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Share feelings in a safe and fun way. Quick team check-ins that start your meeting in the right mood.

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Data talks are short 5-10 minute classroom discussions to help students develop data literacy. This pedagogical strategy is similar in structure to a number talk, but instead of numbers students are shown a data visual and asked what interests them. In a data talk the teacher does not have to be an…

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Lesson Plan: How Do Recommendation Systems Work’

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Lesson Plan: How Do Recommendation Systems Work’

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Lesson Plan: How Do Recommendation Systems Work

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Gathering data for data.pumice.si activities

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Gathering data for data.pumice.si activities

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Book Recommendations - Collaborative Google Sheet

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Book Recommendations - Collaborative Google Sheet

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Please add to this if you wish to survey children's favourite reads

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Data Talk: Price of Eggs (NY Times) Miriam

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Data Talk: Price of Eggs (NY Times) Miriam

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What’s Going On in This Graph? | Price of Eggs

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The DALI4US project, which stands for "Data Literacy for Upper Primary Schools," is an Erasmus+ funded project aimed at equipping primary school students and educators with essential data literacy skills. The project is using the OrangeEDU platform, along with curated teaching and learning materials and a professional training programme to equip primary school teachers with the essential confidence, knowledge, skills, and attitudes needed to effectively teach data literacy. As part of this, DALI4US is developing and implementing a data literacy framework that integrates into the primary education curriculum across several European countries including Slovenia, Luxembourg, and Ireland.

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DALI4US - Data literacy for upper primary education

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The DALI4US project, which stands for "Data Literacy for Upper Primary Schools," is an Erasmus+ funded project aimed at equipping primary school students and educators with essential data literacy skills. The project is using the OrangeEDU platform, along with curated teaching and learning materials and a professional training programme to equip primary school teachers with the essential confidence, knowledge, skills, and attitudes needed to effectively teach data literacy.

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Arnold, P., & Franklin, C. (2021). What Makes a Good Statistical Question?. Journal of Statistics and Data Science Education, 29(1), 122-130.

Bargagliotti, A., Franklin, C., Arnold, P., Gould, R., Johnson, S., Perez, L., & Spangler, D., (2020). Pre-K - 12 Guidelines for Assessment and Instruction in Statistics Education II (GAISE II): A Framework for Statistics and Data Science Education. Retrieved from: https://www.amstat.org/asa/files/pdfs/GAISE/GAISEIIPreK-12_Full.pdf

K-12 Computer Science Framework Steering Committee. (2016). K-12 Computer Science Framework. ACM. Retrieved from: https://k12cs.org/

Seehorn, D., & Clayborn, L. (2017, March). CSTA K-12 CS Standards for All. In Proceedings of the 2017 ACM SIGCSE Technical Symposium on Computer Science Education (pp. 730-730).

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Arnold, P., & Franklin, C. (2021). What Makes a Good Statistical Question?. Journal of Statistics and Data Science Education, 29(1), 122-130. Bargagliotti, A., Franklin, C., Arnold, P., Gould, R., Johnson, S., Perez, L., & Spangler, D., (2020). Pre-K - 12 Guidelines for Assessment and Instruction in Statistics Education II (GAISE II): A Framework for Statistics and Data Science Education.

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Over 60 New York Times Graphs for Students to Analyze (Published 2020)

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A collection of graphs, maps and charts organized by topic and graph type from three years of “What’s Going On in This Graph?”

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Over 75 New York Times Graphs for Students to Analyze

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A new collection of graphs, maps and charts organized by topic and type from our “What’s Going On in This Graph?” feature.

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This AI Hub provides information and resources on artificial intelligence and how it can benefit and support users, as well the current limitations and concerns about its use.

What is Artificial Intelligence?

Artificial Intelligence (AI) refers to the development of computer systems that can perform tasks that typically require human intelligence. It involves creating algorithms - a list of rules or steps - that are used by computers to analyse, understand, and respond to information.

While AI systems can process and analyse large amounts of data to recognise patterns and make predictions, they are not able to think and understand context like humans can.

AI has been around since the 1950s and has evolved over the decades, but has seen rapid and significant progress in recent years.

What is the impact?

AI has been an established part of day-to-day tasks for some time. Virtual assistants like Siri, Alexa, and Google Assistant use AI to understand and respond to our voice commands; AI algorithms power recommendation systems on platforms like Netflix, Amazon, and YouTube; Social media platforms use AI algorithms to curate your newsfeed, showing you content based on your interests, engagement, and connections; and mapping systems like Google Maps use AI to provide real time traffic updates.

AI is evolving quickly, with new advancements and applications being developed that have the potential to impact on our lives. This brings opportunities, but also concerns about how to safely and ethically navigate the online world.

AI in Education

Artificial Intelligence systems and tools are already part of our everyday lives. As AI continues to evolve, it is important to be aware of the benefits and the risks it can have in teaching and learning.

This technology has the potential to transform education, so it is important for educators and students to understand how to ethically, critically and positively engage with AI in order to make the most of its potential. It's important to note that AI can compliment, but not replace a teachers' expertise. The human element a teacher brings to the classroom will still be crucial to fostering meaningful learning experiences.

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This AI Hub provides information and resources on artificial intelligence, its benefits, as well the current limitations and concerns.

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Hans Rosling's 200 Countries, 200 Years, 4 Minutes - The Joy of Stats - BBC Four

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At some point in the past few years, humanity collided with a new kind of intelligence. And things are getting strange. People are being accused of crimes by algorithms; falling in love with digital beings; pioneering new ways to fight old diseases; turning to machines for comfort in their worst moments, and using artificial intelligence to commit - and hide from - terrible crimes.

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Seeing the Invisible Using Data Sets - interact with data sculptures on 4 invisible environmental issues.

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Seeing the Invisible Using Data Sets - interact with data sculptures on 4 invisible environmental issues.

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Seeing the Invisible - Google Arts & Culture

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In collaboration with the World Health Organization and artist Cristina Tarquini, interact with data sculptures on 4 invisible environmental issues.

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MRI OF THE EARTH by Refik Anadol Studio and Variable in collaboration with Google Arts & Culture

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Julius is a powerful AI data analyst that helps you analyze and visualize your data. Chat with your data, create graphs, build forecasting models, and more.

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Clarifications

The 18,062 ideas were collected between July and November 2021.

Including age/county information during submission of ideas was optional, as a result over 11,000 submissions did not have either element.

The thematic categories were assigned retrospectively after the expert analysis was complete to facilitate public use of the data.

Some submissions have been edited to remove clear grammatical errors and any offensive language.

The Creating Our Future campaign does not endorse any of the views, research proposals or commercial endeavours highlighted within submissions.

Links to external websites and papers were included within some submissions. The campaign is not responsible for the status of those links.

Identifiable information has been removed to ensure GDPR compliance.

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I shared my idea for #CreatingOurFuture on creatingourfuture.ie

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Creating Our Future is an invitation to everyone to tell us what researchers in Ireland can do to create a better future

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I shared my idea for #CreatingOurFuture on creatingourfuture.ie

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Creating Our Future is an invitation to everyone to tell us what researchers in Ireland can do to create a better future

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In this section there are many free downloadable resources containing a variety of classroom activities available.

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For a more powerful place name search, and to find all the recorded occupants who lived in a particular place, use the Griffith’s Names search option.

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Classroom screen has a poll facility which is very useful for quickly gathering data

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Getting some people together? Visual tools can enable you to think from a different angle. We’ve created a bunch of remixable artwork which can come in useful for ice-breakers, event registration, and badge pressing.

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What words or statements come to mind when you think of data science?

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What words or statements come to mind when you think of data science?

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What difficulties do pupils encounter when analysing data?

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What difficulties do pupils encounter when analysing data?

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Student see it as maths based topics

Clarity interpreting data

Standard unit of measurement

Different styles of presentation

Presentation of data

Interpretation of numerical data

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What challenges do you encounter when teaching data?

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What challenges do you encounter when teaching data?

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One standalone chapter not revisited again

Resources

Time - too much time on drawing graphs versus understanding

Teacher data literacy

Teacher confidence and competence

Variety of graphs

Focus on the mathematics as opposed to the data

To make it more interesting

Disconnect with wider curriculum and world

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Does your school currently teach data skills to prepare students for the words they live in?

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Does your school currently teach data skills to prepare students for the words they live in?

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Procedural

Maths orientated

Simple datasets

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What role does data literacy play in students ability to critically analyse information from social media/news sources?

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What role does data literacy play in students ability to critically analyse information from social media/news sources?

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Identify fake news

Make properly informed choices

Makes them conscious consumers

Enable them to be critical of information targeted at them

Using multiple sources to collect data to inform opinion

Fake news

Real live versus staged live

Improving data literacy can provide students with the language and interpretation tool to engage critically with what is presented to them online in particular

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What implication does data have on your pupils life currently/in the future?

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What implication does data have on your pupils life currently/in the future?

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Over exposure online leaving them vulnerable online

Digital footprint

Many are over sharing their personal data online without being aware of it

Preventing data breaches

Child safety

Future job prospects

Pupil safety and what they are sharing

Pupils need to consider their future status when providing information online, healthy awareness of this is essential

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How could improve in data literacy impact students confidence and understanding real-world issues like climate change or public health?

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How could improve in data literacy impact students confidence and understanding real-world issues like climate change or public health?

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Identify misinformation

Build confidence to make decisions about the impact of their daily actions

Be critical of the data source (is a biased)

- leading questions

- implications as a result

Showing direct impact - power cuts on their lives - energy usage - how can data help us to cut down!

Build skills to critically analyse the data they are saying

Enabling pupils with the experience in using and interpreting data enables them to analyse real world issues through critical lens

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How do I think differently about the concepts now?

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How do I think differently about the concepts now?

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There is a place for creativity.

The value of data in our lives.

Data as a commodity.

Have visual representations.

Using data in a cross-curricular manner.

Enabling critical thinking for my pupils.

Data across the curriculum, not just maths

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Data can tell a story

Dear Data a narrative way of teaching data

Creativity and data

Dear Data

Need to allow children to produce visual representations.

More open to different uses of data - for the pupils rather than the teacher using it as an assessment tool

Use in more subjects,

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What learning can we take back to school?

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What learning can we take back to school?

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Integrating Data across the curriculum away from maths.

Use Moodclap and Moodfirst in class.

Use data in more subjects.

Data is more than drawing lovely graphs!

Morning meeting: NY Times, Data talk

NY Times

Data Talk

Dear Data

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Thought provoking course that makes you really think about data, how it is being used and how we can analyse it.

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Very collaborative and teamwork feel between tutors and participants.

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Very collaborative and teamwork feel between tutors and participants.

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Dear Data or using a visual bar chart to tell a story to inform a topic or perhaps a stem research project for a class.

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We need to think more like the children and not adults and how we want data to be represented. Let it serve a purpose.

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I really liked the opening with moodfirst.ai, together with the examination of data across the curriculum.

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in a few clicks thanks to our intuitive interface. Do you need inspiration? Explore the 21 question types (QCM, Word Cloud, etc.) and their templates in the examples gallery.

💡Provide a seamless experience for your audience by integrating the questions into your Powerpoint or Google Slide presentation.

Create interactive presentations

Interact face-to-face or remotely

with your audience. Wherever they are, your learners connect via a smartphone or computer.

💡To keep your audience's attention, display your slides on the participants' screen in real time.

Interact face-to-face or remotely

Measure the understanding

of your audience in real time and after the course. Use our data analysis page to identify the most challenging questions and track the progress of each participant.

💡Download post-course reports for detailed answers that will enhance your next interactive presentation.

Measure the understanding

Reinforce learning

through neuroeducation. Our applications are designed around Stanislas Dehaene's 4 pillars of learning: attention, active engagement, feedback on mistakes, and consolidation.

Reinforce learning

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Create Interactive Presentations with Wooclap and engage Your Audience

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Engage your audience with Wooclap's interactive presentation tool. Create dynamic and engaging presentations that keep your audience hooked. Try Wooclap today and take your presentations to the next level.

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Wordwall - Create better lessons quicker

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Need a fresh teaching resource that fits your class and teaching style? Create a customized pack of interactive and printable activities in just one minute.

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Dot-voting (also known as dotmocracy or voting with dots) is an established facilitation method used to describe voting with dot stickers or marks with a marker pen.

In dot-voting participants vote on their chosen options using a limited number of stickers or marks with pens - dot stickers being the most common. This sticker voting approach is a form of cumulative voting.

Process specifics

The dot-voting process includes the following steps:

Participants are each given a set number of dot stickers (as decided by the facilitator)

They place dot stickers next to options presented that they like (they may place any number of their dots on any number of the options)

Options with the most dots at the end of voting "win"

Variations include:

using different colour dots to signify different values, e.g. green for "like" and red for "dislike".

using different colour dots for different types of participants e.g. blue for management and red for staff.

The origins of dot-voting are unclear. Professional facilitators have been said to use it since the 1980s.

Dot-voting is now widely used for making quick collaborative decisions by teams adopting agile and lean methodologies. For example, it's one of the methods endorsed by the 18F digital services agency of the United States' General Services Administration, and it's part of the Design Sprint methodology.

Dot-voting is a quick and simple method for prioritize a long list of options.

It's less cognitively demanding than having to perform a full ranking of all the options, because participants are not required to give a comparative judgment of each option, and it allows participants to express a preference for more than one option at the same time.

It leverages the collective wisdom of the team, and provides an equal way for all the voices on the team to be heard and have accountability in prioritizing key issues.

It also creates a sense of engagement and allows participants to see the decision process in action and understand how the final choice was made.

Dot-voting has been criticized for limiting creativity and diversity of ideas, and giving confusing or false results. Dot-voting is like a one question multiple-choice survey done with stickers.

Participants are expected to review, consider and compare all options before sticking their dots. As a result, too many options can be overwhelming ( overchoice aka choice overload) and thus facilitators are encouraged to amalgamate and generalize unique ideas into broader and less specific concepts.

New options cannot be added once dotting has started, as this would not be fair to the new additions.

Similar or related options are penalized, as these can cause vote-splitting.

Participants can easily cheat by adding extra dots, peeling off dots or moving dots.

Often people will simply add their dots where everyone else has dotted, without considering their own opinion on all the options, thus an example of the Bandwagon effect.

It is also impossible to tell if a result represents broad popularity (because many people gave one dot), or an enthusiastic minority (where a few people gave many dots).

Overall all results are not reliable.

Better than Sticker Voting

If you want to use a much more reliable and empowering tool to help large groups find agreement, (and is still have fun without going digital) checkout Feedback Frames.

Here is how they work...

Order your set today at FeedbackFrames.com

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Dot-voting (also known as dotmocracy or voting with dots) is an established facilitation method used to describe voting with dot stickers or marks with a marker pen. In dot-voting participants vote on their chosen options using a limited number of stickers or marks with pens - dot stickers being the most common.

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Meet the new AI that knows you better than you know yourself

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Train a computer to recognize your own images, sounds, & poses. A fast, easy way to create machine learning models for your sites, apps, and more - no expertise or coding required.

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Webwise Parents Hub

The Webwise Parents Hub is the key internet safety online access point for parents in Ireland. It provides free advice, information, and resources to ensure that your child makes the most of their time online. Get advice from experts in parenting, education, technology and psychology, access Explainer Guides to popular apps and platforms, How To Guides, downloadable resources, and much more.

This guide gives parents support, advice and information to help their children have a positive experience online. Topics explored in the guide include cyberbullying, screen time, sexting, social media and online pornography.

#TalkListenLearn

The #TalkListenLearn campaign supports children and parents/guardians online.
Having regular open conversations is one of the most effective ways of supporting your child online. The #TalkListenLearn campaign has a range of free resources and advice to support families, and you can start the chat using our Topic Generator!

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Internet Safety Resources: Get free lessons on cyberbullying

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Webwise teaching resources help young people learn how to use new media in a safe and positive way. Topics covered include privacy and cyberbullying.

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‘Big data’ has transformed the economy we live in. Over the last few decades, it’s become far cheaper to collect and store, and much more valuable to own and use. It’s now overtaken oil to become the most valuable resource in the world.

For more information and lessons go to: https://www.webwise.ie/connected/

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Oide Technology in Education guidance on Artificial Intelligence / AI for primary and post primary schools.

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This AI Hub provides information and resources on artificial intelligence and how it can benefit and support users, as well the current limitations and concerns about its use.

What is Artificial Intelligence?

Artificial Intelligence (AI) refers to the development of computer systems that can perform tasks that typically require human intelligence. It involves creating algorithms - a list of rules or steps - that are used by computers to analyse, understand, and respond to information.

While AI systems can process and analyse large amounts of data to recognise patterns and make predictions, they are not able to think and understand context like humans can.

AI has been around since the 1950s and has evolved over the decades, but has seen rapid and significant progress in recent years.

What is the impact?

AI has been an established part of day-to-day tasks for some time. Virtual assistants like Siri, Alexa, and Google Assistant use AI to understand and respond to our voice commands; AI algorithms power recommendation systems on platforms like Netflix, Amazon, and YouTube; Social media platforms use AI algorithms to curate your newsfeed, showing you content based on your interests, engagement, and connections; and mapping systems like Google Maps use AI to provide real time traffic updates.

AI is evolving quickly, with new advancements and applications being developed that have the potential to impact on our lives. This brings opportunities, but also concerns about how to safely and ethically navigate the online world.

AI in Education

Artificial Intelligence systems and tools are already part of our everyday lives. As AI continues to evolve, it is important to be aware of the benefits and the risks it can have in teaching and learning.

This technology has the potential to transform education, so it is important for educators and students to understand how to ethically, critically and positively engage with AI in order to make the most of its potential. It's important to note that AI can compliment, but not replace a teachers' expertise. The human element a teacher brings to the classroom will still be crucial to fostering meaningful learning experiences.

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This AI Hub provides information and resources on artificial intelligence, its benefits, as well the current limitations and concerns.

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Nov 08, 2023

Circumvent the limitations of second-hand data portals: Orange with Dask enables you to process big data sets while ensuring the source's authenticity and enabling custom workflows.

Oct 28, 2023

An experimental version of Orange supports much larger data sets. It never loads the whole data set into the working memory; data is only processed in small chunks. We show a case study on a 13 GB spectroscopy data set.

Oct 24, 2023

Preparing large HDF5 datasets that load into Orange as on-disk data.

Oct 20, 2023

Highlighting our papers from the International Conference on Discovery Science

Visual Programming

Interactive data exploration for rapid qualitative analysis with clean visualizations. Graphic user interface allows you to focus on exploratory data analysis instead of coding, while clever defaults make fast prototyping of a data analysis workflow extremely easy. Place widgets on the canvas, connect them, load your datasets and harvest the insight!
Learn more Watch video

Interactive Data Visualization

Perform simple data analysis with clever data visualization. Explore statistical distributions, box plots and scatter plots, or dive deeper with decision trees, hierarchical clustering, heatmaps, MDS and linear projections. Even your multidimensional data can become sensible in 2D, especially with clever attribute ranking and selections.
Learn more

Add-ons Extend Functionality

Use various add-ons available within Orange to mine data from external data sources, perform natural language processing and text mining, conduct network analysis, infer frequent itemset and do association rules mining. Additionally, bioinformaticians and molecular biologists can use Orange to rank genes by their differential expression and perform enrichment analysis. Check out also Orange cousins Single Cell and Quasar.
Watch video

Orange users

When teaching data mining, we like to illustrate rather than only explain. And Orange is great at that. Used at schools, universities and in professional training courses across the world, Orange supports hands-on training and visual illustrations of concepts from data science. There are even widgets that were especially designed for teaching.
Learn more

My laboratory produces large amounts of data from RNA-seq, ChIP-seq and genome resequencing experiments. Orange allows me to analyze my data even though I don't know how to program. It also allows me to communicate with my collaborators, who are experts in data mining, and with my colleagues and trainees.

Gad Shaulsky, Ph.D.
Molecular biologist and Director of Graduate Studies (Baylor College of Medicine, Houston, USA)

The scientific community is in need of tools that allow easy construction of workflows and visualizations and are capable of analyzing large amounts of data. Orange is a powerful platform to perform data analysis and visualization, see data flow and become more productive. It provides a clean, open source platform and the possibility to add further functionality for all fields of science.

Ferenc Borondics, Ph.D.
Principal beamline scientist at SMIS (SOLEIL synchrotron, France)

I teach Orange workshops monthly to a diverse audience, from undergrad students to expert researchers. Orange is very intuitive, and, by the end of the workshop, the participants are able to perform complex data visualization and basic machine learning analyses. Most of our attendees have been able to incorporate this tool in their research practice.

Francesca Vitali, Ph.D.
Research Assistant Professor (Center for Biomedical Informatics & Biostatistics, The University of Arizona)

Contribute to Orange

If you love using Orange and want to support us, a donation would be very much appreciated. The funds help us fix bugs, implement new features, provide free educational content, and maintain computational infrastructure.

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I was chatting with my class about where I was yesterday and organically through the discussion the issue of going to sleep at night came up as a class issue when we were discussing the fitbit sleeptrack function. We have decided to do a science experiment in Jan '25 to track if going to sleep improves by adopting the use of sleep meditation at bedtime.

They were so excited by this and even suggested using a pie chart through use of percentages which they have not even been taught yet!!

It was such a healthy conversation between them all as it turns out all of them find it very hard to go to bed at night. One of them even said finally I might have a solution!!! Anyway, below is the letter I have just sent to parents with all the details and a sleep tracker template if any of this is relevant to you and your class! I put in the connections to some of the different curriculum areas also.

Thanks,

Ger

Project Timeline and Approach:

Baseline Data Collection

The first two weeks of January (Monday, January 8th – Sunday, January 21st) will involve tracking students’ sleep habits without using any sleep meditation.

Students will record:

The time they go to bed.

The approximate time they fall asleep.

Any wake-ups during the night (optional).

The time they wake up.

Sleep Meditation Experiment

The next two weeks (Monday, January 22nd – Sunday, February 4th), students will listen to a guided sleep meditation before bed and track the same data.

Analysis and Findings

After collecting data for both periods, we will analyze and compare results in class to determine if sleep meditation has made a measurable difference.

How You Can Help: I would ask for your support in helping your child track their sleep data during both phases of this project. If listening to a sleep meditation does not suit your household, that is perfectly fine. Your child can still participate by analyzing data from classmates who used the meditation.

Curriculum Connections: This project aligns with several key areas of the 5th Class curriculum, including:

Maths: Data collection, creating and interpreting graphs (e.g., bar charts, pie charts), and analyzing trends.

Science: Formulating questions, conducting an investigation, recording results, and reflecting on findings.

SPHE (Social, Personal, and Health Education): Exploring the importance of sleep, mindfulness, and self-care.

Participation Notes: Participation in data collection is entirely voluntary. Students only need to submit their results if it is appropriate for your household. However, all students will still participate in data analysis and representation using class data.

Sleep Tracker Instructions: Your child will bring home a Sleep Tracker Sheet to record observations for both the baseline and experiment phases. Please encourage your child to:

1. Note the time they go to bed.

2. Estimate how long it takes to fall asleep.

3. Record any wake-ups (optional).

4. Write down the time they wake up.

Thank you for supporting this exciting and practical project. If you have any questions or concerns, please don’t hesitate to contact me. We look forward to seeing what insights the students uncover!

Kind regards,
Ms Kelly

Sleep Tracker Sheet

Name: ___________________________

DateTime to BedApprox. Time AsleepWake-ups? (Optional)Wake-up TimeMonday    Tuesday    Wednesday    Thursday    Friday    Saturday    Sunday

Notes:

Baseline (January 8th–21st): No sleep meditation.

Experiment (January 22nd–February 4th): Listen to a sleep meditation before bed.

Thank you for helping to make this a meaningful and engaging learning experience!

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Data Exploration Session in Ireland: Teachers Explore Recommendation Systems with Orange – DALI4US

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After exploratory experimentation sessions with teachers in Slovenia and Luxembourg, the first days of December were reserved for a session with Irish teachers.

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The lesson introduces the workings of a simple machine learning algorithm and model. For older students, it can serve as preparation for Identifying Quadrilaterals; in this case, do not skip the explanation of the tree-building algorithm (see Conclusion). The computer-based part can be omitted if desired, but it doesn’t take much time or require extensive knowledge of artificial intelligence from the teacher.

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Code.org lesson training a AI Model - classification

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Code.org lesson training a AI Model - classification

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Anyone can learn computer science. Make games, apps and art with code.

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Training AI #2 | How AI Makes Decisions - Code.org

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Anyone can learn computer science. Make games, apps and art with code.

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An educational tool for teaching kids about machine learning, by letting them train a computer to recognise text, pictures, numbers, or sounds, and then make things with it in tools like Scratch.

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Machine Learning for Kids — Decision Trees

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In the world of machine learning, decision trees are commonly used for classification/ regression analysis. Help make decisions easier with decision trees.

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The lesson is part of mathematics: students review how to recognize different types of quadrilaterals and their properties.

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van Hiele Model of Geometric Thinking | kidsmathtalk

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While there is no specific grade level attachment to the van Hiele model of Geometric Thinking, when thinking about the Common Core State Standards, achieving Level 2: Informal Deduction, is an excellent goal for the end of 5th grade.

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The development of spatial and geometric thinking: The Importance of Instruction | NRICH

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This article provides some answers to these questions by looking at levels of geometric thinking and the types of activities required to develop this thinking.

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Include questions about animals (frog, hedgehog, fish)Besides quadrilaterals, there are images of fish, frogs and hedgehogs that can be used to teach about redundant information. Include them if you intend to cover this topic.

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Several things happen in this activity. Students

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This activity can be used for rounding up the learning about animal groups (vertebrates, invertebrates, amphibians, reptiles, birds, fish etc.), as it gives students a thourough review of the characteristics of individual groups of animals as well as those of individual animals (Are dolphins fish? Do penguins have fur?).

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Make a Guess Who Game - Data Education in Schools

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Using the well known children’s game to help us think about data, categorisation and pattern matching.

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Teach Data Literacy: a guide for primary teachers

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Teach Data Literacy: a guide for primary teachers

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https://dataschools.education/teachdata/

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The analysis of the data of the votes for Eurovision would be interesting for children and could tie in with something like the Blue Flag Programme.

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Eurovision 2025 Results: Voting & Points

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Eurovision 2025 results: All the voting and points from the Eurovision Song Contest 2025 in Basel. Austria won with the song “Wasted Love” by JJ with 436 points