ensure that students who had been away would not miss the notification. I also screenshot the board and reposted it to the stream to indicate ‘where’ on the map there might be updates to check out. The benefit of the visual map as a way to present learning is that the students can ‘explore’ all of the resources in one place and have a better understanding of how they fit together through the process of exploration (active learning) and they also don’t need a tab open for every document.

Addressing Challenges with Google Classroom

Google Classroom can be a frustrating conduit for learning..There is limited functionality as far as how resources can be presented to students. The list view has limited iconographic or colour-coding functionality and I am constantly guiding students how to find things even when there are clear titles because the headings alone are what distinguishes one resources from another. Students seem to waste so much time clicking in and out and around to find documents. By presenting hyperlinks to the key resources within the Canva whiteboard, I am able to streamline the ‘purpose’ of each doc with explainer notes. Similarly, students can ‘see’ what they are about to click on before they click into it.

A major benefit of visual learning is how complex information can be presented in a more memorable way. Finding a metaphor and using visual aid is a useful way to present multiple steps or share pieces of a bigger project. Using a whiteboard is also an engaging way for students to zoom in and review/pick a path and explore class materials as well as supporting information or explanatory notes without needing multiple tabs open to organise their exploration.

Visual learning and using visual aids can also make it easier for students to process and remember information. Additionally, the use of metaphor can also improve memory retention so that students can visually re-trace connections by remembering parts of an image. Further, presenting material visually and/or with metaphor is a more inclusive way to present information because it can so easily include iconographic supports.

Trials and Tweaks

If I were to use this particular canvas again, I might make it more linear rather than ‘scattered’ or I might potentially number sections or use more arrows to indicate flow and progressions. In this instance and as an initial experiment, this map was built alongside students and added to incrementally to build on synchronous and collaborative learning in class. As a tool, the students were already familiar with the boat/anchor metaphor so the board served them like a revision tool. If it were a stand-alone tool that I needed students to explore on their own, I might need to scaffold the pathways a bit more clearly.

Canva whiteboards are a fun way to present a lot of information in a visual way. An important note is that this visual learning/mapping tool is presented ‘as well as’ the list view within Google Classroom rather than ‘instead of’. It is also an optional way to explore materials and is not a ‘must’ for students who prefer more traditional delivery methodology.

Miro is another great whiteboard tool with a few more embed functions that Canva hasn’t got yet (although it needs a paid account). As a note, my Canva account is an education account and the hyperlinking of docs is a workaround to try to get some of the functionality of the Miro ‘embed PDF’ option that I like. (Just as an FYI). I have found that you can embed video and powerpoints/slideshows relatively easily within Canva too.

And that’s my picture.

What do you think? How might you use more visual learning tools or metaphors in the classroom?

Hold please, caller. What real learning looks like.

Noisy classroom. Kids out of seats. Animated conversations. Kids drawing on whiteboards. Kids exploding out into the hall. So loud! Enough!

But wait.

Take a closer look: students are discussing measurement, others are tinkering with motors to prototype a powered hat design, someone is researching portable solar panels, someone else is designing in Tinkercad and there are drawings and diagrams and things being tweaked and thought about everywhere you look.

I always look forward to this bit. This is the bit when you see that learners have 'earned their stripes as learners’ and that they know how to learn. They are finding things out, they are tinkering, they are thinking, they are wondering out loud and they are problem-solving.

The launching pad for this was a ‘think tank’ unit exploring the history of Aotearoa’s taonga, early trade and enterprise, the history of New Zealand inventors and entrepreneurs, critical analysis of Shark Tank pitches and exploration of the United Nations’ Sustainable Development Goals. Now it is the students’ turn to come up with something useful, something that services a need, something that targets a sustainable development goal, and something that they can pitch to (albeit pretend) ‘sharks’. They have two weeks to work through the empathising, defining, ideating, designing, prototyping and testing phases.

Design Thinking is a process that opens up so much potential for students. When explored thoroughly, the empathy stage opens up problems to solve that were there all along. The ‘goldilocks’ card sheds real light on problems (see my emptahy deck). We can walk in someone else’s shoes and really think and feel what they are thinking and feeling - and as a consequence, we can design new and improved solutions to actually make the world better.

Maybe it is this part that is the most rewarding - the idea that we can make the world better. The actual asking of ‘how can we make the world better?’ and the actual belief that ‘we can make the world better.’ But actually, this part IS so rewarding. I can stand back and watch, observe the noise and the ‘real and beautiful chaos of learning’ and see that they are all immersed in their learning. The noise is the good kind.

“It is such a loud class today,” said one student. “I know,” I replied. “Because look, everyone is into it.”

So, when at first glance it looks like ‘all noise and boisterousness’ and something that needs to be controlled, stopped or silenced - look closer. Hold please, caller. Don’t step in and stop it. Embrace it. It is what learning looks like.

Top Tip - Secret teacher affirmation stash ideas

Sometimes you have days where the kids are scratchy, everyone is tired, no one wants to go to school/work, the spoon drawer is low, the plan didn’t work, your coffee got cold before you got around to drinking it and you forgot your lunch. It’s never one thing…

On those days, it’s handy to have a pick-me-up in your back pocket.

For me it is a bookmark.

Secretly and stealthily hiding in my book is a ‘Stay Weird’ affirmation postcard. I think I got it in a package when I ordered a custom vintage plate with a crow on it for my wall once. It is a picture of a girl with a face hugger on her face. It makes me laugh and reminds me to be myself. I don’t do what I do to fit in. I’m not afraid to stand out. I’m not afraid to stand up.

There are loads of people out there who will have the same humour as you do. And whatever it is, embrace it.

Keep doing what you do. Every drop in the bucket is still a drop in the bucket.

Some other fun places to hide your ‘keep your chin up’ affirmations are:

Your login password
Your screensaver
Your email signature (depending on where you work and what it is)
The dashboard of your car
Your desk
Your pen
Your pencil
The bathroom
The mirror
Your phone wallpaper

Stay weird.