Ключові слова
зворотний дизайн
східчасті завдання
автентичне оцінювання
розширене оцінювання
ЗСУВ підхід
академічна доброчесність
Як цитувати
Анотація
Швидкий розвиток генеративного штучного інтелекту зумовлює фундаментальну зміну парадигми оцінювання в освітньому процесі. Це ставить під сумнів обґрунтованість та об'єктивність традиційних методів перевірки знань. У цьому дослідженні
проаналізовано адаптацію класичної методології зворотного проєктування Г. Віггінса та Д. МакТайга як стратегічного інструменту переосмислення академічних дисциплін у відповідь на виклики цифровізації. Обґрунтовано доцільність переходу від контент-орієнтованого викладання до результатоцентрованого проєктування, що базується на пріоритетності
формування «тривалих розумінь» і складних компетентностей, які неможливо імітувати за допомогою репродуктивних знань чи алгоритмічних відповідей. Особливу увагу приділено синергії розуміння та самопізнання (пояснення, інтерпретації, застосування, перспективи, емпатії) в системі управління знаннями. Це дає змогу відокремити людський інтелект від
когнітивних патернів великих мовних моделей. Виокремлено три інноваційні стратегії оцінювання: впровадження «східчастих» чи поетапних завдань для візуалізації архітектури мислення; використання автентичного оцінювання в реальних професійних сценаріях; концепцію розширеного чи доповненого оцінювання, де штучний інтелект виступає
керованим когнітивним партнером. На основі порівняльного аналізу міжнародних практик та останніх Рекомендацій Міністерства освіти і науки України (2025) запропоновано практики переходу до методів «захисту логіки», симуляційного навчання та оцінювання процесу замість результату (на прикладах зі STEM-дисциплін, гуманітарних наук, медицини
та права). Необхідність відмови від концепції «карального виявлення» на користь стратегії «прозорого використання» технологій є критично важливою. Запропоновано підхід ЗСУВ до переформатування завдань. Успішна адаптація вищої освіти залежить від формування нової культури академічної доброчесності, де ШІ-грамотність стає невід’ємною частиною
професійної підготовки викладачів та здобувачів. Педагогічний дизайн має фокусуватися на розвитку критичного мислення, здатності до верифікації інформації та етичного використання інноваційних інструментів.
Посилання
Міністерство освіти і науки України. (2025). Рекомендації щодо відповідального впровадження та використання технологій штучного інтелекту в закладах вищої освіти. https://mon.gov.ua/static-objects/mon/sites/1/news/2025/04/24/shi-v-zakladakh-vyshchoi-osvity-24-04-2025.pdf
Родінова, Н. Л., Логай, В. А., & Ковальчук, М. Б. (2024). Імплементація штучного інтелекту в оцінювання якості української освіти: вплив на академічну доброчесність. Академічні візії, (29), 11(3), 101–108. https://www.academy-vision.org/index.php/av/article/download/978/880/890
Яворська, Г. В. (2023). Формувальне оцінювання під час викладання дисциплін спеціальності 091 Біологія. У .Зінченко, О. Ю., Ямборко, Г. В., & Іваниця, В. О. (Ред.). Проблеми та перспективи онлайн-навчання (Mатеріали методичного семінару в рамках XVIII Літньої школи «Молекулярна біологія, біотехнологія та біомедицина» 27 червня 2023 р.). Одеса: Одеський національний університет імені І. І. Мечникова (с. 33–36). https://dspace.hnpu.edu.ua/server/api/core/bitstreams/861df82d-c92f-49ff-9b85-616e1eb5b926/content
Яворська, Г. (2025). Штучний інтелект в освіті: партнерство, виклики та перспективи. Вісник Львівського університету. Серія педагогічна, (42), 149–161. http://dx.doi.org/10.30970/vpe.2025.42.13465
Alduais, A., Qadhi, S., Chaaban, Y., & Khraisheh, M. (2025). Utilizing Generative AI Responsibly and Ethically for Research Purposes in Higher Education: A Policy Analysis. Serials Review, 51 (3–4), 120–170. https://doi.org/10.1080/00987913.2025.2581429
Anthology. (2023). AI, academic integrity, and authentic assessment: An ethical path forward for education. University of Pittsburgh Research. https://www.research.pitt.edu/sites/default/files/assets/AI%2C%20Academic%20Integrity%2C%20and%20Authentic%20Assessment%20-%20An%20Ethical%20Path%20Forward%20for%20Education.pdf
Bilen, E., & Hervé, J. (2024). When AI gives bad advice: Critical thinking in human-AI collaborations. Available at SSRN. https://doi.org/10.2139/ssrn.5040466
Borges, B., Foroutan, N., Bayazit, D., Sotnikova, A., Montariol, S., Nazaretsky, T., Banaei, M., Sakhaeirad, A., Servant, P., Neshaei, S. P., Frej, J., Romanou, A., Weiss, G., Mamooler, S., Chen, Z., Fan, S., Gao, S., Ismayilzada, M., Paul, D., ... Bosselut, A. (2024). Could ChatGPT get an engineering degree? Evaluating higher education vulnerability to AI assistants. Proceedings of the National Academy of Sciences, 121(49), e2414955121. https://doi.org/10.1073/pnas.2414955121
Chien, A. A. (Ed.). (2021). Communications of the ACM, 64(3). Association for Computing Machinery. https://redes.fi-b.unam.mx/fi_acm/2021/communications202103-dl.pdf
Dockens, A. L., & Shelton, K. (2026). AI for formative and summative assessment: A balanced approach. In V. Wang (Ed.), Emerging Trends, Global Perspectives, and Systemic Transformation in AI (pp. 353–386). IGI Global Scientific Publishing. https://doi.org/10.4018/979-8-3373-5102-5.ch013
Doherty, C. E. (2024). A nuanced perspective on Harvard Business School’s jagged technological frontier. Lokad Blog. https://www.lokad.com/blog/2024/4/8/a-nuanced-perspective-on-jagged-technological-frontier/
East Carolina University. (n. d.). Backwards design. Teaching Toolkit. https://teachingtoolkit.ecu.edu/backwards-design/
Goff, L., & Dennehy, T. (2025, October 24). Case studies in learning and teaching. Toolkit for the Ethical Use of GenAI in Learning and Teaching. University College Cork. https://www.ucc.ie/en/ethical-use-of-generative-ai-toolkit/case-studies-in-learning-and-teaching/
Hicke, Y., Geathers, J., Rajashekar, N., Chan, C., Jack, A. G., Sewell, J., Preston, M., Cornes, S., Shung, D., & Kizilcec, R. (2025). MedSimAI: Simulation and formative feedback generation to enhance deliberate practice in medical education. arXiv. https://doi.org/10.48550/arXiv.2503.05793
Howell, R. W. (Ed.). (2025). ACMS Journal and Proceedings: 24th Biennial Conference (Vol. 24). Association of Christians in the Mathematical Sciences; Dordt University. https://acmsonline.org/wp-content/uploads/2025/05/journal-and-proceedings-2025.pdf
Hutson, J. (2025). From prohibition to preparation: Reframing academic integrity in the age of AI // MRS Journal of Arts, Humanities and Literature, 2(11), 54–65. https://digitalcommons.lindenwood.edu/faculty-research-papers/782/
Kickbusch, S., Ashford-Rowe, K., Kemp, A., Boreland, J., & Huijser, H. (2025). Beyond detection: Redesigning authentic assessment in an AI-mediated world. Education Sciences, 15(11), 1537. https://doi.org/10.3390/educsci15111537
Kofinas, A. K., Tsay, C. H.-H., & Pike, D. (2025). The impact of generative AI on academic integrity of authentic assessments within a higher education context. British Journal of Educational Technology, 56(6), 2522–2549. https://doi.org/10.1111/bjet.13585
Lorteau, S., & Sarro, D. (2025). Artificial intelligence in legal education: A scoping review. The Law Teacher. https://doi.org/10.2139/ssrn.5762982
McTighe, J. (2023). AI and understanding by design. McTighe & Associates Consulting. https://jaymctighe.com/ai-and-ubd/
Melliti, M. (2024). Using genre analysis to detect AI-generated academic texts. Diá-logos, 16(29), 9–27. https://doi.org/10.61604/dl.v16i29.377
Michigan State University. (2025). Guidelines for the use of generative artificial intelligence (Generative AI) tools. https://ai.msu.edu/guidelines
Millin, T., Millin, M., & Pearce, J. (2025). Asynchronous video-based scaffolding of English academic writing skills for distance tertiary students: An innovative approach to supporting postgraduate students in hybrid courses. Video Journal of Education and Pedagogy, 10(1). https://doi.org/10.1163/23644583-bja10062
MIT Sloan Teaching & Learning Technologies. (2024). 4 steps to design an AI-resilient learning experience. Massachusetts Institute of Technology. https://mitsloanedtech.mit.edu/ai/teach/4-steps-to-design-an-ai-resilient-learning-experience/
Moppett, S. A. (2025). Preparing students for the artificial intelligence era: The crucial role of critical thinking skills. Mitchell Hamline Law Review, 52(1). 7 https://open.mitchellhamline.edu/mhlr/vol52/iss1/7/
Quality Assurance Agency for Higher Education. (2023). Reconsidering assessment for the ChatGPT era: QAA advice on developing sustainable assessment strategies. https://www.qaa.ac.uk/docs/qaa/members/reconsidering-assessment-for-the-chat-gpt-era.pdf
Quidwai, S. (2023, June 7). AI and assessment: Why graduating with a LinkedIn portfolio is a must for every student. Designing Schools. https://designingschools.org/ai-and-assessment-why-graduating-with-a-linkedin-portfolio-is-a-must-for-every-student/
Reihanian, I., Hou, Y., & Sun, Q. (2026). From pilots to practices: A scoping review of GenAI-enabled personalization in computer science education. AI, 7(1), 6. https://doi.org/10.3390/ai7010006
Ritholz, E. (2025). Introducing the AI-Teaching Assistant (AITA) framework. Educational Technology, Hostos Community College. https://commons.hostos.cuny.edu/edtech/ai/aita/
Sangwa, S., Mutabazi, P., & Muvunyi, J. B. (2025). AI-enabled framework for program and course design in higher education [v1]. Preprints. https://doi.org/10.20944/preprints202512.0682.v1
Shaban, S., & Magzoub, M. E. (2025). Artificial Intelligence in medical education and assessment: The next step in the IT Revolution. F1000Research, 14, 1360. https://f1000research.com/articles/14-1360
Stapleton-Corcoran, E. (2023). Backward design. Center for the Advancement of Teaching Excellence, University of Illinois Chicago. https://teaching.uic.edu/cate-teaching-guides/syllabus-course-design/backward-design/
Tao, Z., Werry, I. P., Zeng, Z., & Miao, Y. (2024). The role and value of generative AI in medical education and training. International Journal of Information Technology (IntJIT), 29(1), 1–12. https://intjit.org/cms/journal/volume/29/1/291_4.pdf
University College Cork. (2025). Case studies in learning and teaching. Toolkit for the Ethical Use of GenAI in Learning and Teaching. https://www.ucc.ie/en/ethical-use-of-generative-ai-toolkit/case-studies-in-learning-and-teaching/
University of Houston-Downtown. (n.d.). Designing courses in the age of AI. Center for Teaching and Learning Excellence. https://www.uhd.edu/provost/teaching-learning-excellence/designing-courses-in-the-age-of-ai.aspx
University of Maine. (n. d.). Generative AI teaching and learning guidelines. Community Standards, Rights, and Responsibilities. https://umaine.edu/communitystandards/resources-policies-and-forms/generative-ai-teaching-and-learning-guidelines/
University of Saskatchewan. (2025, November). GenAI – Academic integrity. https://academic-integrity.usask.ca/gen-ai.php
University of Toronto. (n. d.). Backward design. Digital Learning Innovation. https://onlinelearning.utoronto.ca/backward-design/
Utomo, P. S., & Yan, J. (2025). The use of GenAI in medical education in China and Indonesia: A comparative literature review. Education for Health, (38). https://doi.org/10.62694/efh.2025.404
Wang, H., Dang, A., Wu, Z., & Mac, S. (2024). Generative AI in higher education: Seeing ChatGPT through universities’ policies, resources, and guidelines. Computers and Education: Artificial Intelligence, (7), 100326. https://doi.org/10.1016/j.caeai.2024.100326
Wenpang, L., Yingsoon, G. Y., Abdul Rahman, N. A. B., Abdullah, N. A. C. B., Suyan, Z., Yiming, C., & Xiaoyao, T. (2025). Revolutionizing vocational education. In Advances in Computational Intelligence and Robotics: Harnessing Transformational AI Tools for Enhanced Learning and Skill Development (pp. 209–240). IGI Global. https://doi.org/10.4018/979-8-3373-5102-5.ch008
Wiggins, G., & McTighe, J. (1998). Understanding by Design. https://books.google.com.cu/books?id=hL9nBwAAQBAJ&printsec=copyright&source=gbs_pub_info_r#v=onepage&q&f=false
Wiggins, G., & McTighe, J. (2005). Understanding by design (2nd Ed.). Association for Supervision and Curriculum Development (ASCD).
Alduais, A., Qadhi, S., Chaaban, Y., & Khraisheh, M. (2025). Utilizing Generative AI Responsibly and Ethically for Research Purposes in Higher Education: A Policy Analysis. Serials Review, 51 (3–4), 120–170. https://doi.org/10.1080/00987913.2025.2581429 (in English).
Anthology. (2023). AI, academic integrity, and authentic assessment: An ethical path forward for education. University of Pittsburgh Research. https://www.research.pitt.edu/sites/default/files/assets/AI%2C%20Academic%20Integrity%2C%20and%20Authentic%20Assessment%20-%20An%20Ethical%20Path%20Forward%20for%20Education.pdf (in English).
Bilen, E., & Hervé, J. (2024). When AI gives bad advice: Critical thinking in human-AI collaborations. Available at SSRN. https://doi.org/10.2139/ssrn.5040466
Borges, B., Foroutan, N., Bayazit, D., Sotnikova, A., Montariol, S., Nazaretsky, T., Banaei, M., Sakhaeirad, A., Servant, P., Neshaei, S. P., Frej, J., Romanou, A., Weiss, G., Mamooler, S., Chen, Z., Fan, S., Gao, S., Ismayilzada, M., Paul, D., ... Bosselut, A. (2024). Could ChatGPT get an engineering degree? Evaluating higher education vulnerability to AI assistants. Proceedings of the National Academy of Sciences, 121(49), e2414955121. https://doi.org/10.1073/pnas.2414955121 (in English).
Chien, A. A. (Ed.). (2021). Communications of the ACM, 64(3). Association for Computing Machinery. https://redes.fi-b.unam.mx/fi_acm/2021/communications202103-dl.pdf (in English).
Dockens, A. L., & Shelton, K. (2026). AI for formative and summative assessment: A balanced approach. In V. Wang (Ed.), Emerging Trends, Global Perspectives, and Systemic Transformation in AI (pp. 353–386). IGI Global Scientific Publishing. https://doi.org/10.4018/979-8-3373-5102-5.ch013 (in English).
Doherty, C. E. (2024). A nuanced perspective on Harvard Business School’s jagged technological frontier. Lokad Blog. https://www.lokad.com/blog/2024/4/8/a-nuanced-perspective-on-jagged-technological-frontier/ (in English).
East Carolina University. (n. d.). Backwards design. Teaching Toolkit. https://teachingtoolkit.ecu.edu/backwards-design/ (in English).
Goff, L., & Dennehy, T. (2025, October 24). Case studies in learning and teaching. Toolkit for the Ethical Use of GenAI in Learning and Teaching. University College Cork. https://www.ucc.ie/en/ethical-use-of-generative-ai-toolkit/case-studies-in-learning-and-teaching/ (in English).
Hicke, Y., Geathers, J., Rajashekar, N., Chan, C., Jack, A. G., Sewell, J., Preston, M., Cornes, S., Shung, D., & Kizilcec, R. (2025). MedSimAI: Simulation and formative feedback generation to enhance deliberate practice in medical education. arXiv. https://doi.org/10.48550/arXiv.2503.05793 (in English).
Howell, R. W. (Ed.). (2025). ACMS Journal and Proceedings: 24th Biennial Conference (Vol. 24). Association of Christians in the Mathematical Sciences; Dordt University. https://acmsonline.org/wp-content/uploads/2025/05/journal-and-proceedings-2025.pdf (in English).
Hutson, J. (2025). From prohibition to preparation: Reframing academic integrity in the age of AI // MRS Journal of Arts, Humanities and Literature, 2(11), 54–65. https://digitalcommons.lindenwood.edu/faculty-research-papers/782/ (in English).
Kickbusch, S., Ashford-Rowe, K., Kemp, A., Boreland, J., & Huijser, H. (2025). Beyond detection: Redesigning authentic assessment in an AI-mediated world. Education Sciences, 15(11), 1537. https://doi.org/10.3390/educsci15111537 (in English).
Kofinas, A. K., Tsay, C. H.-H., & Pike, D. (2025). The impact of generative AI on academic integrity of authentic assessments within a higher education context. British Journal of Educational Technology, 56(6), 2522–2549. https://doi.org/10.1111/bjet.13585 (in English).
Lorteau, S., & Sarro, D. (2025). Artificial intelligence in legal education: A scoping review. The Law Teacher. https://doi.org/10.2139/ssrn.5762982 (in English).
McTighe, J. (2023). AI and understanding by design. McTighe & Associates Consulting. https://jaymctighe.com/ai-and-ubd/ (in English).
Melliti, M. (2024). Using genre analysis to detect AI-generated academic texts. Diá-logos, 16(29), 9–27. https://doi.org/10.61604/dl.v16i29.377 (in English).
Michigan State University. (2025). Guidelines for the use of generative artificial intelligence (Generative AI) tools. https://ai.msu.edu/guidelines (in English).
Millin, T., Millin, M., & Pearce, J. (2025). Asynchronous video-based scaffolding of English academic writing skills for distance tertiary students: An innovative approach to supporting postgraduate students in hybrid courses. Video Journal of Education and Pedagogy, 10(1). https://doi.org/10.1163/23644583-bja10062 (in English).
Ministry of Education and Science of Ukraine. (2025). Recommendations for the Responsible Implementation and Use of Artificial Intelligence Technologies in Higher Education Institutions. https://mon.gov.ua/static-objects/mon/sites/1/news/2025/04/24/shi-v-zakladakh-vyshchoi-osvity-24-04-2025.pdf (in Ukrainian).
MIT Sloan Teaching & Learning Technologies. (2024). 4 steps to design an AI-resilient learning experience. Massachusetts Institute of Technology. https://mitsloanedtech.mit.edu/ai/teach/4-steps-to-design-an-ai-resilient-learning-experience/ (in English).
Moppett, S. A. (2025). Preparing students for the artificial intelligence era: The crucial role of critical thinking skills. Mitchell Hamline Law Review, 52(1). 7 https://open.mitchellhamline.edu/mhlr/vol52/iss1/7/ (in English).
Quality Assurance Agency for Higher Education. (2023). Reconsidering assessment for the ChatGPT era: QAA advice on developing sustainable assessment strategies. https://www.qaa.ac.uk/docs/qaa/members/reconsidering-assessment-for-the-chat-gpt-era.pdf (in English).
Quidwai, S. (2023, June 7). AI and assessment: Why graduating with a LinkedIn portfolio is a must for every student. Designing Schools. https://designingschools.org/ai-and-assessment-why-graduating-with-a-linkedin-portfolio-is-a-must-for-every-student/ (in English).
Reihanian, I., Hou, Y., & Sun, Q. (2026). From pilots to practices: A scoping review of GenAI-enabled personalization in computer science education. AI, 7(1), 6. https://doi.org/10.3390/ai7010006 (in English).
Ritholz, E. (2025). Introducing the AI-Teaching Assistant (AITA) framework. Educational Technology, Hostos Community College. https://commons.hostos.cuny.edu/edtech/ai/aita/ (in English).
Rodinova, N. L., Logai, V. A., & Kovalchuk, M. B. (2024). Implementation of artificial intelligence in assessing the quality of Ukrainian education: impact on academic integrity. Academy of Vision, 11(3), 101–108. https://www.academy-vision.org/index.php/av/article/download/978/880/890 (in Ukrainian).
Sangwa, S., Mutabazi, P., & Muvunyi, J. B. (2025). AI-enabled framework for program and course design in higher education [v1]. Preprints. https://doi.org/10.20944/preprints202512.0682.v1 (in English).
Shaban, S., & Magzoub, M. E. (2025). Artificial Intelligence in medical education and assessment: The next step in the IT Revolution. F1000Research, 14, 1360. https://f1000research.com/articles/14-1360 (in English).
Stapleton-Corcoran, E. (2023). Backward design. Center for the Advancement of Teaching Excellence, University of Illinois Chicago. https://teaching.uic.edu/cate-teaching-guides/syllabus-course-design/backward-design/ (in English).
Tao, Z., Werry, I. P., Zeng, Z., & Miao, Y. (2024). The role and value of generative AI in medical education and training. International Journal of Information Technology (IntJIT), 29(1), 1–12. https://intjit.org/cms/journal/volume/29/1/291_4.pdf (in English).
University College Cork. (2025). Case studies in learning and teaching. Toolkit for the Ethical Use of GenAI in Learning and Teaching. https://www.ucc.ie/en/ethical-use-of-generative-ai-toolkit/case-studies-in-learning-and-teaching/ (in English).
University of Houston-Downtown. (n.d.). Designing courses in the age of AI. Center for Teaching and Learning Excellence. https://www.uhd.edu/provost/teaching-learning-excellence/designing-courses-in-the-age-of-ai.aspx (in English).
University of Maine. (n. d.). Generative AI teaching and learning guidelines. Community Standards, Rights, and Responsibilities. https://umaine.edu/communitystandards/resources-policies-and-forms/generative-ai-teaching-and-learning-guidelines/ (in English).
University of Saskatchewan. (2025, November). GenAI – Academic integrity. https://academic-integrity.usask.ca/gen-ai.php (in English).
University of Toronto. (n. d.). Backward design. Digital Learning Innovation. https://onlinelearning.utoronto.ca/backward-design/ (in English).
Utomo, P. S., & Yan, J. (2025). The use of GenAI in medical education in China and Indonesia: A comparative literature review. Education for Health, (38). https://doi.org/10.62694/efh.2025.404 (in English).
Wang, H., Dang, A., Wu, Z., & Mac, S. (2024). Generative AI in higher education: Seeing ChatGPT through universities’ policies, resources, and guidelines. Computers and Education: Artificial Intelligence, (7), 100326. https://doi.org/10.1016/j.caeai.2024.100326 (in English).
Wenpang, L., Yingsoon, G. Y., Abdul Rahman, N. A. B., Abdullah, N. A. C. B., Suyan, Z., Yiming, C., & Xiaoyao, T. (2025). Revolutionizing vocational education. In Advances in Computational Intelligence and Robotics: Harnessing Transformational AI Tools for Enhanced Learning and Skill Development (pp. 209–240). IGI Global. https://doi.org/10.4018/979-8-3373-5102-5.ch008 (in English).
Wiggins, G., & McTighe, J. (1998). Understanding by Design. https://books.google.com.cu/books?id=hL9nBwAAQBAJ&printsec=copyright&source=gbs_pub_info_r#v=onepage&q&f=false (in English).
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