Mapping Upper Secondary Computer Science Specifications Against UNESCO's Framework of AI Learning Outcomes

Abstract

In this paper, we explore the coverage of artificial intelligence (AI) and machine learning in upper secondary computing specifications, guided by an AI curriculum mapping framework established by UNESCO. This framework organizes learning outcomes into three main AI categories: a) Knowledge, b) Skills, and c) Values & Attitudes; and is based on AI curricula developed and implemented by 11 governmental or otherwise authorized bodies. Although the UNESCO framework is fairly comprehensive, Ireland or nearest neighbours, were not included in it. Through the lens of the UNESCO framework, we investigate how the upper secondary computing curriculum specifications of Ireland and six other regions with English-based, similar educational systems (England, Malta, Northern Ireland, Scotland, Wales, and Western Australia) align with the 222 AI learning outcomes identified by UNESCO. This allows us to map the existing educational terrain, identifying both the common threads and divergences in how AI is taught at the upper secondary level, without suggesting any normative judgments on these curricular eforts. Our intention is to help other regions align their curricular eforts best. By doing so, we aim to contribute to a broader understanding of how AI education is currently structured across diferent contexts, ofering insights into the multifaceted dimensions of preparing students for the complexities of AI technology and its implications. This study shows that AI education pays little attention to the technical aspects of algorithms, big data principles, environmental considerations, and ethical considerations. This underscores the need for a more comprehensive approach that includes practical and ethical dimensions of AI technologies.

Keywords

• eol>Artificial Intelligence
• curriculum mapping
• England
• Ireland K-12 Malta Northern Ireland Scotland school second-level secondary specification UNESCO UK Wales Western Australia

1. Introduction

‘IBM-CBSE AI Curriculum’ for grades XI & XII, Microsoft’s textbook series in India, and the Microsoft Computer Science Curriculum Toolkit; and curricula from IBM, Microsoft, Intel and MIT that were used as benchmarks.

The LOs of the curricula studied in the UNESCO report were extracted through an analysis of the frameworks and programs of study, and the curricula were analyzed comparatively in aggregate to map out LO specifications across grade levels. The types of engagements that were listed as curriculum objectives at each level were also extracted. It is important to note that the report makes no claim on what should or should not be included or covered in a K–12 AI curriculum, but merely represents current practices. We have numbered the 222 LOs found in the UNESCO AI framework (p.39-44) [ 1 ] for clarity, and they are listed in Table 2 to 11.

2. AIM & RELATED WORK

The Computer Science curriculum for Ireland [2] was not included in the UNESCO study. Nor were the curricula of its nearest (in terms of geography and educational system) English speaking neighbours (England [ 3, 4 ], Scotland [ 5, 6 ], Wales [ 7 ], Northern Ireland [ 8 ], Malta [ 9, 10 ], and Western Australia [ 11, 12 ]). In this paper we address this omission by systematically mapping the upper secondary Computer Science (CS) curriculum specifications from these 7 regions against the UNESCO [ 1 ] framework for the categorization of AI LOs - see Tables 2 to 11. We are not aware of any other publications that have utilized the UNESCO AI Curricula Mapping Framework. It is, however, mentioned in several papers [ 13, 14 ]. This mapping exercise is intended to identify key themes, strengths, and potential gaps in current AI educational practices, thereby ofering insights into how these specifications can be further developed or enhanced. The aim of this paper is to answer the following research question:

How do the learning outcomes of the upper secondary CS specifications from Ireland and its nearest English speaking neighbours align with the UNESCO mapping of learning outcomes in the AI categories: (a) Knowledge, (b) Skills and (c) Values & Attitudes?

3. METHOD

This section describes the curriculum mapping process adopted in this work and describes the diferent grade levels of the regions studied, and how they align with each other.

3.1. Curriculum Mapping

A curriculum map is a visual depiction of the elements and features of a curriculum that makes the individual components visible for easy examination and possible comparison [ 15 ]. This research involves employing curriculum mapping as a methodological tool to conduct a comparative analysis of upper secondary CS specifications from 7 regions. The primary focus of this comparison is to understand the extent to which these specifications have integrated AI into their educational frameworks. A systematic approach was adopted for data extraction and input - findings were input into a standardized instrument which facilitates easy analysis and comparison of the AI components across diferent regions. This analysis presented a challenge. Some LOs, while not explicitly stated, are intricately woven into the content of some curricula. On the other hand, there are instances where some LOs fall short of comprehensive realization within the specification given in some curricula.

This complexity underscores the need for a discerning approach when evaluating the alignment between educational objectives and content, ensuring a deeper understanding of the extent to which LOs are integrated and fulfilled. Thus, we used the following scale to quantify whether a particular LO appears within a curriculum specification: (1) Not addressed, (2) Partially addressed, (3) Interwoven into content, and (4) Addressed in content. The LOs were initially rated by one author. A second author then reviewed their rating, and discrepancies were discussed and reconciled through discussion, including the third author.

EQF

Level 4

3.2. Grade Levels

The European Qualifications Framework (EQF) [ 16, 17 ], established in 2008, serves as a common reference framework for qualifications (EQF Levels 1-8). Table 1 shows qualifications approved by national qualifications frameworks of the United Kingdom (England, Scotland, Wales and Northern Ireland), Ireland, Malta and Western Australia mapped against Level 1 to 4 of the EQF. The specifications chosen for analysis are positioned at Level 4 on the EQF (except Scotland - Level 4/5). The UNESCO report mapped the 222 AI LOs against three grade levels: primary, middle and high school (high school being grades 10-12 for most countries) [ 1 ]. Our focus is on what students are being taught in CS in the ifnal 2 years of school (ages 16-18 years). The grade levels and curricula studied for Ireland and the 6 other regions investigated in this paper are described below.

ENGLAND The General Certificate of Secondary Education (GCSE) is an academic qualification that is taken in a range of subjects in England, Wales and Northern Ireland (Year 11, Level 2 EQF). It is followed by the Advanced Subsidiary (AS) and Advanced (A-level) exams, typically studied during the final two years of second-level schooling. The General Certificate of Education Advanced Level (GCE A-levels) is an entry qualification for universities, normally based on three A-level grades. The CS subject is optional to students who may choose this from a large selection of other subjects. A number of examining boards ofer diferent A-Level CS curricula (for example, AQA [ 18 ] and Cambridge [ 19 ]), all of which must comply with UK government regulations set by the Ofice of Qualifications and Examinations Regulation (Ofqual). OCR (Oxford, Cambridge, and RSA) [ 20 ] is one of the leading UK awarding organizations (they ofer over 100 occupational qualifications in addition to the GCSEs and A-levels in more than 40 subjects) and we use their curricula in our study. At the A-Level, our reference was OCR, Computer Science, H446, Version 2.7, March 2024 [ 4 ], and at AS Level, OCR, Computer Science, H046, Version 1.5, February 2024 [ 3 ].

WALES The Welsh Joint Exam Committee (WJEC) [ 21 ], was established in 19481 and ofers over 400 internationally recognized GCSE, AS, A-level and vocational qualifications. The regulator, Qualifications Wales, decides on the subject content and the assessment rules for GCSEs, AS and A-levels. The AS and A-level CS qualifications, were introduced for first teaching from September 2015, and are available to all schools and colleges in Wales. In June 2023, 659 students sat the A-level CS 1In Welsh, WJEC is known as Cyd-bwyllgor Addysg Cymru (CBAC), and it also operates under the Eduqas brand. exam, with 31.6% of students achieving an A* or A grade. At A-Level and at AS Level we consulted the WJEC CBAC, GCE AS/A Level in Computer Science, Version 2, March 2019 specification document [ 7 ]. NORTHERN IRELAND The Council for the Curriculum, Examinations & Assessment (CCEA) [ 22 ] was established in 1994, and is funded by and responsible to the Department of Education. GCE A-levels are ofered at Level 3 on the Regulated Qualifications Framework (RQF). The AS and A-Level GCE courses in Digital Technology were first taught from September 2016. In the Summer of 2023, 596 students completed the subject at A-Level, with 34.2% achieving an A* or A grade. Students in Northern Ireland may also take examinations set by other UK boards such as OCR or AQA. For A-Level and AS Level, our guidance came from CCEA GCE Specification in Digital Technology, updated September 2019 [ 8 ]. SCOTLAND Unlike some other jurisdictions where schools can select from a range of examination bodies to present their students, the Scottish Qualifications Authority (SQA) [ 23 ] is the only body in Scotland2. Scottish Higher exams are a one year course, and students can use a second year of study to complete Advanced Highers. In the University of Edinburgh [ 25 ], for example, Advanced Highers are not required for entry (with the exception of medicine and veterinary medicine), but it is strongly recommended that students pursue their studies at a more advanced level by taking at least one subject at Advanced Higher. We consulted SQA, Advanced Higher Computing Science, C816 77, Version 3.1, September 2023 [ 6 ] at A-Level, and SQA, Higher Computing Science, C816 76, Version 3.0, May 2023 [ 5 ] at AS Level. IRELAND The State Examinations Commission [ 26 ] is responsible for the development, assessment, accreditation and certification of the second-level examinations of the Irish state: the Junior Cycle and the Leaving Certificate. The Junior Cycle concludes with a state assessment, formerly known as the Junior Certificate (JC), at Level 3 on the National Framework of Qualifications for Ireland (NFQ IE). The Senior Cycle ends with the Leaving Certificate (LC) exam, the results of which are used for university admission (Level 5 NFQ IE, Level 4 EQF). Exams are ofered at Ordinary and Higher level, and students typically complete 6 LC subjects at the end of their sixth year of secondary education. In 2018, the LC CS subject was rolled out in a pilot phase to 40 schools around Ireland [ 27 ]. In 2024, 2,470 students sat the Leaving Certificate Computer Science examination at Higher level with 16.3% achieving a H1 grade [ 26 ]. The Computer Science, Leaving Certificate, Ordinary and Higher Level, updated 2023 specification document [2] was our reference.

MALTA In Malta the Matriculation and Secondary Education Certificate (MATSEC) Examinations Board ofers examinations at two levels: Secondary Education Certificate (SEC) examinations and Matriculation examinations. The latter are ofered at Intermediate Matriculation (IM) and Advanced Matriculation (AM) levels. The IM level Computing is intended as a natural progression from SEC level and covers a portion of the AM level syllabus. An 18-year-old student in Malta typically sits for the Matriculation exams - this is at Level 4 on both the Malta Qualifications Framework (MQF) and the EQF. For AM Level, we referred to MATSEC Advanced Matriculation AM Syllabus 2025, Computing, AM 07 [ 9 ], and for IM Level purposes, we referred to MATSEC Intermediate Matriculation IM Syllabus 2025, Computing, IM 07 [ 10 ]. 148 students registered to sit for AM Computing in 2023 [ 28, 29, 30, 31 ]. WESTERN AUSTRALIA Senior secondary schooling in Western Australia covers students in Year 11 and Year 12, in which students typically complete the Western Australian Certificate of Education (WACE). Australian Tertiary Admission Rank (ATAR) courses and their exams contribute to the WACE, and are administered by the School Curriculum and Standards Authority (SCSA) [ 32 ]. In this study we referred to the SCSA Computer Science ATAR course [ 33 ] (a List B course [ 34 ]) which is organized into a Year 11 syllabus [ 33 ] and a Year 12 syllabus [ 35 ], both efective from January 2024. 2The Scottish Government has recently announced that SQA is to be replaced by a new qualifications body in 2025, which will also take on SQA’s current accreditation and regulation functions [ 24 ].

VALUES & ATTITUDES OUTCOME MAPPING Section 1 -Personal

SPECIFICATIONS LEARNING OUTCOMES SPECIFICATIONS LEARNING OUTCOMES E S W N M A I 1 Interest in ICT E S W N M A I 5 Critical thinking and reflection X X X X 1.1 Explores existing AI tools 5.1 Designs, develops and employs strategies for 1.2 Creates innovative solutions through AI tools solving real-life problems using computational thinking 2 Persistence/resilience 5.2 Explains how the programmers’ bias influences 2.1 Solves problems using programming methodology the fairness of AI rules 2.2 Tests and redesigns artefacts and products 5.3 Compares, analyses and critically evaluates information 3 Personal empowerment and digital content (e.g. to recognize manipulation) 3.1 Creates a project using design thinking 6 Entrepreneurship 3.2 Researches exposed private data on the internet 6.1 Uses design thinking methodology to 4 Reflection produce a prototype 4.1 Reflects on how ‘my personal future work’ 6.2 Develops awareness of entrepreneurship may be impacted by AI principles/processes to implement innovative ideas 4.2 Describes the role and importance of AI and its applications 4.3 Explores emerging technologies that have the potential to disrupt the way people live, learn and work

4. Results

Based upon Section 2 of the ’Values & Attitudes Outcome Mapping’ (p. 44) table in the UNESCO [ 1 ] AI curricula mapping framework. An X indicates whether the learning outcome is absent (neither expressly nor implicitly included) from selected upper secondary computer science specifications of England (E), Scotland (S), Wales (W), Northern Ireland (N), Malta (M),Western Australia (A) & Ireland (I). In Tables 2 to 11 we have identified those LOs that are not addressed (neither expressly nor implicitly included) in the specification documents, and they are symbolised by an X. While there are other LOs that are not thoroughly covered in the curricula, we aim to highlight those AI LOs that we found to be entirely overlooked. We discuss these findings under the three AI categories from the UNESCO framework: Knowledge, Skills, and Values & Attitudes.

Values and Attitudes: Across all regions, there is a common trend of under representation of values and attitudes related to AI in curricula (Table 2 to 5), particularly in the "Social" and "Societal" sections (see Table 3 and 4). This suggests that there is a broader need for educational systems to incorporate these LOs to ensure students not only develop technical skills but also cultivate a responsible and ethical mindset towards AI. For example, without addressing topics such as the environmental cost of AI or its potential to reinforce socioeconomic inequalities, students may lack the critical perspective needed to innovate responsibly or advocate for equitable policies.

VALUES & ATTITUDES OUTCOME MAPPING Section 3 - Societal

SPECIFICATIONS LEARNING OUTCOMES SPECIFICATIONS LEARNING OUTCOMES E S W N M A I 1 Respect for others E S W N M A I 3 Integrity 1.1 Engages respectfully with others 3.1 Understands methods of mitigating/lessening 1.2 Protects personal data and own/others’ privacy bias in AI algorithms 2 Personal responsibility X X X X X X 3.2 Designs an end-to-end ML process that X X X X X 2.1 Disposes of technology properly maximizes transparency and ensures fairness 2.2 Understands that humans control AI and ML 4 Tolerance

X X X 4.1 Shows tolerance for diferent ideas/positions grammatically controlling robots. Without exposure to these skills, students may struggle to grasp the practical applications of AI. In Table 7, large gaps persist consistently across all regions. Key topics such as chatbots, deep fakes, classifiers, and regression algorithms are underrepresented. This reflects a narrow focus within existing curricula which prioritizes general or high-level knowledge over hands-on, applied skills necessary for understanding and developing AI. This gap not only limits students’ ability to engage with real-world AI applications but also hinders their ability to critically analyze and respond to the implications of these technologies. Table 8 highlights significant gaps in addressing the ethical and societal impacts of AI across the curricula in the seven regions analyzed. These omissions include critical topics such as algorithmic bias, fairness, accountability, and transparency — issues that are increasingly pivotal as AI systems become more embedded in decision-making processes across sectors. S X X X X X X implicitly included) from selected upper secondary computer science specifications of England (E), Scotland (S), Wales (W), Northern Ireland (N), Malta (M),Western Australia (A) & Ireland (I).

SKILLS OUTCOME MAPPING Section 2 - Understanding, Using and Developing AI SPECIFICATIONS SPECIFICATIONS implicitly included) from selected upper secondary computer science specifications of England (E), Scotland (S), Wales (W), Northern Ireland (N), Malta (M),Western Australia (A) & Ireland (I). X X X X X X X X X

A X X X X X X X X X

I X X X X X X X X X 1 AI techniques 1.1 Classifies objects by characteristics 1.2 Constructs a decision tree (paper prototype) 1.3 Designs a workflow to train and test an AI algorithm 1.4 Cleans and prepares textual data for analysis and ML 1.5 Designs and tests supervised learning solutions for classification problems. 1.6 Uses open-source AI application frameworks to build simple intelligent systems 1.7 Interprets the performance of an ML model (e.g., using a confusion matrix) 1.8 Identifies whether various media products are GAN or not 1.9 Creates GANs in diferent subject areas (music, art, biology) 1.10 Creates a story and illustrations using GANs

E X X X X X X X X X X

S X X X X X X X X X

W X X X X X X X X X X

N X X X X X X X X X X

M X X X X X X X X X X X X

A X X X X X X X X X X X

I X X X X X X X 2 AI technologies 2.1 Builds and tests a classifier using a teachable machine or similar AI tool 2.2 Builds a chatbot with support 2.3 Constructs and controls a simple robot that can use AI 2.4 Programs an autonomous robot 2.5 Sets a new goal for an existing AI algorithm 2.6 Uses existing AI technologies to develop new products 2.7 Constructs and prepares a dataset for NLP processing 2.8 Creates a chatbot with appropriate human/bot interfaces 3 AI development 3.1 Works as part of a team 3.2 Uses design thinking methodology to implement a project as part of a team 3.3 Creates innovative solutions through AI tools 3.4 Manages a technology-development project 3.5 Verifies the correctness of the technological solutions applied X X 2.2 Representations and simulations 2.2.1 Understands rule-based reasoning 2.2.2 Develops an awareness of iterative processes in creating artefacts 2.2.3 Develops knowledge of simulations/ models/computational abstractions of real-world physical systems 2.2.4 Reflects on the limits and possibilities of simulations 3 Contextual problem-solving 3.1.1 Discusses and assesses the power and applicability of various AI approaches to practical problems 4 Data Literacy 4.1.1 Understands data trends 4.1.2 Understands the principles and processes of data collection and simple analysis 4.1.3 Understands how to collect, process, analyse, and report using data 4.1.4 Understands the types of sources of information 4.1.5 Describes the basic structure of a table in a spreadsheet 4.1.6 Describes the characteristics of data and information 4.1.7 Assesses the capabilities of big-data management (e.g. warehousing processes) 4.1.8 Discusses the advantages and disadvantages of big-data cloud storage 4.1.9 Compares structured and unstructured data 4.1.10 Explores encoding techniques to represent data eficiently 4.1.11 Develops an awareness of how the transformation and presentation of of large datasets through visualization/ modelling can be used for decision-making Based upon Section 2 of the ’Knowledge Outcome Mapping’ (p. 39 - 41) table in the UNESCO [ 1 ] AI curricula mapping framework. An X indicates whether the learning outcome is absent (neither expressly nor implicitly included) from selected upper secondary computer science specifications of England (E), Scotland (S), Wales (W), Northern Ireland (N), Malta (M),Western Australia (A) & Ireland (I).

Knowledge: The data in Tables 9 to 11 shows a consistent lack of coverage of advanced AI concepts such as machine learning and the application of algorithms in everyday contexts. This uniform weakness suggests that while foundational CS concepts might be addressed, there is a significant need for curricular updates to incorporate more advanced AI topics. Without these updates, students in these regions might be under prepared for future advancements and careers in AI-related fields, as well as for understanding and addressing the profound impact AI has on society. In this area, the ’Digital Technology’ curriculum from Northern Ireland addresses more AI LOs than those of the other six regions (particularly in the areas ”Understanding, Using, and Developing AI” and ”Ethics and Social Impact” - Table 10 and 11).

5. Conclusion

The study presented in this paper contributes to global AI education by supporting the development of efective AI content and teaching strategies in upper secondary education. Our analysis highlights the widespread absence of key AI learning outcomes—such as those related to advanced data structures, ethical considerations, and practical applications—in national curricula, which raises concerns. In every region, crucial knowledge, skills, and values & attitudes relating to the social implications of AI is also missing, which underscores the necessity for curriculum updates to ensure students are adequately equipped with essential AI knowledge and skills, preparing them for the evolving technological landscape. This paper highlights a lack of uniformity in the approach to AI education across these 7 regions, with a particular need for enhanced focus on the practical, social and ethical dimensions of AI technologies. X X X X X X X X X

X X X X X X X X X X X X X X X X X X X X Based upon Section 3 of the ’Knowledge Outcome Mapping’ (p. 39 - 41) table in the UNESCO [ 1 ] AI curricula mapping framework. An X indicates whether the learning outcome is absent (neither expressly nor implicitly included) from selected upper secondary computer science specifications of England (E), Scotland (S), Wales (W), Northern Ireland (N), Malta (M),Western Australia (A) & Ireland (I). * 3.4.3 Cited by the MIT DAILy Curriculum as: ‘Invokes emotion; polarization; spreading conspiracy theories; deflecting blame; impersonating or fake accounts; and “trolling” people online’

6. Acknowledgments

This publication has emanated from research conducted with the financial support of Science Foundation Ireland under Grant number 18/CRT/6183 and Huawei Ireland.

Organization, Paris, France. Catalog Number 0000380602. //unesdoc.unesco.org/ark:/48223/pf0000380602, United Nations Educational, Scientific and Cultural [2] National Council for Curriculum and Assessment and the Department of Education, Computer Science Curriculum Specification, Leaving Certificate, Ordinary and Higher Level, up

References

[1] UNESCO , K-12 AI curricula. A Mapping of Government-Endorsed AI Curricula , 2022 . URL: https: dated 2023 , https://www.curriculumonline.ie/getmedia/cf6eb86-9f8 - 4e68 - abf9-e42ca637492d/ Computer-Science-Final-Specification.pdf, 2023 .

[3] Oxford, Cambridge and RSA, AS Level GCE - Computer Science ( H046) For first assessment in 2016, Version 1 .5 ( February 2024 ), https://www.ocr.org.uk/Images/ 170845-specification -accredited-as-level-gce-computer-science-h046 .pdf, 2024 .

[4] Oxford, Cambridge and RSA, A Level GCE - Computer Science ( H446) For first assessment in 2017, Version 2 .7 (March 2024 ), http://www.ocr.org.uk/Images/ 170844-specification -accredited-a-level-gce-computer-science-h446 .pdf, 2024 .

[5] Scottish Qualifications Authority , Course Specification: Computing Science, https://www.sqa.org. uk/sqa/files_ccc/h-course -spec-computing-science .pdf, 2024 .

[6] Scottish Qualifications Authority , Advanced Higher Computing Science Course Specification , https://www.sqa.org.uk/sqa/files_ccc/ah -course-spec-computing-science .pdf, 2024 .

[7] Welsh Joint Exam Committee , WJEC CBAC , GCE AS /A Level in Computer Science, Version 2, March 2019 , https://www.wjec.co.uk/media/wl4kj5l1/wjec -gce-computer-science-spec-from-2015 . pdf, 2019 .

[8] Council for the Curriculum, Examinations & Assessment, CCEA GCE Specification in Digital Technology , updated September 2019 , Subject Code: 2650 , 2019 . URL: https://ccea.org.uk/downloads/docs/Specifications/GCE/GCE%20Digital% 20Technology % 20 % 282016 %29/GCE%20Digital% 20Technology % 20 % 282016 % 29 -specification-Standard.pdf.

[9] Matriculation and Secondary Education Certificate Examinations Board , University of Malta, MATSEC Advanced Level AM Syllabus 2025 Computing AM07 , https://www.um.edu.mt/media/ um/docs/directorates/matsec/syllabi/2025/am/Syllabus-AM07Computing2025.pdf, nd.

[10] Matriculation and Secondary Education Certificate Examinations Board , University of Malta, MATSEC Intermediate Level IM Syllabus 2025 Computing IM07 , https://www.um.edu.mt/media/ um/docs/directorates/matsec/syllabi/2025/im/IM072025.pdf, nd.

[11] School Curriculum and Standards Authority, SCSA Computer Science ATAR Year 11 Syllabus from January 2024 , https://senior-secondary.scsa.wa.edu.au/__data/assets/pdf_file/0011/1089785/ Computer-Science -ATAR-Year- 11- Syllabus-for-teaching-from-January-2024_pdf .PDF, 2024 .

[12] School Curriculum and Standards Authority, SCSA Computer Science ATAR Year 12 Syllabus for teaching from January 2024 , https://senior-secondary.scsa.wa.edu.au/__data/assets/pdf_file/0004/ 1089787/Computer-Science -ATAR-Year- 12- Syllabus-for-teaching-from-January-2024_pdf .PDF, 2024 .

[13] J. J. Benjamin , J. Lindley , E. Edwards , E. Rubegni, T. Korjakow , D. Grist , R. Sharkey , Responding to Generative AI Technologies with Research-through-Design: The Ryelands AI Lab as an Exploratory Study , in: Proceedings of the 2024 ACM Designing Interactive Systems Conference, DIS '24 , Association for Computing Machinery, New York, NY, USA, 2024 , p. 1823 - 1841 . doi: 10 .1145/ 3643834.3660677.

[14] F. Jetzinger , S. Baumer , T. Michaeli, Artificial Intelligence in Compulsory K-12 Computer Science Classrooms: A Scalable Professional Development Ofer for Computer Science Teachers , in: Proceedings of the 55th ACM Technical Symposium on Computer Science Education V. 1 , SIGCSE 2024 , Association for Computing Machinery , New York, NY, USA, 2024 , p. 590 - 596 . URL: https: //doi.org/10.1145/3626252.3630782. doi: 10 .1145/3626252.3630782.

[15] G. Elliott , Method in our madness? The Advantages and Limitations of Mapping Other Jurisdictions' Educational Policy and Practice ( 2014 ). URL: https://doi.org/10.17863/CAM.100304.

[16] Europass , European Union , The European Qualifications Framework, https://europass.europa.eu/en/europass -digital-tools/european-qualifications- framework , 2017 .

[17] Quality Assurance Agency for Higher Education (QAA), Qualifications Can Cross Boundaries: A Guide to Comparing Qualifications Frameworks in the UK and Ireland , https://www.qaa.ac.uk/ docs/qaa/quality-code/ qualifications-can-cross-boundaries .pdf, 2023 .

[18] Assessment and Qualifications Alliance, AQA - Education Charity Providing GCSEs, A-levels and Support ., 2024 . URL: https://www.aqa.org.uk/.

[19] Cambridge International, Cambridge International AS & A Levels, https://www. cambridgeinternational.org/programmes-and-qualifications/cambridge-advanced/ cambridge-international -as-and-a- levels , 2024 .

[20] Oxford, Cambridge and RSA, Who We Are, https://ocr.org.uk/about/who-we-are/, 2024 .

[21] Welsh Joint Exam Committee , WJEC - Welsh Joint Education Committee, https://www.wjec.co.uk/, 2020 .

[22] Council for the Curriculum, Examinations & Assessment, CCEA Oficial Website , https://ccea.org. uk/, 2024 .

[23] Scottish Government , Putting Learners at the Centre: Towards a Future Vision for Scottish Education , https://www.gov.scot/publications/ putting-learners -centre-towards-future- vision- scottish-education/pages/6/, 2022 .

[24] Scottish Qualifications Authority , National Qualifications - Highers , 2024 . URL: https://www.sqa. org.uk/sqa/100808.11353.html.

[25] University of Edinburgh, SQA Highers and Advanced Highers ., 2024 . URL: https://www.ed.ac.uk/ studying/undergraduate/entry-requirements/scottish-qualifications/highers.

[26] State Examinations Commission , State Examinations Commission - Ireland, https://www. examinations.ie/, 2024 .

[27] R. Faherty , K. Nolan , K. Quille , B. Becker , E. Oldham , A Brief History of K-12 Computer Science Education in Ireland., in: International Journal of Computer Science Education in Schools , 6 ( 1 ), 3 - 34 ., 2023 . URL: https://doi.org/10.21585/ijcses.v6i1. 148 .

[28] University of Malta, MATSEC Examinations Board About Us , 2020 . URL: https: //www.um.edu.mt/matsec/aboutus/#:~:text= The%20Matriculation%20Certificate%20is%20the, the%20Humanities%20and%20the%20Sciences.

[29] MATSEC Examinations Board , Examiners' Report Advanced Computing Main Session 2023 , 2023 . URL: https://www.um.edu.mt/matsec/reportscommunication/examinersreports/ advanced-matriculationcertificate/ 2023 /.

[30] MATSEC Examinations Board G˙ . F. Abela Junior , College Matriculation Course Standard Find Out More , 2020 . URL: https://www.jc.um.edu.mt/study/programmes/matriculationcoursestandard.

[31] Malta Further & Higher Education Authority , Malta Qualifications Database , 2024 . URL: https: //qualifications.mfhea.gov.mt/#/dashboard.

[32] School Curriculum and Standards Authority , Public Information Statement. Document Number: 2019 /22020[v9], 2023 . URL: https://www.scsa.wa.edu.au/about-us/about-scsa.

[33] School Curriculum and Standards Authority, Computer Science ATAR Course Year 11 syllabus , 2023 . URL: https://senior-secondary.scsa.wa.edu.au/syllabus-and - support-materials/technologies/ computer-science.

[34] School Curriculum and Standards Authority, SCSA WACE Manual 2024 . General Information for Senior Secondary Schooling 2023 / 49640 [v6], 2023 . URL: https://www.scsa.wa.edu.au/publications/ wace-manual.

[35] School Curriculum and Standards Authority, Computer Science ATAR Course Year 12 syllabus , 2023 . URL: https://senior-secondary.scsa.wa.edu.au/syllabus-and - support-materials/technologies/ computer-science.