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.

…

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.

Briefing report No. 2
by the European Digital Education Hub’s squad on artificial intelligence in education Authors: Cristina Obae, Yann-Aël Le Borgne, Francisco Bellas, Riina Vuorikari, Oksana
Pasichnyk, Petra Bevek, Bertine van Deyzen, Ari Laitala, Madhumalti Sharma, Robbe Wulgaert, Jessica Niewint-Gori, Johanna Gröpler, Alexa Joyce and Lidija Kralj.

Tekst na hrvatskom je dostupan niže.

Artificial intelligence (AI) technology has already moved from an emergent to a more advanced stage where people are trying to explore its affordances and discover new innovative usages. It became extremely clear that AI technology is here to stay, and teachers cannot ignore it anymore. How should offerings to educators be positioned, and which problems are we going to solve through AI usage? We will try to model the 5 Whys technique on how AI is making an impact on education, teaching and learning. The below sets of questions refer first to education in general and then to the teaching/learning process:

1) Why is AI making an impact on education, teaching and learning?
AI is making an impact on education, both for teachers and for students as it enables new forms of personalisation and learning through individual feedback and coaching. While there are concerns over academic integrity, there is also hope that AI will enable teachers to provide more personalised learning experiences for their students.
2) Why is personalisation important in education?
Every student is different in their abilities, interests and circumstances of learning. It is important to tailor learning experiences for each individual student. This task is incredibly difficult in large classes, when a teacher cannot provide real-time feedback for every student.
3) Why is real-time feedback valuable in education?
Real-time feedback helps students identify their strengths and weaknesses, adjust their learning strategies, and improve their performance. It allows them to focus on achieving educational outcomes most effectively.
4) Why is enhancing educational outcomes important?
Education provides students with the knowledge and skills they need to succeed in their personal and professional lives. Educational outcomes are designed in a way that improves students’ future prospects and contributes to societal well-being.
5) Why is societal well-being important?
Providing students with high-quality education can help create a more just and equitable society, where everyone has the opportunity to reach their full potential regardless of their background or circumstances.
…

Briefing report ends with Recommendations by the Squad

• Create an online course for school management on integrating AI at the school level to support education.
• Define “human-AI interface interaction skill”.
• Make recommendations for including “teaching with AI” in initial teacher education.
• Propose several professional development pathways for teachers to get acquainted with AI.
• Teachers who are wondering how to get started with AI could access this flowchart
  and find guidance depending on the choices they make.

Read whole report No. 2 “How to Support Teachers to Use AI in Teaching” 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.

Kako pružiti podršku učiteljima pri upotrebi umjetne inteligencije u poučavanju
Pregledno izvješće br. 2 stručne skupine za umjetnu inteligenciju u obrazovanju Europske platforme za digitalno obrazovanje.  
Autori: Cristina Obae, Yann-Aël Le Borgne, Francisco Bellas, Riina Vuorikari, Oksana
Pasichnyk, Petra Bevek, Bertine van Deyzen, Ari Laitala, Madhumalti Sharma, Robbe Wulgaert, Jessica Niewint-Gori, Johanna Gröpler, Alexa Joyce i Lidija Kralj.

Tehnologija umjetne inteligencije (UI) već je prešla iz faze novosti u napredniju fazu u kojoj ljudi pokušavaju istražiti njezine mogućnosti i otkriti nove inovativne načine uporabe. Postalo je potpuno jasno da je UI tehnologija tu da ostane pa je učitelji više ne mogu ignorirati. Kako će se umjetna inteligencija predstaviti učiteljima i koje ćemo probleme riješiti njenom upotrebom? Pokušat ćemo primijeniti model 5 Zašto na utjecaje umjetne inteligencije na obrazovanje, poučavanje i učenje. Sljedeći niz pitanja najprije se odnose na obrazovanje općenito, a zatim na proces poučavanja ili učenja:

1) Zašto umjetna inteligencija utječe na obrazovanje, poučavanje i učenje?
UI utječe na obrazovanje, kako na učitelje tako i na učenike jer omogućuje nove oblike personalizacije i učenja uz individualne povratne informacije i pružanje podrške. Iako postoji zabrinutost oko akademske čestitosti, postoji nada da će umjetna inteligencija omogućiti učiteljima stvaranje personaliziranijih iskustava učenja za svoje učenike.
2) Zašto je personalizacija važna u obrazovanju? 
Svaki učenik ima drugačije sposobnosti, interese i okolnosti učenja. Važno prilagođavanje iskustava učenja svakom pojedinom učeniku. Ovaj zadatak je nevjerojatno težak u velikim razredima, kada učitelj ne može pružiti povratnu informaciju u stvarnom vremenu svakom učeniku.
3) Zašto su povratne informacije u stvarnom vremenu vrijedne u obrazovanju?
Povratne informacije u stvarnom vremenu pomažu učenicima da prepoznaju svoje snage i slabosti, prilagode svoje strategije učenja i poboljšaju svoje rezultate. Omogućuju im usredotočivanje na učinkovito ostvarivanje obrazovnih ishoda.
4) Zašto je poboljšavanje obrazovnih ishoda važno?
Obrazovanje učenicima pruža znanja i vještine koje su im potrebne za uspjeh u osobnom i profesionalnom životu. Obrazovni ishodi osmišljeni su na način koji poboljšava buduće uspjehe učenika i pridonosi društvenoj dobrobiti.
5) Zašto je društvena dobrobit važna?
Pružanje visokokvalitetnog obrazovanja učenicima može pomoći u stvaranju pravednijeg i ravnopravnijeg društva u kojem svatko ima priliku ostvariti svoj puni potencijal bez obzira na svoje porijeklo ili okolnosti.
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Pregledno izvješće završava Preporukama stručne skupine

• Napravite online tečaj za vodstvo škole o integraciji umjetne inteligencije na školskoj razini kako bis se pružila podrška obrazovanju.
• Definirajte “vještinu interakcije između čovjeka i umjetne inteligencije”.
• Pripremite preporuke za uključivanje „poučavanja s umjetnom inteligencijom” u početno obrazovanje učitelja.
• Predložite nekoliko načina profesionalnog razvoja učitelja kako bi se upoznali s umjetnom inteligencijom.
• Učitelji koji se pitaju kako započeti s umjetnom inteligencijom mogu slijediti ovaj dijagram toka i pronaći prijedloge ovisno o izborima koje naprave.

Pročitajte cijelo pregledno izvješće br. 2 “Kako pružiti podršku učiteljima pri upotrebi umjetne inteligencije u poučavanju” 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. 1
by the European Digital Education Hub’s squad on artificial intelligence in education Authors: Yann-Aël Le Borgne, Francisco Bellas, Dara Cassidy, Riina Vuorikari and Lidija Kralj.

Tekst na hrvatskom je dostupan niže.

Demands on the teaching professions are continually evolving, necessitating the development of an increasingly sophisticated set of competences. In particular, the speed at which digital technologies are developing creates a strong impetus for educators to enhance their digital competence. The realisation of the potential educational benefits of artificial intelligence (AI), and digital data more generally, calls for the active and meaningful engagement of teachers and school leaders. This in turn requires the development of the necessary AI and data literacy to appreciate the full potential of such systems, while being aware of their drawbacks and limitations. What teachers should be aware of, understand, and be able to do and what kind of attitudes could support them were questions to which the European Digital Education Hub’s (EDEH) squad on artificial intelligence in education searched for answers. We are starting with the presentation of several documents that cover teachers’ competences in the area of digital technology, data and artificial intelligence. Competences are presented in three segments, although there are overlaps in competences for teaching for, with and about AI.

Teaching for AI entails competences for all citizens, including teachers and learners, to engage confidently, critically and safely with AI systems to provide them with the necessary knowledge, skills and attitudes to live in a world surrounded and shaped by AI.
Teaching with AI focuses on how AI systems can be used for educational goals, including using pedagogical judgement on when to use them, but also knowledge about the functioning of underlying algorithms, pedagogical models and data.
Teaching about AI is the more technical part, focused on training students in the fundamentals of AI. It is usually part of AI literacy which should comprise both the technological and the human dimensions of AI organised according to the student’s age. Knowledge about AI basics is key for preparing students for the labour market, independently of their future careers.

Briefing report ends with Recommendations by the Squad

• Different competences are needed for teachers, school leaders, IT support personnel and other professionals in education. This can mean varying levels of knowledge, skills and attitudes related to teaching for, with and about AI.
• There are significant differences in competences for those who will teach about AI (the techniques and the technologies) and those who will just use AI as support for teaching and learning processes, but all teachers need to know what impact AI has on people and have competences to teach for and with AI.
• All competences need to be described contextually and with existing subject-specific examples.

Read whole report No. 1 “Teacher’s competences” 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.

Učiteljske kompetencije
Pregledno izvješće br. 1 stručne skupine za umjetnu inteligenciju u obrazovanju Europske platforme za digitalno obrazovanje.  
Autori: Yann-Aël Le Borgne, Francisco Bellas, Dara Cassidy, Riina Vuorikari i Lidija Kralj.

Zahtjevi za učiteljsku profesiju neprestano se razvijaju, zahtijevajući razvoj sve sofisticiranijeg skupa kompetencija. Posebice, brzina kojom se digitalne tehnologije razvijaju snažno potiče učitelje na unaprjeđivanje digitalnih kompetencija. Ostvarenje potencijalnih obrazovnih prednosti umjetne inteligencije (UI) i digitalnih podataka općenito zahtijeva aktivan i smislen angažman učitelja i ravnatelja škola. To ujedno zahtijeva razvoj pismenosti u području umjetne inteligencije i podataka za razumijevanje punog potencijala takvih sustava, uz razvijanje svijesti o njihovim nedostacima i ograničenjima. Čega bi učitelji trebali biti svjesni, što bi trebali razumjeti i moći napraviti te kakve stavove bi trebali razvijati, pitanja su na koja je tim za umjetnu inteligenciju u obrazovanju Europske platforme za digitalno obrazovanje (EDEH) tražio odgovore. Počinjemo s predstavljanjem nekoliko dokumenata koji pokrivaju kompetencije učitelja u području digitalne tehnologije, podataka i umjetne inteligencije. Kompetencije su predstavljene u tri segmenta, koji se međusobno preklapaju: kompetencije za poučavanje za umjetnu inteligenciju, poučavanje s umjetnom inteligencijom te poučavanje o umjetnoj inteligenciji.

• Poučavanje za umjetnu inteligenciju podrazumijeva kompetencije svih građana, uključujući učitelje i učenike, da se pouzdano, kritički i sigurno koriste sustavima umjetne inteligencije kako bi im se pružilo potrebno znanje, vještine i stavovi za život u svijetu okruženom i oblikovanom umjetnom inteligencijom.
• Poučavanje s umjetnom inteligencijom usredotočuje se na to kako se sustavi umjetne inteligencije mogu koristiti za obrazovne ciljeve, uključujući pedagoško procjenjivanje o tome kada ih koristiti, ali i znanja o funkcioniranju osnovnih algoritama, pedagoških modela i podataka.
• Poučavanje o umjetnoj inteligenciji sadrži više tehničkih aspekata, usmjereno je na obrazovanje učenika o osnovama umjetne inteligencije. Obično je to dio pismenosti o umjetnoj inteligenciji koja bi trebala uključivati i tehnološku i ljudsku dimenziju umjetne inteligencije prilagođenu dobi učenika. Poznavanje osnova umjetne inteligencije ključno je za pripremu učenika za tržište rada, neovisno o njihovoj budućoj karijeri.

Pregledno izvješće završava Preporukama stručne skupine

• Različite kompetencije potrebne su za učitelje, voditelje škola, informatičko osoblje i druge stručnjake u obrazovanju. To može značiti različite razine znanja, vještina i stavova u vezi s poučavanjem za, s i o umjetnoj inteligenciji.
• Postoje značajne razlike u kompetencijama za one koji će poučavati o umjetnoj inteligenciji (tehnike i tehnologije) i one koji će koristiti umjetnu inteligenciju samo kao podršku procesima poučavanja i učenja, ali svi učitelji trebaju znati kakav utjecaj umjetna inteligencija ima na ljude te imati kompetencije za poučavanje za i s umjetnom inteligencijom.
• Sve kompetencije potrebno je opisati kontekstualno i s postojećim predmetnim primjerima.

Pročitajte cijelo pregledno izvješće br. 1 “Kompetencije učitelja” 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.