On October 19th 2023 I had an excellent opportunity to talk with experts from different AI areas with different perspectives and points of view and exchange ideas with them as a part of the Council of Europe EduTalk@Council of Europe series. Let me share with you their one-sentence wrap-up (and the rest of the talk you’ll have to watch by yourself 🙂

🏵 Arjana Blazic: Embrace AI, never stop learning and remember to always use your professional judgement and expertise.

🌳 Christian M. Stracke: Please use them and use them carefully and think always about your pupils.

🌴 Francisco Bellas: Use AI to think with you not to think instead of you.

🌷 And mine would be: Think before you click. (I like being a moderator on my topics, so much to learn and share)

Thank the Council of Europe team for their time and support Ahmet Murat KILIÇ Arzu Burcu Tuner and Maria Benedita Santos Silva

The recording is available on CoE website, alongside announcements of next EduTalks and other news.

🎙️ I just wrapped up two insightful sessions at the EDUtech Europe conference in Amsterdam, where I talked about the intersection of AI and education, focusing on some, for me, important aspects.  🤖📚

🌟 Safeguarding Well-being and Mental Health with AI 🌟

Do students understand that at the other end, there are not humans but machines? How do you find the balance between AI magic and AI errors without developing dependence or addiction? In this age of rapid technological advancement, we must strike a balance between the benefits of AI in education and the potential risks it poses to the mental and emotional health of learners and teachers.

💡 Existing Frameworks for AI Regulation in Education 💡

We also discussed the existing frameworks and guidelines that provide much-needed support for AI in the education sector. As a leader of the European Digital Education Hub’s “AI in Education” squad, I proudly talked about our Briefing reports that cover different aspects of AI in Education such as teachers’ AI competences, supporting teachers for the AI age, AI curriculum development, ethical and governance considerations, and impact of AI on assessment, feedback and personalisation.

🤖👩‍🏫 What will we outsource to AI, and what will we keep to ourselves, human teachers?  🤖👩‍🏫

One of the most thought-provoking questions we explored was the balance between AI and human teachers. What aspects of education should we outsource (or offload) to AI, and what should remain in the capable hands of human educators? Which activity is worth our time and effort? Do our students deserve personal feedback from teachers? Or are we heading towards a scenario where AI creates tasks, students use AI to answer them, and teachers use AI to grade those answers?

🌐 Getting the Best from AI While Protecting Privacy and Humanity 🌐

Ultimately, our discussion revolved around the central question: How can we harness the full potential of AI in education without compromising privacy, the essence of humanity, the teaching profession, or the quality of education itself? It’s a complex challenge, but by fostering dialogue and collaboration, we can navigate this ever-evolving landscape successfully.

😍 I want to thank my fellow panellists for their interesting perspectives and the opportunities to learn from their experiences Laura Knight Tamara Ciobanu Timothy Kelley Botond Pakucs Darren Neethling Kearon McNicol

👏 A special thank you goes to Human Power, who made EDUtech Europe happen Alessandro Bilotta & Shamala Gowri Anbalaghan you are stars ✨

Let’s continue to work together to shape a future where we put the well-being of our students and the quality of education at the forefront.

#EDUtechEurope #AIinEducation #FutureofLearning #Privacy #WellBeing #AIinTeaching #AIEd

Watch webinar recording

I was honoured with the opportunity to present my reactions to the UNESCO Guidance on generative AI in education and research during the launch as part of the Digital Learning Week in Paris. Let me share with you some of my words. 💬

This is not AI generated feedback on the Guidance 😁 I read Guidance by myself and commented by myself because this Guidance deserves my time and effort.

🐾The same is with our teaching and learning – our students deserve our time, our expertise, compassion and support. We shouldn’t outsource teaching to AI. We should not get enfeebled or deskilled by the AI. Otherwise our years of expertise are wasted on prompting.

🤡 We should be honest with our students, our colleagues how we are using AI and why. If we can’t say why – we are already making mistakes!

The Guidance follows UNESCO path for #TechOnOurTerms helping us to answer questions Why tech, What we are aiming for…

⚖️ UNESCO Guidance pointed to important aspect of creating balance between regulation and promotion of generative AI, importance of age limit ( I would add age verification too). Importance of monitoring and validation, especially pedagogical validation, testing locally and building evidence. We had the opportunity to see some examples of how partnerships between researchers, government and education could answer those challenges. We know that those are complex issues, but this is not an excuse for not doing it!

🏋️‍♀️Unburdening teachers, solving teacher’s problems are some of the buzzwords we hear as promises of EdGPT – but how do they know what teachers really need? Do they have teachers in teams, have teachers been asked – or is this one more “big thing” dumped on the teacher’s shoulders?

The Guidance correctly put more responsibility for GenAI on the providers and institutions not individual teachers.

🎨In the chapters about facilitating creative use of GenAI, the Guidance present excellent examples, among which I suggest automated feedback and assessment should be added (Do we know how students react to AI feedback? Do our students know that we use AI to write feedback for them?)

🌌 The Guidance on generative AI in education and research finish with ideas about GenAI and Future of Education. 🌑 My comment was that one of the possible futures is with a human teacher available only for the rich while the rest of us are stuck with an artificial teacher. I hope that this Guidance and our collaborative effort will steer us away from that version of the Future of Education.

🎉 Thank you Fengchun Miao for the invitation and opportunity to contribute to DLW. Looking forward to the implementation of the Guidance.

✒️ Now is you turn! Read the Guidance (or ask some AI tool to read it for you 🤓) and do your best to create better future of education.

Recording of the panel

EDEH Squad “AI in Education” learning journey

Nowadays, we are overwhelmed with news about artificial intelligence, its impact on our work and daily lives, and its potential benefits and threats. What impact does AI have on education? How can we employ it for good and avoid negative influence?

Artificial intelligence (AI) refers to computer systems that, given a set of human-defined objectives, can influence real or virtual environments through predictions, recommendations, or decisions. AI systems interact with us and have direct or indirect effects on our environment. Often, they appear to operate autonomously and can adapt their behaviour by acquiring knowledge about the context. (UNICEF, 2021)

Connections between AI and education are multiple, AI has the potential to support education by providing personalized and adaptive learning experiences to students, automating administrative tasks, analysing large amounts of education data, to identify patterns and trends that can inform decision-making. AI role in Education is usually described as teaching or learning with AI, about AI and for AI. While only a small percentage of a population of learners may wish or be required to learn about AI in order to become AI designers or developers, the suggestion is that all citizens should be encouraged and supported to attain a certain level of AI literacy. (CoE, 2022)

As AI systems continue to evolve and data usage rises, it is of the utmost importance to develop a better comprehension of their impact on the world, especially in education.  Educators and school leaders must have a fundamental understanding of artificial intelligence and data usage in order to interact positively, critically, and ethically with this technology and to maximise its potential. (EC, 2022)

But often we are facing some common misconceptions about AI, including that it is too difficult to comprehend the functionality of AI systems, that AI systems cannot be trusted, that AI has no place in education, or that AI will undermine the teacher’s role. Rather than replacing teachers, AI can support teachers, enabling them to construct learning experiences that empower students to be creative, to think, to solve real-world problems, to collaborate effectively, and to engage in activities that AI systems cannot do on their own. (EC, 2022)

Some of already existing examples of the AI use in education are:

• Tutoring system – the learner follows a step-by-step sequence of tasks through conversation.
• Teaching assistants – AI recommendation engines are used to recommend specific learning activities or resources based on each student’s preferences, progress and needs.
• Formative assessment – Learners are provided with regular automatic feedback.

However, it is important to note that the use of AI in education also raises ethical concerns, such as privacy and security issues, potential biases in algorithms, and the potential for automation to replace human teachers and staff. Therefore, it is important to ensure that AI is used in a responsible and ethical manner in educational settings.

In February 2023, European Digital Education Hub Squad “AI in Education” is founded in response to recent AI-related developments. From February until the end of June 2023, the “AI in Education” Squad worked intensively to discuss various aspects of AI use and its impact on Education. The result of these discussions is the creation of seven briefing reports.

As a leader of the European Digital Education Hub’s “AI in Education” squad I would like to assist you in discovering the benefits and risks of AI and learning about AI to be able to teach with AI. Please review Squad’s briefing reports, which cover topics such as teachers’ AI competences, supporting teachers for the AI age, AI curriculum development, and ethical and governance considerations; and join us on this learning journey.
Briefing reports by AI in Education EDEH Squad:

1. Teachers’ competences
2. How to support teachers to use AI in teaching
3. Use scenarios & practical examples of AI use in education
4. Education about AI
5. Influence of AI on governance in education
6. AI and Ethics, human rights, law, education data
7. Teaching with AI – assessment, feedback and personalisation

I would like to thank to all Squad members who contributed to these reports: Riina Vuorikari, Jessica Niewint-Gori, Dara Cassidy, Francisco Bellas, Madhumalti Sharma, Ari Laitala, Cristina Obae, Yann-Aël Le Borgne, Anne Gilleran, Petra Bevek, Oksana Pasichnyk, Elise Rondin, Johanna Gröpler, Gordana Janakievska, Bertine van Deyzen, Martina Weber, Robbe Wulgaert, Alexa Joyce and Lidija Kralj; supported by Leon Koch

Briefing report No. 7
by the European Digital Education Hub’s squad on artificial intelligence in education Authors: Jessica Niewint-Gori, Dara Cassidy, Riina Vourikari, Francisco Bellas, Lidija Kralj.

The focus of this report is to explore the potential of a number of related areas in the domain of teaching with artificial intelligence (AI) – assessment, feedback and personalisation. It builds on the previous briefing reports, each of which have explored different facets of the use of AI in education. One of the most touted benefits of AI for education is the potential it offers for personalisation – the delivery of education
interventions that are tailored to the specific needs of individual learners. This may be manifest in a variety of ways, including via adaptive learning and intelligent tutoring systems. At the core of this capacity is the ability to assess a learner’s mastery of a particular concept, identify gaps in knowledge or areas for improvement, and deliver feedback or resources to address that gap (Phillips et al, 2020). The ability to
harness AI to create high quality assessments, feedback and tailored resources has the potential to deliver benefits for individual students, teachers, education institutions, and society as a whole.

In considering this potential, it is important to consider education in all its complexity and be mindful of the potential risks as well as the benefits. As detailed in briefing report 5: The Influence of AI on Governance in Education, the draft EU Artificial Intelligence Act proposes a risk-based approach to AI focused on four risk levels: unacceptable, high, limited, and minimal. Throughout this report, we aim to draw attention to the
potential for risk as we explore how AI’s capacity for personalisation might deliver benefits at many levels (learner, teacher, institution, using the same distinction as the Wayne Holmes et al, 2022 report) of the education system and ultimately at the broader societal level.

…

Briefing report ends with Recommendations by the Squad

AI holds great promise for enhancing education, but it should be implemented responsibly to ensure the protection of students’ rights and interests. Proper checks and balances, transparency, and human oversight are key to mitigating the potential risks associated with AI in education. AI should be used to complement and enhance existing pedagogical practices rather than replace them. AI algorithms, especially in education, should be designed to produce understandable and interpretable outcomes. Explainable AI aims to make AI decision-making processes transparent to understand how the system arrived at its conclusions, which is particularly crucial in areas like assessment. Despite the use of AI for automating various processes, human oversight should still be a significant part of the system. Educators should have the final say in grading or making decisions that significantly affect students’ academic standing. AI systems must respect and protect the privacy of the students. Data handling procedures should comply with privacy laws and regulations, ensuring the confidentiality and security of sensitive student information. Biases can influence the fairness of the system and have serious implications for all stakeholders in education, so efforts should be made to identify and mitigate biases in AI algorithms. Also, if the system fails or produces erroneous results, there should be mechanisms in place to identify the cause of the issue and rectify it. To ensure the accuracy of the performance of AI systems, they should be regularly monitored and evaluated to identify and address any
emerging issues promptly and to help to ensure fairness and effectiveness.

Read whole report No. 7 “Teaching with AI – Assessment, Feedback and Personalisation” and find all other briefing reports by European Digital Education Hub’s squad on artificial intelligence in education in the post “Learning journey for, about, and with AI“.
We also invite you to join the European Digital Education Hub.

Briefing report No. 6
by the European Digital Education Hub’s squad on artificial intelligence in education Authors: Elise Rondin, Francisco Bellas, Martina Weber, Petra Bevek, Bertine van Deyzen, Jessica Niewint-Gori, Cristina Obae, Anne Gilleran and Lidija Kralj.

The issues linked to ethics of AI, the right to privacy, data protection, gender inequality or human rights, are also present in the education sector, where the population is often more vulnerable, notably due to a young age and a lack of understanding. Therefore, it is highly important to put in place and implement legal safeguards and technical norms for the ethical use of AI in education, to ensure that its use does not violate rights of students, teachers and other people in the educational sphere. If this duty must be mainly the responsibility of the states, other actors, including schools, teachers as well as tech companies have an important role to play. Ensuring that students are aware of these issues is also important for them to understand how AI systems work and what their risks are.

…

Briefing report ends with Recommendations by the Squad

Caution should be a keyword at every level in using AI in education. Students need to be taught their rights and how to protect themselves, teachers need to be cognisant of the range of information collected in the AI tools they use, developers need to guard against undue influence and be aware of potential bias, and finally governmental bodies need to take a firm position with robust legislations to protect their citizens while excising a rigorous approach to their own use of AI in data collection.
In general, we recommend the following learning goals related to AI literacy and ethics:

• Identify and analyse the ethical and environmental opportunities and threats
  arising from the everyday use of AI.
• Promote a safe, responsible and conscious use of digital tools and technologies
  related to AI.
• Analyse and understand the human footprint and the influence of risks in automated decision-making processes.
• Identify and evaluate the ethical and policy implications of the design and use of AI systems, including fairness, bias, discrimination and accountability.
• Critically analyse the potential of AI to improve peoples’ quality of life, assessing
  its operability in different social, economic and cultural contexts.
• Know and understand the risks and benefits of AI in different areas, such as health, security and privacy.

Read whole report No. 6 “AI and Ethics, Human Rights, Law and Educational Data” and find all other briefing reports by European Digital Education Hub’s squad on artificial intelligence in education in the post “Learning journey for, about, and with AI“.
We also invite you to join the European Digital Education Hub.

Briefing report No. 5
by the European Digital Education Hub’s squad on artificial intelligence in education Authors: Gordana Janakievska, Riina Vuorikari, Yann-Aël Le Borgne, Martina Weber, Cristina Obae, Jessica Niewint-Gori, Anne Gilleran and Lidija Kralj.

Education governance refers to how decision making happens in education systems and how education systems allocate roles and responsibilities, determine priorities and designs, and carry out education policies and programmes (OECD, 2019). From an education governance point of view, it is increasingly important to explore and discuss the possibilities, risks and limits of artificial intelligence (AI) in education. Observing
the institutionalisation of new education governance practices that emerge as a result of the integration of digital technologies into education is necessary in order to share best practices and gain knowledge. To discuss these new governance practices, the UNESCO guidance for policy makers for AI in education and European Parliament proposal of AI Act (adopted text, June 2023) are taken into consideration.
A number of AI tools for educational purposes are already in use (see Briefing report No.3 “Use Scenarios and practical examples of AI use in Education”). Many positive examples for effective use start to emerge, however, there are also many concerns for responsible adoption, such as the lack of strategies to specify measures that are conducive to effective use of AI for educational purposes. There is a need for establishing an integrated education governance package for AI that encompasses educational reform, ensuring inclusive, equitable and ethical use of AI. Policies and strategies for using AI in education are central to maximising AI’s benefits and mitigating its potential risks as a new tool to accelerate the progress towards the achievement
of the UN’s sustainable development goal 4 (SDG 4) – Ensure inclusive and equitable quality education and promote lifelong learning opportunities for all.

…

Briefing report ends with Recommendations by the Squad

With AI and the associated data, new norms and new governance models emerge, and new actors enter the education sector while others lose their value in the system. Although national authorities are reacting quickly establishing or improving their AI strategies, it is difficult at the moment to have a clear picture of what this virtual AI-based ecosystem will look like, what governance it will have, and what actors will be involved, but four common areas of concern emerge from the national and regional policies:

• the importance of governance for data and privacy;
• the importance of openness to ensure equal universal access and promote
  transparency;
• curriculum innovation that can address the potential and implications of AI;
• financial support for the effective implementation of AI.

The primary purpose of applying AI in education should be to enhance learning, enabling every learner to develop their individual potential, and policies should reflect and support it. A comprehensive AI strategy is recommended covering interdisciplinarity, humanity, ethics, scalability and sustainability, responsibility, equity and lifelong learning for all.

Read whole report No. 5 “Influence of AI on Governance in Education” and find all other briefing reports by European Digital Education Hub’s squad on artificial intelligence in education in the post “Learning journey for, about, and with AI“.
We also invite you to join the European Digital Education Hub.

Briefing report No. 4
by the European Digital Education Hub’s squad on artificial intelligence in education Authors: Cristina Obae, Jessica Niewint-Gori, Francisco Bellas, Oksana Pasichnyk,  Gordana Janakievska, Anne Gilleran, Yann-Aël Le Borgne, Riina Vuorikari, Madhumalti Sharma and Lidija Kralj

Tekst na hrvatskom je dostupan niže.

Artificial intelligence education is a highly active field, with new resources and tools arising continuously. In previous briefing reports, you may have read about teaching for, with, and about AI, supporting teachers, and identifying the necessary competences for them to become fluent in emerging technologies. With all these dynamic changes, this briefing report aims to highlight the importance of integrating AI literacy into both existing and new curricula. Our focus will be on providing valuable ideas and concrete examples for effectively incorporating AI education.

This is why the current document proposes some examples of different countries’ approaches on education about AI. As you will see below, some countries have chosen to develop new curricula, while others integrated AI into their existing ones.

… short summary
Belgium
Although AI competences are briefly mentioned in the new curricula, there is little detail provided regarding what should be taught to students. A few Belgian organisations, mostly from the non-formal education sector, are starting to implement drafts of AI curricula aimed at primary and secondary schools.
Ireland
Using the Digital Strategy document as a basis, some curriculum work has been done in the past year to develop pupils’ understanding of AI.
Italy
Civic education was introduced for all school grades in 2020/2021 and the lesson time could be used to teach transdisciplinary topics like in this case AI skills, focusing on ethical, societal and political aspects of AI.
Spain
The new education law in Spain includes contents of AI at different levels, from primary school to high school, mainly related to technology subjects.
Ukraine
A working group comprising school and university teachers, along with IT professionals, was able to suggest AI-oriented content that could be covered in approximately 10 hours of class time. The content is designed to provide a general introduction to the topic of AI, rather than focusing on specific technologies or in-depth understanding.

…

Briefing report ends with Recommendations by the Squad

• To ensure a comprehensive and unbiased approach to learning, it is essential that AI curricula are not tied to specific technologies or brands.
• With the aim of facilitating the development of the European Education Area, it would be beneficial if Member States shared good practice examples, thereby ensuring that students entering tertiary education possess comparable levels of competence about AI.
• Integrating AI into curricula requires both resource development and teacher training.
• The evidence-based approach would enhance the content and effectiveness of AI curriculum.
• Education about AI is needed, but freely embracing education with AI needs to be done with some caution.

Read whole report No. 1 “Education about AI” and find all other briefing reports by European Digital Education Hub’s squad on artificial intelligence in education in the post “Learning journey for, about, and with AI“.
We also invite you to join the European Digital Education Hub.

Obrazovanje o umjetnoj inteligenciji (UI)

Pregledno izvješće br. 4 stručne skupine za umjetnu inteligenciju u obrazovanju Europske platforme za digitalno obrazovanje.  

Autori: Cristina Obae, Jessica Niewint-Gori, Francisco Bellas, Oksana Pasichnyk,  Gordana Janakievska, Anne Gilleran, Yann-Aël Le Borgne, Riina Vuorikari, Madhumalti Sharma i Lidija Kralj

Obrazovanje o umjetnoj inteligenciji vrlo je aktivno područje s novim resursima i alatima koji se neprestano pojavljuju. U prethodnim preglednim izvješćima mogli ste čitati o poučavanju za, s i o AI, podršci učiteljima i identificiranju potrebnih učiteljskih kompetencija za razumijevanje novih tehnologija. Sa svim ovim dinamičnim promjenama, ovo pregledno izvješće ističe važnost integracije pismenosti o umjetnoj inteligenciji u postojeće i nove kurikulume. Fokus je na prezentiranju vrijednih ideja i konkretnih primjera za učinkovito uključivanje obrazovanja o umjetnoj inteligenciji.

Zbog toga u ovom dokument predstavljamo neke primjere pristupa obrazovanja o umjetnoj inteligenciji različitih zemalja. Kao što ćete vidjeti u nastavku, neke su zemlje odlučile razviti nove kurikulume, dok su druge integrirale UI u postojeće.

… kratki sažetak

Belgija
Iako se kompetencije o umjetnoj inteligenciji ukratko spominju u novim kurikulumima, postoji malo detalja o tome što bi trebalo poučavati učenike. Nekoliko belgijskih organizacija, uglavnom iz sektora neformalnog obrazovanja, počinje provoditi nacrte kurikuluma o umjetnoj inteligenciji u osnovnim i srednjim školama.

Irska
Zasnovano na irskoj Digitalnoj strategiji, u protekloj godini napravljene su određene promjene kurikuluma kako bi učenici razvili razumijevanje umjetne inteligencije.

Italija
Građansko obrazovanje uvedeno je za sve razrede 2020./2021., pa se nastavno vrijeme tog predmeta može iskoristiti za poučavanje interdisciplinarnih tema kao što su, u ovom slučaju, vještine umjetne inteligencije, s fokusom na etičke, društvene i političke aspekte umjetne inteligencije.

Španjolska
Novi zakon o obrazovanju u Španjolskoj uključuje sadržaje o umjetnoj inteligenciji na različitim razinama, od osnovne do srednje škole, uglavnom vezano uz tehničke nastavne predmete.

Ukrajina
Radna skupina sastavljena od školskih i sveučilišnih nastavnika, zajedno s IT stručnjacima, uspjela je predložiti sadržaje usmjerene na UI koji bi se mogli pokriti u približno 10 sati nastave. Sadržaj je osmišljen tako da pruži opći uvod u temu umjetne inteligencije, bez fokusiranja na specifične tehnologije ili dubinsko razumijevanje.

…

Pregledno izvješće završava Preporukama stručne skupine

• Kako bi se osigurao sveobuhvatan i nepristran pristup učenju, bitno je da kurikulumi o umjetnoj inteligenciji nisu vezani za određene tehnologije ili tvrtke.
• S ciljem olakšavanja razvoja Europskog obrazovnog prostora, bilo bi korisno kada bi države članice razmjenjivale primjere dobre prakse, čime bi se osiguralo da učenici koji ulaze u tercijarno obrazovanje posjeduju usporedive razine kompetencija o umjetnoj inteligenciji.
• Integracija poučavanja o UI u kurikulume zahtijeva razvoj resursa i edukaciju učitelja.
• Pristup temeljen na dokazima poboljšao bi sadržaj i učinkovitost kurikuluma o umjetnoj inteligenciji.
• Obrazovanje o umjetnoj inteligenciji je potrebno, ali ga je potrebno oprezno pripremiti i primijeniti.

Pročitajte cijelo pregledno izvješće br. 4 “Obrazovanje o umjetnoj inteligenciji” i pronađite sva ostala izvješća stručne skupine za umjetnu inteligenciju u obrazovanju Europske platforme za digitalno obrazovanje u objavi “Learning journey for, about, and with AI“.
Također vas pozivamo da se pridružite Europskoj platformi za digitalno obrazovanje.

Briefing report No. 3
by the European Digital Education Hub’s squad on artificial intelligence in education Authors: Dara Cassidy, Yann-Aël Le Borgne, Francisco Bellas, Riina Vuorikari, Elise Rondin, Madhumalti Sharma, Jessica Niewint-Gori, Johanna Gröpler, Anne Gilleran and Lidija Kralj.

Tekst na hrvatskom je dostupan niže.

This report presents a set of use scenarios based on existing resources that teachers can use as inspiration to create their own, with the aim of introducing artificial   intelligence (AI) at different pre-university levels, and with different goals. The Artificial Intelligence Education field (AIEd) is very active, with new resources and tools arising continuously. Those included in this document have already been tested with students and selected by experts in the field, but they must be taken just as practical examples to guide and inspire teachers’ creativity.
The use scenarios have been organised in three main categories, according to the three main approaches followed in AIEd: Teaching for AI, Teaching about AI and Teaching with AI.
Teaching for AI implies training students in all the AI topics from an AI user perspective, rather than an AI developer perspective, which will be covered in the Teaching about AI section. We could differentiate these two perspectives with the following key ideas:

• In terms of curriculum, teaching about AI should be included as specific subjects or courses (or part of them) with a detailed program covering the main AI topics (perception, actuation, reasoning, representation, learning, impact, etc.). The learning outcomes are more technical and specific, so before learning about AI, students should receive background training in maths, programming, and other technical knowledge required to properly understand the AI topics from a developer perspective. Teaching for AI could be organised in a more transversal manner through embedding it in different courses and areas (e.g., language, history, natural sciences, mathematics, arts). The learning material could be organised as small activities within different subjects (not only technical), or as specific subjects where the AI topics are delivered without relying on deep technical aspects (like programming). Learning for AI does not require a specific background in maths or programming.
• In terms of methodology, in teaching about AI, students develop simple AI-based solutions by programming them, while in teaching for AI, they can focus on analysing existing AI-based applications or tools by using them, understanding the way they work and their impact.
• In terms of specialisation, teaching for AI is necessary for all students, independently of their area (humanities, science, engineering, arts). Teaching about AI could be targeted to technical paths, thinking about those students interested in working as “AI engineers”. Hence, teaching for AI is a pre-requisite for educators and learners before moving to teaching about AI.

The following 3 sections of briefing report contain selected use scenarios in these categories that exemplify their differences and opportunities at classes.
…

Briefing report ends with Recommendations by the Squad

It can be observed that our main recommendation places Teaching for AI is on the top,
representing the idea that it should be a pre-requisite for the other two.

• Focus first on teaching for AI by means of practical projects and learning scenarios that provide activities for teachers to engage students in activities that improve knowledge, skills, and attitudes towards how AI systems are used in today’s society and focus on everyday application that are driven by AI.
• Take advantage of existing resources for teaching with AI to enhance teaching and learning. It is essential to know how to select tools that align with the curriculum, pedagogical goals, and students’ requirements, while considering the efficacy, ease of use, and privacy issues associated with these tools.
• Apply a developer approach when teaching about AI to train more specialised students in the fundamental areas of real-world AI, like perception, reasoning, representation or learning. They must face different AI challenges through hands-on and programming projects, so they attain the AI basics from a more technical perspective.

Read whole report No. 3 “Use Scenarios & Practical Examples of AI Use in Education” and find all other briefing reports by European Digital Education Hub’s squad on artificial intelligence in education in the post “Learning journey for, about, and with AI“.
We also invite you to join the European Digital Education Hub.

Scenariji i praktični primjeri upotrebe umjetne inteligencije u obrazovanju
Pregledno izvješće br. 3 stručne skupine za umjetnu inteligenciju u obrazovanju Europske platforme za digitalno obrazovanje.  

Autori: Dara Cassidy, Yann-Aël Le Borgne, Francisco Bellas, Riina Vuorikari, Elise Rondin, Madhumalti Sharma, Jessica Niewint-Gori, Johanna Gröpler, Anne Gilleran and Lidija Kralj.

U ovom preglednom izvješću predstavljamo skup scenarija korištenja na temelju postojećih resursa koje učitelji mogu koristiti kao inspiraciju za stvaranje vlastitih scenarija, s ciljem uvođenja umjetne inteligencije (UI) na različite osnovno i srednjoškolske razine te s različitim ciljevima. Područje primjene umjetne inteligencije u obrazovanju (AIEd) vrlo je aktivno pa novi sadržaji i alati nastaju kontinuirano. Sadržaje koje predstavljamo u ovom dokumentu već su testirani s učenicima i odabrani od strane stručnjaka u tom području, ali i dalje su samo praktični primjeri koji mogu nadahnuti vašu kreativnost.
Scenariji upotrebe organizirani su u tri glavne kategorije, prema tri glavna pristupa AIEd: Teaching for AI, Teaching about AI i Teaching with AI (Poučavanje za , i s umjetnom inteligencijom).
Poučavanje za umjetnu inteligenciju podrazumijeva obrazovanje učenika u svim temama umjetne inteligencije iz perspektive korisnika umjetne inteligencije, a ne perspektive stvaratelja aplikacija umjetne inteligencije, koju opisujemo u odjeljku Poučavanje o umjetnoj inteligenciji. Ove dvije perspektive možemo razlikovati po sljedećim ključnim idejama:

• Što se tiče kurikuluma, poučavanje o umjetnoj inteligenciji trebalo bi biti uključeno kao posebni predmeti ili tečajevi (ili njihovi dijelovi) s detaljnim programom koji pokriva glavne teme umjetne inteligencije (percepcija, aktivacija, rezoniranje, predstavljanje, učenje, utjecaj itd.). Ishodi učenja su više tehnički i specifični, tako da bi prije učenja o umjetnoj inteligenciji, učenici trebali dobiti temeljno obrazovanje iz matematike, programiranja i drugog tehničkog znanja potrebnog za pravilno razumijevanje tema umjetne inteligencije iz perspektive programera. Poučavanje za umjetnu inteligenciju moglo bi se organizirati na transverzalniji način ugradnjom u različite tečajeve i područja (npr. jezik, povijest, prirodne znanosti, matematika, umjetnost). Materijal za učenje može se organizirati kao male aktivnosti unutar različitih predmeta (ne samo tehničkih) ili kao specifični predmeti gdje se teme umjetne inteligencije predaju bez ulaženja u dublje tehničke aspekte (poput programiranja). Učenje za UI ne zahtijeva posebno znanje iz matematike ili programiranja.
• Što se tiče metodologije, u poučavanju o umjetnoj inteligenciji učenici razvijaju jednostavna rješenja temeljena na umjetnoj inteligenciji programirajući ih, dok se u poučavanju za umjetnu inteligenciju mogu usredotočiti na analizu postojećih aplikacija ili alata temeljenih na umjetnoj inteligenciji, koristeći ih, razumijevati načine na koji rade i njihov utjecaj.
• Što se tiče specijalizacije, poučavanje za umjetnu inteligenciju potrebno je svim učenicima, neovisno o njihovom području (humanističke znanosti, prirodne znanost, inženjerstvo, umjetnost). Poučavanje o umjetnoj inteligenciji moglo bi se uključiti u tehničke smjerove, imajući na umu učenike zainteresirane da postanu “inženjeri umjetne inteligencije”. Stoga je poučavanje o umjetnoj inteligenciji preduvjet za učitelje i učenike prije nego što prijeđu na poučavanje o UI.

Sljedeća 3 odjeljka preglednog izvještaja sadrže odabrane scenarije korištenja u ovim kategorijama pokazujući njihove razlike i mogućnosti u nastavi.

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Pregledno izvješće završava Preporukama stručne skupine

Možete uočiti da naša glavna preporuka stavlja poučavanje za AU na vrh, predstavljajući ideju da bi to trebalo biti preduvjet za druge dvije kategorije.

• Najprije se usredotočite na poučavanje za umjetnu inteligenciju kroz praktične projekte i scenarije poučavanja koji predlažu aktivnosti za uključivanje učenika u aktivnosti koje poboljšavaju znanje, vještine i stavove o tome kako se sustavi umjetne inteligencije koriste u današnjem društvu i usredotočuju se na svakodnevne primjere primjene umjetne inteligencije.
• Iskoristite postojeće sadržaje za poučavanje s UI kako biste poboljšali poučavanje i učenje. Ključno je znati kako odabrati alate koji su u skladu s kurikulumom, pedagoškim ciljevima i mogućnostima učenika, uzimajući u obzir učinkovitost, jednostavnost korištenja i zaštitu privatnosti tih alata.
• Primijenite razvojni pristup pri poučavanju o umjetnoj inteligenciji kako biste obrazovali specijalizirane učenike u temeljnim područjima umjetne inteligencije u stvarnom svijetu, poput percepcije, rezoniranja, predstavljanja ili učenja. Učenici bi se trebali suočiti s različitim izazovima umjetne inteligencije kroz praktične i programerske projekte, tako da svladaju osnove umjetne inteligencije iz tehničke perspektive.

Pročitajte cijelo pregledno izvješće br. 2 “Scenariji i praktični primjeri upotrebe umjetne inteligencije u obrazovanju” i pronađite sva ostala izvješća stručne skupine za umjetnu inteligenciju u obrazovanju Europske platforme za digitalno obrazovanje u objavi “Learning journey for, about, and with AI“.
Također vas pozivamo da se pridružite Europskoj platformi za digitalno obrazovanje.