ГРАМОТНОСТ ЗА РАБОТА С ИЗКУСТВЕН ИНТЕЛЕКТ В ПРОФИЛИРАНАТА ПОДГОТОВКА ПО ИНФОРМАТИКА — ДИАГНОСТИКА НА ПОТРЕБНОСТИТЕ И ПРЕГЛЕД НА РАМКОВИТЕ ДОКУМЕНТИ

Таня Христова Евтимова¹, Марияна Иванова Николова²
¹ППМГ „Акад. Никола Обрешков“, Бургас
²Великотърновски университет „Св. св. Кирил и Методий“, Велико Търново

AI LITERACY IN PROFILED INFORMATICS EDUCATION – NEEDS DIAGNOSIS AND REVIEW OF FRAMEWORK DOCUMENTS

Tanya Hristova Evtimova¹, Mariyana Ivanova Nikolova²
¹High School of Mathematics and Natural Sciences “Acad. Nikola Obreshkov”
²St. Cyril and St. Methodius University of Veliko Tarnovo, Veliko Tarnovo

* Авторите изказват благодарност към научен проект ФСД-31-354/28.04.2026 – Анализ на възможностите за приложения на креативните компютърни технологии в науката, бизнеса и образованието за частичното финансиране на настоящата работа.

Abstract: This paper reports on AI literacy among students studying Informatics in a Bulgarian high school and reviews current AI literacy frameworks. The survey reveals that students demonstrate extensive but uncritical AI use, with evidence of „metacognitive laziness“ [1] and emerging dependency on AI-generated outputs. The paper reviews UNESCO’s AI Competency Framework for Students, DigComp 3.0, the OECD/EC AILit framework, and the draft framework of the Bulgarian Ministry of Education and Science. While all four frameworks share a common conceptual foundation, they differ in their level of specialization. The paper concludes that specific AI competencies for profiled Informatics education are needed, and that their development requires a differentiation of Informatics from related subjects as IT.

Keywords: AI literacy, Informatics, generative AI, digital competence frameworks, metacognitive laziness

References:

1. Fan, Y., Tang, L., Le, H., Shen, K., Tan, S., Zhao, Y., Shen, Y., Li, X., Gašević, D., Beware of metacognitive laziness: Effects of generative artificial intelligence on learning motivation, processes and performance. British Journal of Educational Technology, 56(2), 489–530, 2025. https://doi.org/10.1111/bjet.13544
2. Gašević, D. & Yan, L., Generative AI for human skill development and assessment: implications for existing practices and new horizons. In OECD (Ed.), OECD Digital Education Outlook 2026: Exploring Effective Uses of Generative AI in Education. OECD Publishing, Paris, 2026. https://doi.org/10.1787/062a7394-en
3. Cosgrove, J. and Cachia, R., DigComp 3.0: European Digital Competence Framework – Fifth Edition. Publications Office of the European Union, Luxembourg, 2025. https://data.europa.eu/doi/10.2760/0001149 , JRC144121.

(Endnotes:)

1. OECD (2026), OECD Digital Education Outlook 2026: Exploring Effective Uses of Generative AI in Education, OECD Publishing, Paris, https://doi.org/10.1787/062a7394-en
2. OECD / European Union (2026). Empowering learners for the age of AI: An AI literacy framework for primary and secondary education. OECD Publishing, Paris. https://doi.org/10.1787/65cd27d4-en
3. MON. (2026). Viziya za vavezhdane i izpolzvane na izkustveniya intelekt v balgarskoto uchilishtno obrazovanie. Ministerstvo na obrazovanieto i naukata. https://www.mon.bg/nfs/2026/01/pr27012026_vizia-ai-strategyeducation.pdf
4. UNESCO. (2024). AI Competency Framework for Students. UNESCO. https://www.unesco.org/en/articles/aicompetency-framework-students
5. MON. (2026). Ramka za II gramotnost v uchilishtnoto obrazovanie. Ministerstvo na obrazovanieto i naukata. https://www.mon.bg/nfs/2026/03/pr_ramka-ii-gramotnost_25032026.pdf
6. MON. (2020). Uchebna programa po Informatika za XI i XII klas (Profilirana podgotovka) – https://web.mon.bg/upload/18364/profil-Informatika.pdf
7. MON. (2020). Uchebna programa po Informatsionni tehnologii za XI i XII klas (profilirana podgotovka) https://www.mon.bg/nfs/2018/12/profil-it.pdf

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