The State of Artificial Intelligence and Education Across Europe: the resultsof A a Survey of Council of Europe Member States
Irene-Angelica Chounta,Vania Dimitrova, PauloNuno Vicente, Malgorzata Cyndecka, Wayne Holmes, Lidija Kralj, Jen Persson,Barbara Wasson Council of Europe, AI&ED Expert Group
Acknowledgements[SSB1]
The authors would like to thank the Council of Europe Education Department for their support and
guidance throughout the drafting of this report, more specifically
· Villano Qiriazi, Head of the Education Department
· Ahmet-Murat Kiliç, Head of the Digital Transformation and E-learning Unit
· Arzu Burcu Tuner, Senior Project Officer
(XXX)-
The authors would also like to thank to (XXX)
Executive Summary
The Council of Europe's 'Steering Committee for Education Policy and Practice' (CDPPE) launched a new project in 2019 as part of the 2020-21 'Education for Democracy' program. This initiative, titled 'Artificial Intelligence and Education,' aims to explore the implications of AI and AI-based technologies and applications in education. The project aims to examines how learning with AI, learning about AI, and preparing for AI can contribute to upholding the Council of Europe's core values on human rights, democracy, and the rule of law.
The COVID-19 pandemic accelerated the adoption of digital platforms in education, including AI technologies such as adaptive tools and chatbots. However, there is a lack of empirical studies on their effectiveness, as well as a lack of mapping of AI policies and strategies in education across member states.
Following this initiative, the Council of Europe launched a survey to its member states, with the aim to gather data to better understand how member states address the different connections between AI and Education. This report provides an overview and analysis of the survey conducted.
The survey objectives were to identify promising policies and strategies related to AI and education, identify successful practices in learning with AI, learning about AI, and preparing for AI, and to examine the Council of Europe’s involvement and potential role in supporting the development of appropriate policy and legal instruments[SSB2].
The conclusions drawn from the survey highlight several key findings. Firstly, member states have established general policies and strategies for AI but lack specific policies for AI and education. Stakeholder consultation, particularly with teachers, parents, and students, is necessary for developing specific AI and education policies. Secondly, there is a lack of rigorous monitoring and regulation in education regarding AI, emphasizing the need for coordinated efforts at the national and European levels. Thirdly, evidence on the impact of AI in education is lacking, which is crucial for informed decision-making and the implementation of regulatory measures. Lastly, AI literacy primarily focuses on educational institutions, with limited training for teachers and staff, indicating the need for a broader perspective on AI literacy and dedicated resources.
TBA
In summary, the survey findings emphasize the importance of developing specific AI policies and strategies for educationimplementing effective monitoring and regulatory measures, generating evidence on AI's impact, and promoting comprehensive AI literacy across the education sector. These actions will ensure responsible, fair, accountable, and transparent connections between AI and education in alignment with the Council of Europe's values and for the common good[SSB3].
Table of Contents
Chapter 1: Introduction
Background
In recent years, there has been a growing connection between Artificial Intelligence (AI) and education. This connection includes: (i) learning with AI, using AI technologies to enhance teaching and learning; (ii) learning about AI, how AI works and how to createit; and (iii) preparing for living in a world impacted by AI (henceforth: preparing for AI), preparing all citizens for the implications of AI for all our lives. Each of theseconnections entail multiple opportunities, but also challenges and risks. It is crucial that the benefits outweigh the risks. For example, it is essential to ensure that AI does not undermine inclusion or equity in education, or increase the digital divide, especially for those who are most vulnerable.
The Council of Europe is already examining the impact of AI in general on human rights, democracy, and the rule of law. In particular, the ‘Ad hoc Committee on Artificial Intelligence’ (CAHAI) undertookmulti-stakeholder consultations to examine the feasibility and potential elementsof a legal framework for the development, design, and application of artificial intelligence. CAHAI has now been superseded by the Committee on Artificial Intelligence (CAI), which is tasked by the Council of Europe’s Committee of Ministers with “conduct(ing) work to elaborate an appropriate legal framework on the development, design, and application of artificial intelligence, based on the Council of Europe’s standards on human rights, democracy and the rule of law.”
Now the Council of Europe is also focusingon the impact of AI on[BSS4] the educationsector. In 2019, the Council of Europe’s ‘Steering Committee for Education Policy and Practice’ (CDPPE[BSS5] – now CDEDU) launched a new project as part of the 2020-21 ‘Education for Democracy’ programme.1 This project, entitled ‘Artificial Intelligence and Education,’ aims to explorethe implications of the use of AI and AI-enabledbased technologies and applications for [BSS6]education. The project is exploring how learning with AI, learning about AI, and preparing for AI will contribute towards the Council of Europe’s core values on human rights, democracy, and the rule of law.
The COVID-19 pandemic forced education systems to make greater use of digital platforms and applications, in many cases adopting emergencyremote teaching practicesrather than established online learning strategies2. Some of these have involved AI technologies, such as adaptive tools, chatbotsand e-proctoring. However,while such tools are widely used in educational settings across Europe, there remain few empirical studies to demonstrate their validity or efficacy. There is also a lack of mapping of AI policies and/or strategies and practices in education in member states. Given the potential impact and the fast-paced development of AI and education, co-ordinated action and common policies and strategies are of key importance - to facilitate the effective exchange of promising practices among member states, and to ensure that the connections between AI and education are all developed with respect of the Council of Europe values and for the common good.
Survey Objectives
This survey aimed to gather data from the Council of Europe member states to enable a better understanding of the differentconnections between AI and education.
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1 See the Committee of Ministers Recommendation CM/Rec(2019)10 on developing and promoting digitalcitizenship education
The specific objectives were:
− to identify promising policies and/or strategies focused on the connections between AI and education that safeguard the fundamental rights and freedoms of learners and complement existingwork by other organisations;
− to identify promising practices in relation to (i) learningwith AI, (ii) learning about AI, and
(iii) preparing for AI;
−to inform the working conference to be heldhoeld in September 2022 as part of the Council of Europe’s work programme (2023-2025) on Artificial Intelligence and Education through the lensof human rights,democracy, and rule of law; and
−to facilitate support the Council of Europe indeveloping to develop appropriate policy and legal instruments to ensure that the connection between AI and education is responsible, accountable, transparent, aligned with the values of the Council of Europe and for the common good.
Survey Structure
The survey included six parts, compriseding background information and three themes: (1)Policies/Strategies, (2) CurrentPractices, and (3) Regulations.
Figure 1 presents the topics inquired aboutin each theme.
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Figure 1. Topics inquiredabout in each of the three themes:Policies/Strategies, Current Practicesand Regulations.
The surveycontained 65 questions, distributed as follows:
● Profile (7 questions)
This sectioncollects the background information about the responding memberState.
● Part I – Policies and/or strategies for Artificial Intelligence (in general) and Artificial intelligence and education (24 questions)
In this section existing policies and/or strategiesin the member states, startingwith the generaland moving onto the educationrelated, are mapped.
● Part II – Learning with Artificial intelligence (10 questions)
In this section information was sought aboutthe use of AI technologies to support teachingand learning.
● Part III – Learning about Artificial Intelligence (6 questions)
In this section information was sought aboutthe teaching and learning of AI (how it worksand how to create it).
● Part IV – Preparing for Artificial Intelligence (9 questions)
In this section information was sought about how citizens are being prepared to live in a world increasingly impacted by AI, and how and what strategies AI developers are using to develop AI responsibly.
● Part V – Regulation, accountability, monitoring, and evaluation(9 questions)
In this section information was sought about how the connections between AI and education are regulated, monitored, and evaluated in the member states. In addition, information about which accountability mechanisms are in place to ensure AI development in the context of education is responsible and attuned to human rights, democracy, and the rule of law was elicited.
Survey Launch
The intention was that the survey was to be completed or co-ordinated by Ministries of Education in the 46 member states. As policies and/or strategies concerning AI and education and the AI systems themselves may be developed by various organisations (such as public authorities, directorates, think tanks, private organisations, civil society, or academia), the Ministries were asked to contact those needed to help them provide a holistic pictureof AI and education in their country.
The survey was developed and conducted with Survey Monkey. The invitation and link to the survey was distributed via email from the Council of Europe. The survey was launched in September20223 and participation was possible until the end ofOctober 20223.
Respondents
Responses were received from 28 member states. 3 were deleted since the answers were null (empty).Hence, the analysispresented here includesthe responses from 25 memberstates.
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[TAB7]
Chapter 2: Policies and/or strategies for AI
The survey exploredexisting policies and/or strategies in the member states, startingwith general AI policies and/orstrategies and moving onto education-related policies and/orstrategies.
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21 memberstates reported that they have a nationalgeneral AI policyand/or strategy, and 12of them continue to work on further developments. 2 member states do not have a general AI policy in place but work on development. This makes, in total, 14 member states currently working on the development of general AI policy and/or strategy at the time of the survey, and 9 member states that currently arewere not in a development phase. 1 member state reported that they have no general AI policyand/or strategy and that they are not workingon one.
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The survey participants reported that their national AI development strategyincludes: (1) planning interventions and investments (in technical infrastructure, in education and training for digitalskills, in the use of AI in public administration), (2) the continuation of a pro-innovation approach to regulate AI, and (3) the preparation of a general work agenda on digitisation. Other participants reported that they are still assessing the need for AI regulation and/or don't have a specific AI strategy but do have an overall action plan for digital transformation.
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15 member states reported that they have measures in place to inform stakeholders about developments, while 4 member states stated they have no measures in place. Member states also reported that they have consulted stakeholders from academia(23 out of 25 member states), policymakers (23 out of 25 member states) and the private sector (22 out of 25 member states) on general AI policies.
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Participants reporting that "other" (n=6) stakeholders were involved/consulted in the development of their country'soverall AI policy/strategy mentioned public bodies in the fields of cybersecurity, public procurement, consumer protection bodies, data protection authorities, regulatory bodies, and potential users. The general AI policies have been communicated via information sessions (17 outof 25 member states)and social media (14 out of 25 member states).
Participants reporting other forms of information dissemination methods (n= 10) mentioned: workshops, conferences, meetings with direct stakeholders, public initiatives and consultations, publications, and official government portals.
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Most member states (22 out of 25) reportedthat educational issuesare specifically addressed in their generalAI policies.
Respondents reported that they involved policymakers (19 out of 25) and stakeholders from academia (18 out of 25) and the private sector (18 out of 25) to develop their AI and Education policies. Teacher representatives, learners, and parents of learners were the least-involved stakeholders.
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An analysisof the participants' reports of education issuesspecifically addressed in their country's AI policy/strategy are summarised below:
● AI Literacy(Technological dimensions). Recognizing Recognising that it is one of the main challenges, most national policies give centrality to the strengthening of teachers' digital skills and competences associated with the field of Artificial Intelligence, covering the different levelsof education, including vocational education and lifelong learning.Overall, there is a clear recognition that teachers need to acquire or regularly update their digital skills (e.g., “make teachers digitally proficient”; “digitally literateteachers and pupils”;“train a new generation of teachers”).
● AI Literacy (Human dimensions). There is an emerging recognition that curricula for teaching AI should not be limited to technology but should focus on educating informed individuals who can deal with both the technical, ethical,social, and societalaspects of AI as an area of digitiszation. The need to prepare parents and teachers for the proper protection of children is occasionally mentioned. It is often recogniszed that teaching AI needs to expose students to discussions about the ethical choices that will often be part of programming and algorithm design (e.g., “discuss the ethical choices”; “taking into account AI ethics”; “protect the rights of participants in the education system”). In certain national contexts, it is recogniszed that in cases where AI systems provide professional support to qualified personnel in their daily work in schools, they should be able to be provided with a capacity to check and correct the AI systems adopted.
● Using AI to learn about learning. The need for more evidence-supported research around the opportunities and limits of adopting learning progress assessments in self- directed learning is mentioned, including looking at ways in which learning analytics can and cannot be used by considering ethical and data protection aspects (e.g., “self- determination”; “the right to control one’sdata”). The adoptionof data analysis systems is also aimed at the administrators of educational institutions to provide experiences for students (e.g., “to make informed decisions”).
● Learning with AI. The personaliszation of learning is the most common trend present in the national policies that mention a strategic investment on teaching-learning practices with AI (e.g., “adaptation of learning to personal needs”; “customised education”). Inspecific cases, collaboration with private sector experts is encouraged to obtain support in the preparation of teaching materials and the implementation of the teaching process. Some national documents concretize plans with targets set to achieveprogressively more citizens benefiting from AI-supported education. A priority is highlighted for developing personalised, data-driven, and digitally assisted forms of learningto fully supportindividual learning paths. In some national contexts, the creation of awards for teachers who take the leadin using AI is mentioned.
Only 5 member states reportedthat AI and education (including learning with AI, using AI to learnabout learning, learning about AI and preparing for AI) is regulated and only 4 reported that AI and education is monitored or evaluated. 9 (out of 25) member states reported that they do not regulate Al and education, while 10 (out of 25) do not monitor or evaluate it. Almost half of the respondents (11 out of 25) either did not know or did not provide a response to the questions about regulation, monitoring and evaluation of AI and education.
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Funding for research on the efficacy of learning with AI is provided in 10 (out of 25) member states; In 9 member states research on human and societal implications on AI and education is funded. Respondents from 11 member states did not have or did not know about any large programs that fund research into the societalimplications of AI and education; similarly 8
respondents did not have or did not know about any programs to fund researchon the efficacy of AI and education.
Chapter 3: Policies, strategies, and practices for AIin Education
The surveyexplored the use of AI technologies to support teachingand learning, including AI systems in educational contexts and the use of AI to learnabout learning.
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While 4 out of 23 member states reported that they have specific policies for the use and/or implementation of AI systems in education, 9 member states reported that they are currently discussing, planning, or implementing policies about AI systems in education, most of them as part of a general AI national plan.6 member states reportedthat there are no relevantpolicies in place.At the same time, most of the member statesreported that eitherthey do not know whetherthere is a specific budget for the development of such policies (10 out of 22) or that there is no budget available(9 out of 22).
Most member states reported that there are no policies in place on the use of AI to learn about learning (11 out of 23) and no related budget (11 out of 20). Some member states indicated that these topics are addressed in their general AI strategy or that they will be addressed in AI and education policies currently under development. Other member states also referredto policies related to learningabout AI.
Almost one third of the member states (7 out of 25) did not respond to the question about governance policies. Data policies for AI systems in educational contexts exist in 15 member states, while ethical policies exist in 9 member states. Meanwhile, only 3 member states include evidence policies (these member states include all three levels of policies addressed in the question, that is data, ethical and evidence policies). One of these member states provided additional detail, specifying that their Department for Education is developing policies to support the use of AI systemsin educational settings/contexts, including an EducationPrivacy Assurance Scheme for the strengthening of data protection in the education sector. An AI Code of Practice is also being developed. This is on the understanding that educational institutions are data- controllers in their own right, and hence the decision to use this technology is solely their own. The government will provide guidance on what legislation must be considered when making decisions.
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One third of the member states (8 out of 25) did not respond to this question. At a national level, decisionsabout systems to be promotedare taken by 7 member states, decisionsabout permitted systems are taken by 7 member states, and decisions about what systems to support are taken by 6 member states. Only 4 memberstates make decisions at all levels.Several member states
reported that they have a decentralised school system which leaves such decisions up to the school administration (school directors, municipalities), which take decisions on the use and acquisition of specific software(the national government is therefore not directly involved). Other responses reported that only systems developed by the state are promoted/recommended and supported.
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Of the 19 member stateswho responded to this question,11 reported that the commercial sector has implemented the most popular AI systems in education, while 10 reported that research centres had done so. The two member states that include social entrepreneurs also include the commercial sector or researchcentres ,centres, respectively. No member State uses all three development sources. Two member states reported that these decisions are left to individual schools while one member State provided an example of a portal in which the schoolscan share best practices and experiences.
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Of the 20 member states who respondedto this question, 15 reported that AI-based technologies are being used in lower secondary school levels, while 16 reported that they were being used in upper secondary schools (16 member states). Fewer member states reported that AI-based technologies are used in higher education (i.e. tertiary level) (13 out of 20), vocational education training (13 out of 20), and primary education (11 out of 20 responses). Only 1 member State reported using AI-based systemsat all levels.
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Of the 20 member states that responded to the question about uses of AI in their education systems, most reported that AI is used for organisational management tasks, such as administration (10 responses), studentmonitoring (6 responses), attendance and registration (6 responses), exam proctoring (6 responses), admissions (4 responses), retention and prediction of dropouts (3 responses), and teacher performance evaluation (4 responses). Others reported that AI is used for student assessment tasks, and specifically in formative assessment (6 responses), and in summative assessment (5 responses). 5 member states reported that they do not use AI for any of the suggested tasks, while only 1 member State reported using AI toinform national strategies.
Several examples of tasks and specific AI systems used to support these tasks were provided, including the following (names of specific AI systems and links are removed due to responses’ anonymisation purposes): Online learningmaterials explaining the basic functioning/ benefits of AI systems, Early warning and pedagogical support system for preventing early school dropouts; e-procuration portals, admissions support systems, attendance and registration portals, teacher performance assessment tools, summative assessment tools, speech recognition or automatic translation facilitation, chatbots and other virtuallearning assistants.
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Of the 21 member states that responded to a question about specific uses of AI systems in teaching and learning, most reported that they used adaptive learning systems (12 responses), personalised learning environments (6 responses), intelligent interactive environments (4 responses), exploratory learning environments (4 responses), dialogue-based tutoring systems (4 responses), embodied AI and robotics (3 responses), and intelligent tutoring systems (2 responses). Example of such systems named in the responses include software systems and suites such as Google for Education, Zoom and Microsoft Teams; learning management systems such as Moodle, and Blackboard; plagiarism checkers (such as Turnitin); and online proctoring systems(such as Examus and ProctorExam).
There was also a strong emphasis on language-based technologies, including speech to text (11 responses), AI-enabled language learning (10 responses), plagiarism detection (10 responses), chatbots (7 responses), and writing evaluation (5 responses). Learning analytics (11 responses) and educational data mining (5 responses) are also reported. Only a very limited use of emotion detection, biometrics, and well-being support was reported (each having only 2 responses). It is important to note that some approaches go by many different names (e.g. adaptive learning, personalised learning,and Intelligent TutoringSystems).
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Chapter 4: Policies,strategies, and practices for AI Literacy
The survey also explored the policies, strategies and practices for AI literacy, that is Learning about AI and Preparing to live with AI.
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8 out of 23 member states reportedthat they have specific policieson teaching/learning about AI technologies or that they have addressed this topic in “Other” ways (7 out of 23), for example as part of other national strategies or that there is planning to address this in the future. 5 out of 23 reported they have no specific policies on teaching/learning about AI technologies in place. Meanwhile 10 out of 22 member states reported that no specific budget is available for such policies,and 9 out of 22 reported that they are not aware of the existence of any such budget.
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When asked whether learning about AI is addressed in other educational settings/contexts such as vocational education and training, member states reported the following examples: free MOOCs, University courses (e.g. University of Cambridge’s Master in AI Ethics and Society), and Specialisation courses for Upper VET students.
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10 out of 23 member states reported that there are policies in place for preparing to live with AI. However, there is no specific budget dedicated for developing such policies (8 out of 20) or they are not aware about any such budget (8 out of 20).
The answers (5 out of 25) to the questionon whether the general publicis being preparedfor the impact of AI on their lives do not provide a conclusive basis for perceiving if such plans exist at the national level and/or if they are implemented; respondents refer to initiatives that fall under the domain of AI training and competency frameworkdevelopment (e.g. DigComp 2.2., training
programs for pupils,students and teacherson AI ethics, online risks, cyber security, and internet safety).
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At Bachelor level, 14 member states address learning about AI and 11 member states address preparingfor AI. This is almostmatched at Master’slevel - 12 and 10 member states,respectively. Responses on relevant topicstaught in highereducation did not provide sufficient information. Of the 12 responses obtained, 3 said N/A or did not have enough data to answer. Most of the remaining emphasise the existence of a holistic approach of the courses around a general appreciation on the effects of technology on society, withoutgiving specific attention to AI.
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Schools tend to address learning about AI in IT/Computer Science classes (15 member states) or in other subjects (15 member states). The same two categories cover preparing for AI. While every respondent could indicate how learning about AI is addressed in schools, 4 indicated that they did not know how preparing for AI is addressed in schools. Relevant topics that are taught in schools include: Media literacy, Information literacy, Data privacy, Cyber resilience, Internet safety / online protection. It should be noted that key topics,such as fairness, human rights, data ownership, ethics,were occasionally mentioned in the responses.
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19 member states have responded to this question. Respondents were asked to select all that apply to their country. One third (8 out of 25) include teaching AI for higher education academic staff. The numbers are smaller for teacher training . Only 1 member State includes administratortraining and just two member states include educational sector employees. The following topics are taught tothe general public to preparethem for the impact of AIon their lives: Cybersecurity, Privacy,Ethics, Protection againstdiscrimination.
Responses elaborated on how learnersin other educational settings/contexts are being prepared for the impact of AI on their lives mentionvocational training, free Massive Open Online Courses(MOOC), and lifelong learningcourses.
Chapter 5: AI and Education & Council of Europe Values
Finally, the survey asked how the Member states ensure that their approaches to Learning with AI, using AI to Learn about Learners, and Preparing for AI, addressthe Council of Europe valuesof Human Rights,Democracy, and the Rule of Law.
Responses emphasise the centrality of the role given to current schoolcurricula and the curricular reforms planned for the coming years,as well as to the development and implementation of legally bindinginstruments aimed at regulating the design, development, and application of AI systems.
Lastly, responses highlightthe importance of the CoE values for the memberstates and reiterate that these values should be addressed when working or learning with AI, without however providingfurther information or clarifications how these will be achieved.
Chapter 6: Conclusions
This report presented the analysis of survey responses from 25 member states during September-October 20223, aiming to clarify the connections between AI and education from the perspective of the CoE member states and, in particular, a) to identify promising policies and/or strategies focused on the connections between AI and education; b) to identify promising practices in relation to learning with AI, learning about AI, and preparing for AI; c) to facilitate the Council of Europe in developing appropriate policy and legal instruments for safeguarding responsible, fair, accountable, and transparent AI and education[BSS8][TAB9].
6.1. Addressing education aspects in the AI policiesand strategies
Most member stateshave either established generalpolicies and strategies for the use of AI or are in the process of doing so. However, AI and education is not addressed as a special or separate case portrayed by the lack of specific AI&ED policies. This is also reflected by the evident lack of consultation with key stakeholders, such as teachers, parents, and students for drafting AI policies.
In order to promote AI and education while ensuring the core values of the Council of Europe are respected, we perceive as necessary for member states to establish AI policies and strategies dedicated to education aspects rather than rely to general AI frameworks. It would be crucial to involve We [BSS10]envision that the key stakeholders, such asteachers, parents, and students, should be activelyinvolved and consultedthem in the development of such specific-purpose policies and strategies since they are directly and explicitly affected by them.
6.2 Monitoring and regulation particularly in education
Although member states have in place or work towards establishing general AI policies, these policies do not include rigorous monitoring and regulation approaches for education. Only 5 member states reportedthat AI and education (including learning with AI, using AI to learn about learning, learning about AI and preparing for AI) is regulated, and only 4 of them reported that AIand education is monitoredor evaluated.
The lack of adequate monitoring and regulation, particularly in education, is critical since technological advancements happen very fast. To accommodate the rapid changes, critical decisions regarding AI & Education are left to schools, municipalities, and the regional administration, while there are no regulatory bodies across the states to safeguard AI and Education.
We[BSS11]highlightThere is a clearthe need for common , orchestrated efforts on the national and European levels towards establishing monitoring and regulatory actionsthat will protecteducation stakeholders from potentially negative or harmful consequences of AI, particularly in education.
6.3 Evidence used for AI adoptionin education
In terms of adoption of policies, there is the need for evidence about the impact of AI in education to inform decision-making and to guide the implementation of monitoring and regulatory measures. Currently, there seems to be a lack or scarcity of such evidence which is particularly alarming if we consider the lack of regulatory approaches in education, for example trials,that are common practice in other domainssuch as healthcare.
We[BSS12]argue for the necessity of placing such practicesSuch regulatory approaches need to be put in place for the use of AI in education due to the impact these technologies can have on humans, and in particular, children.
6.4 Need for a broad view on AI Literacy
AI literacy is addressed predominantly in educational institutions (secondary and higher education). At the same time, limitedtraining is offeredfor school teachers,staff and educationsector employees and no specific budget is dedicated for promoting AI Literacy, revealing a limited view of member states.
We argue for theThere is a need for a broad view on AI Literacy that will build on policies, strategies and practices for Learning about AI as well as Preparing to live with AI. We envision that this is critical and necessary to prepare member states and their citizens for the generalised use of AI and in the contextof everyday life.
6.5 Council of Europevalues and AI & Education
The member states have explicitly stated the need toaddress the Councilof Europe core values when it comes to establishing policies, strategies and legal frameworks for monitoring and regulating AI, and consequently AI and education. However, it was not clear how this could be achieved. While the Council of Europe values are addressed in education, they are not explicitly addressed in the contextof AI and education.
6.6 Capacity of memberstates to respond
The survey was conducted by We[BSS13]inviteding all 46 Council of Europe member states to respond to the survey using through email invitationssent by the Council of Europe. In total, 25 member states provided validanswers to the survey, ;which is slightly more thanhalf the number of the member states.
We [BSS14]acknowledge that on the one hand Tthe length of the survey and on the other hand the topic of the survey might have deterred stakeholders from participation. At the same time, we believe that the participation rate is suggestive of the capacityof member states to respondto this topic.
While documenting the state of AI and education across Europe is a complicated task that demands input from various levels of national agencies, multiple roles, and stakeholders, we argue that discussions about AI and education should be prioritised and actively promoted, given the importance of education with respect to Human Rights,Democracy and Rule of Law.
As a final note, it remains unclearfrom the analysisof the survey responses whetherrespondents understand the distinction between 'learning with AI', 'using AI to learn about learners and learning' and 'preparing for AI'. We perceive tThis distinction–further discussed in the publication of the Council of Europe “Artificial Intelligence and Education: A critical view through the lens of human rights, democracy and the rule of law”–asis criticalto ensure that AI&ED protectsand does not undermine the core values of the Council of Europe, and contributes towards the common good.
Appendix - Definitions Used in the Survey
The definitions below were given to the participants during the survey.They could refer to the definitions when answering the survey questions.
Adaptive Tutoring Systems or Intelligent Tutoring Systems (ITS) or intelligent interactive learning environments or personalised learning systems (NB Some of these terms are contested): AI-driven tools that might provide step-by-step tutorials, practice exercises, scaffolding mechanisms (e.g. recommendations, feedback, suggestions, and prompts), and assessments, individualised for each student, usually through topics in well-defined structured subjectssuch as mathematics or physics.
AI Literacy: Having competencies in both the human and technological dimensions of Artificial Intelligence, at a levelappropriate for the individual (i.e.according to their age and interests).
AI systems: Shorthand term encompassing AI-driven tools, applications, software, networks, etc.
Artificial Intelligence (AI): Artificial Intelligence is notoriously challenging to defineand understand. Accordingly, we offer two complementary definitions:
A set of sciences,theories and techniques whosepurpose is to reproduce by a machine the cognitive abilities of a human being. Current developments aim, for instance, to be able to entrust a machine with complex tasks previously delegated to a human. (Council of Europe, 2021)3
Machine-based systems that can, given a set of human-defined objectives, make predictions, recommendations, or decisions that influence real or virtualenvironments. AI systemsinteract with us and acton our environment, either directlyor indirectly.
Often, they appear to operate autonomously, and can adapttheir behaviour by learning about the context.(UNICEF, 2021)4
Artificial Intelligence and education (AI&ED): The various connections between AI and education that include what might be called ‘learning with AI’, ‘learning about AI’, and ‘preparing for AI’. Learningwith AI has also been called “Artificial Intelligence for education”.5
Artificial Intelligence in education (AIED): An academic field of enquiry, established in the 1980s,that primarily researchesresearch AI tools to support learning (i.e. ‘learningwith AI’).
Automatic Writing Evaluation: AI-driven tools that use natural language and semantic processing to provide automated feedback on writing submitted to thesystem.
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3 https://www.coe.int/en/web/artificial-intelligence/glossary
4 https://www.unicef.org/globalinsight/reports/policy-guidance-ai-children
5 Recommendation CM/Rec(2019)10 of the Committee of Ministers to member States on developing and promoting digital citizenship education
Big data: Large heterogenous and volatile data sets, generated rapidly from different sources,that are cross-referenced, combined and mined to find patterns and correlations, and to make novel inferences.6 The analysis of big data is too complex for humans to undertake without machine algorithms.
Chatbots: systems designed to respond automatically to messages through the interpretation of natural language. Typically, these are used to provide support in response to queries (e.g. “Where is my next class?”, “Where can I find information about my assessment?”).
Dialogue-based Tutoring Systems: AI-driven tools that engage learners in a conversation, typed or spoken, aboutthe topic to be learned.
e-Proctoring: The use of AI-driven systemsto monitor learnerstaking examinations with the purpose of detecting fraud and cheating.
Educational Data Mining: See Learning Analytics.
Educators: Shorthand term encompassing teachers and other professionals in formal education and early childhood care, including school psychologists, pedagogues, librarians, teaching assistants and tutors.
Embodied AI and Robotics: Movable machines that perform tasks either automatically or with a degree of autonomy.
Exploratory Learning Environments: AI-supported tools in which learners are encouraged to actively construct their own knowledge by exploring and manipulating elements of the learning environment. Typically, these systems use AI to provide feedback to support what otherwise can be a challenging approach to learning.
GOFAI: "Good Old-Fashioned Artificial Intelligence", a type of AI more properly known as “symbolic AI” and sometimes “rule-based AI”, which was the dominant paradigm before Machine Learning (ML) came to prominence.
Intelligent interactive learning environments: See Adaptive Tutoring Systems. Intelligent TutoringSystems (ITS): See Adaptive Tutoring Systems.
K12: Children in primaryand secondary education (i.e. from Kindergarten through grade twelve,ages 5 to 18).
Learners: Shorthand term to encompass children and young people in formal education (i.e. pupils and students) and people of all ages engaged in formal, informal or non-formal education (in accordance with the principle of lifelong learning).7
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6 https://www.coe.int/en/web/artificial-intelligence/glossary
7 Recommendation CM/Rec(2019)10oftheCommitteeofMinisters tomemberStatesondeveloping andpromoting digitalcitizenship education
Learning Analytics and Educational Data Mining: Gathering, analysing, and visualising big data, especially as generated by digital devices, about learners and learning processes, with the aim of supporting or enhancing teaching and learning.
Learning Network Orchestrators: AI-driven tools that enable and supportnetworks of people(e.g. learners and their peers, or learners and teachers, or learners and people from industry) engaged in learning.
Machine Learning (ML): A type of AI, the type that is currently dominant, that uses algorithms and statistical models to analyse big data, identify data patterns, draw inferences and adapt, without specific step-by-step instructions.
Natural Language Processing (NLP) or Speech to text and Natural Language Generation: Systemsthat use AI to transcribe, interpret, translate and create text and spoken language.
Personalised learning systems: See Adaptive TutoringSystems
Plagiarism checking: AI-driven content scanning tool that helps identify the level of plagiarism in documents such as assignments, reports and articles by comparing a submitted text with existing texts.
Profiling: The automated processing of personal data to analyse or predict aspects of that person'sperformance, economic situation, health, personal preferences, interests, reliability, behaviour, location, or movements.
Robotics: See Embodied AI.
Smart curation of learning materials: The use of AI techniques to automatically identify learning materials (such as Open Educational Resources) and sections of those materialsthat might be useful for a teacher or learner.
Speech to text:SeeNatural Language Processing.
[SSB1]This report was prepared within the scope
of the Council of Europe’s intergovernmental
project on Artificial Intelligence and
Education.
[SSB2]I have checked the previous executive summary on the AIED report, and they explore a bit more here, splitting into parts, however its 100 pages compared to the survey report. In any case, would you like me to explain better each part of the survey?
65 question, divided into 5 sections (…)
[SSB3]I would like to add something similar to what is written below; however, it seems ‘accusatory’.
The responses to the survey were limited in detail and lacked concrete information, due to a lack of participation from all member states and likely the absence of extensive knowledge on the subject. Consequently, the survey results are deemed inadequate and would benefit from a reevaluation to obtain more accurate and comprehensive findings. Further research is necessary to gather more appropriate results and provide clarity on the matter.
[BSS4]In the education sector or in education
[BSS5]Former CDEDU
[BSS6]Of the use of AI in education
Should we mention the AIED report?
[TAB7]I think we thought of removing or changing the map
[BSS8]This is a repetition….
[TAB9]It can be rephrased as they need to repeat the aim/message in the conclusion.
[BSS10]It would be crucial to… instrad of ‘we’
[BSS11]‘we’