МОДЕЛЬ ВИКОРИСТАННЯ ШТУЧНОГО ІНТЕЛЕКТУ ТА CHATGPT ДЛЯ ПЕРСОНАЛІЗАЦІЇ НАВЧАННЯ У ВИЩІЙ ОСВІТІ
Анотація
Штучний інтелект швидко імплементується в процеси навчання студентів впродовж 2022-2024 рр., як в Україні, так і в усьому світі, що визначає актуальність розроблення політик, правил, моделей його використання. Метою статті є побудова моделі використання штучного інтелекту та інструменту ChatGPT для персоналізації навчання у вищій освіті. Проаналізовано концепцію персоналізованого навчання. Систематизовано ознаки, які відрізняють персоналізовану освіту від традиційної. Виявлено, що персоналізоване навчання має гнучкий, інтерактивний та індивідуально-адаптивний характер. Впровадження ШІ дозволяє централізувати роль студента в освітній системі та адаптувати навчальний процес відповідно до його цілей, інтересів та потреб. Такий підхід сприяє підвищенню ефективності підготовки студента в якості майбутнього учасника ринку праці, одночасно забезпечуючи розвиток його соціально-психологічних якостей. Проаналізовано за допомогою бінарного методу оцінки вплив інструментів штучного інтелекту на персоналізацію навчання. Аргументовано вплив штучного інтелекту на персоналізацію навчання як середнього рівня (72,7% впливу). Доведено, що інструментарій штучного інтелекту задовольняє більшість основних потреб персоналізованого навчання. Запропоновано модель використання штучного інтелекту та ChatGPT для персоналізації навчання у вищій освіті, що складається з трьох взаємопов’язаних блоків: процес навчання, інтеграція ШІ та результати навчання. Сформовано основні групи стратегії персоналізації навчання (група стратегій за рівнем персоналізації навчання; група стратегій за методами взаємодії зі студентами; група стратегій за масштабом впровадження штучного інтелекту; група стратегій залежно від цілей впровадження штучного інтелекту). Стратегії інтеграції штучного інтелекту концентруються на підвищенні академічної успішності, задоволеності студентів, розробленні специфічних освітніх продуктів. Обґрунтування вибору стратегії імплементації штучного інтелекту в навчальний процес і освітнє середовище вищого навчального закладу визначається цілями трансформації освітнього процесу та готовності до впровадження новітніх технологій.
Посилання
Chegg.org (2023) Global Student Survey 2023. Available at: https://8dfb1bf9-2f43-45af-abce-2877b9157e2c.usrfiles.com/ugd/8dfb1b_e9bad0aef091478397e6a9ff96651f6d.pdf (accessed July 09, 2024)
Rui D. (2023) Surge in Chinese Students Using AI for Academic Edge: New Survey. Sixth Tone. Available at: https://www.sixthtone.com/news/1014132 (accessed July 09, 2024)
von Garrel J., & Mayer J. (2023) Artificial Intelligence in studies—use of ChatGPT and AI-based tools among students in Germany. Humanities and Social Sciences Communications, vol. 10(799). Available at: https://doi.org/10.1057/s41599-023-02304-7 (accessed July 09, 2024)
Neves J., Freeman J., Stephenson R., Sotiropoulou D. P. (2024) Student Academic Experience Survey 2024. Advance HE, HEPI. Available at: https://s3.eu-west-2.amazonaws.com/assets.creode.advancehe-document-manager/documents/advance-he/Student%20Academic%20Experience%20Survey%202024_1718100686.pdf (accessed July 10, 2024)
Digital Care (2023) Wyniki badania: "Technologia okiem studenta" – jak korzysta z elektroniki oraz AI? Focus On Business. Available at: https://focusonbusiness.eu/pl/wiadomosci/wyniki-badania-technologia-okiem-studenta-jak-korzysta-z-elektroniki-oraz-ai/30494 (accessed July 10, 2024)
Compilatio, Le Sphinx polling institute (2023) Press release Nov. 2023 – Survey results: lecturers and students confront their views on AI. Compilatio. Available at: https://www.compilatio.net/en/blog/press-release-ai-survey-2023 (accessed July 11, 2024)
Samaieva Y. (2023) Stavlennia ukraintsiv do shtuchnoho intelektu na dyvo lehkovazhne. Darma [The attitude of Ukrainians toward artificial intelligence is surprisingly lighthearted. It's a shame]. ZN.UA. Available at: https://zn.ua/ukr/TECHNOLOGIES/stavlennja-ukrajintsiv-do-shtuchnoho-intelektu-na-divo-lehkovazhne-darma.html (accessed July 12, 2024)
Kaminskyi B. (2024) Chy vidbere ShI robotu u maibutnikh aitivtsiv: opytuvannia EPAM University [Will AI take away jobs from future IT professionals: EPAM University survey]. Speka. Available at: https://speka.media/ci-vidbere-si-robotu-u-maibutnix-aitivciv-opituvannya-eram-university-vzddzg (accessed July 12, 2024)
Bloom B. S. (1984) The 2 Sigma Problem: The Search for Methods of Group Instruction as Effective as One-to-One Tutoring. Educational Researcher, vol. 13(6), pp. 4–16. Available at: https://web.mit.edu/5.95/www/readings/bloom-two-sigma.pdf (accessed April 29, 2024)
Shemshack A., & Spector J. M. (2020) A systematic literature review of personalized learning terms. Smart Learning Environments, vol. 7(33), pp 1–20. DOI: https://doi.org/10.1186/s40561-020-00140-9 (accessed April 29, 2024).
Tkachuk H. V. (2021) Model realizatsii personalizovanoho navchannia studentiv zakladu vyshchoi osvity [Model of realization of personalized learning of students of higher education institution]. Engineering and Educational Technologies, vol. 9(3), pp. 8-17. Available at: https://dspace.udpu.edu.ua/bitstream/123456789/14222/1/EETECS2021_009(3)_001.pdf (accessed April 29, 2024).
Chemerys O. A., & Kibenko L. M. (2024) Personalizatsiia navchannia yak umova pidvyshchennia yakosti profesiinoi pidhotovky [Personalization of training as a condition for improving the quality of professional training]. Naukovi doslidzhennia ta metodyka yikh provedennia: svitovyi dosvid ta vitchyzniani realii – 2024: VII Mizhnarodna naukovo-praktychna konferentsiia (Vinnytsia, Vienna, March 15th, 2024). Vinnytsia: Grail of Science, pp. 385–387. DOI: https://doi.org/10.36074/grail-of-science.15.03.2024.062 (accessed May 02, 2024)
Quandeng G. (2022) Pereosmyslennia personalizovanoi modeli navchannia [Rethinking the personalized learning model]. Akademichni studii. Seriia «Pedahohika» – Academic studies. Series "Pedagogy", vol. 4(17), pp. 117–121. DOI: https://doi.org/10.52726/as.pedagogy/2022.4.17 (accessed May 02, 2024)
Korchova H. (2022) Personalizovane navchannia yak naukovo-metodychna problema u profesiinii osviti [Personalized learning as scientific and methodological problem in professional education]. Visnyk Kremenchutskoho natsionalnoho universytetu imeni Mykhaila Ostrohradskoho – Bulletin of the Kremenchug National University named after Mikhail Ostrogradsky, vol. 5(8), pp. 61–65. DOI: https://doi.org/10.32782/1995-0519.2022.5.8 (accessed May 02, 2024)
Aslan A., Bakir I., & Vis I. F. A. (2020) A Dynamic Thompson Sampling Hyper-Heuristic Framework for Learning Activity Planning in Personalized Learning. European Journal of Operational Research, vol. 286(2), pp. 673–688. DOI: http://dx.doi.org/10.1016/j.ejor.2020.03.038 (accessed May 02, 2024)
Digital Defynd (2024) Personalized Learning vs Traditional Learning. Available at: https://digitaldefynd.com/IQ/personalized-learning-vs-traditional-learning/ (accessed July 12, 2024)
Felder R. M., & Silverman L. (1988) Learning and Teaching Styles in Engineering Education. Journal of Engineering Education, vol. 78 (7), pp. 674–681. Available at: https://www.researchgate.net/publication/257431200_Learning_and_Teaching_Styles_in_Engineering_Education (accessed April 21, 2024)
King M. R. N., Rothberg S. J., Dawson R. J., & Batmaz F. (2016) Bridging the edtech evidence gap: A realist evaluation framework refined for complex technology initiatives. Journal of Systems and Information Technology, vol. 18(1), pp. 18–40. DOI: https://doi.org/10.1108/JSIT-06-2015-0059 (accessed July 08, 2024)
Sosa-Diaz M. J., Sierra-Daza M. C., Arriazu-Muñoz R., Llamas-Salguero F., & Duran-Rodriguez N. (2022) “EdTech Integration Framework in Schools”: Systematic Review of the Literature. Frontiers Education, vol. 7(895042), pp. 1–14. DOI: https://doi.org/10.3389/feduc.2022.895042 (accessed July 08, 2024)
Januszewski A., & Molenda M. (2007) Educational Technology: A Definition with Commentary (2nd. ed.). New York, Oxford: Routledge, p. 384. Available at: https://books.google.com.ua/books?id=0KnYIgZfxRwC&printsec=frontcover&hl=uk#v=onepage&q&f=false (accessed July 08, 2024)
Corbeil J. R., & Corbeil M. E. (2013) What do educational technologists do? The discipline as defined by educational technology practitioners. Issues in Information Systems, vol. 14(2), pp. 336–345. DOI: https://doi.org/10.48009/2_iis_2013_336-345 (accessed July 08, 2024)
Tymoshchuk T. Geniusee (2022) Education Technology: A Complete Guide to EdTech. Available at: https://geniusee.com/single-blog/education-technology-a-complete-guide-to-edtech (accessed May 11, 2024)
Raja R., & Nagasubramani P. C. (2018) Impact of modern technology in education. Journal of Applied and Advanced Research, vol. 3(1), pp. 33–35. DOI: https://doi.org/10.21839/jaar.2018.v3is1.165 (accessed May 10, 2024)
Herold B. (2016) Technology in Education: An Overview. Education Week. Available at: https://www.edweek.org/technology/technology-in-education-an-overview/2016/02 (accessed May 16, 2024)
Schmid R., Pauli C., Stebler R., Reusser K., & Petko D. (2022) Implementation of technology-supported personalized learning–its impact on instructional quality. The Journal of Educational Research, vol. 115(3), pp. 187–198. Available at: https://doi.org/10.1080/00220671.2022.2089086 (accessed May 17, 2024)
Major L., Francis G. A., & Tsapali M. (2021) The effectiveness of technology‐supported personalised learning in low‐ and middle‐income countries: A meta‐analysis. British Journal of Educational Technology, vol. 52(5), pp. 1935–1964. Available at: https://doi.org/10.1111/bjet.13116 (accessed May 10, 2024)
Bartolomé A., Castañeda L., & Adell J. (2018) Personalisation in educational technology: the absence of underlying pedagogies. International Journal of Educational Technology in Higher Education, vol. 15(14), pp. 1–17. DOI: https://doi.org/10.1186/s41239-018-0095-0 (accessed May 11, 2024)
Maher J. K. O. J. (2023) Personalized learning through AI. Advances in Engineering Innovation, vol. 5(1), pp. 16–19. DOI: http://dx.doi.org/10.54254/2977-3903/5/2023039 (accessed July 09, 2024)
Chen L. (2021) Application of Artificial Intelligence Technology in Personalized Online Teaching under the Background of Big Data. Journal of Physics: Conference Series, vol. 1744(4), pp. 1–6. DOI: http://dx.doi.org/10.1088/1742-6596/1744/4/042208 (accessed July 09, 2024)
Ayeni O. O., Hamad N. M. A., Chisom O. N., Blessing O., & Adewusi O. E. (2024) AI in education: A review of personalized learning and educational technology. GSC Advanced Research and Reviews, vol. 18(2), pp. 261–271. DOI: https://doi.org/10.30574/gscarr.2024.18.2.0062 (accessed July 09, 2024)
Tapalova O., & Zhiyenbayeva N. (2022) Artificial Intelligence in Education: AIEd for Personalised Learning Pathways. The Electronic Journal of e-Learning, vol. 20(5), pp. 639–653. DOI: https://doi.org/10.34190/ejel.20.5.2597 (accessed July 09, 2024)
Fitria T. N. (2021). Artificial intelligence (AI) in education: using AI tools for teaching and learning process. Prosiding Seminar Nasional & Call for Paper STIE AAS, vol. 4(1), pp. 134–147. Available at: https://prosiding.stie-aas.ac.id/index.php/prosenas/article/view/106 (accessed July 11, 2024)
Murtaza M., Ahmed Y., Shamsi J. A., Sherwani F., & Usman M. (2022) AI-Based Personalized E-Learning Systems: Issues, Challenges, and Solutions. IEEE Access, vol. 10, pp. 81323–81342. DOI: https://doi.org/10.1109/ACCESS.2022.3193938 (accessed July 11, 2024)
Pratama M. P., Sampelolo R., Lura H. (2023) Revolutionizing education: harnessing the power of artificial intelligence for personalized learning. Klasikal: Journal of Education, Language Teaching and Science, vol. 5(2), pp. 350–357. DOI: https://doi.org/10.52208/klasikal.v5i2.877 (accessed July 11, 2024)
Demianenko V. M. (2020) Model adaptyvnoi navchalnoi systemy informatsiinoho prostoru vidkrytoi osvity [The model for adaptive learning systems of open education information environment]. Informatsiini tekhnolohii i zasoby navchannia – Information technologies and learning tools, vol. 77(3), pp. 27–38. DOI: http://dx.doi.org/10.33407/itlt.v77i3.3603 (accessed July 11, 2024)
Viznyuk I. M., Buhlai N. M., Kutsak L. V., Polishchuk A. S., & Kylyvnyk V. V. (2021) Vykorystannia shtuchnoho intelektu v osviti [Use of artificial intelligence in education]. Suchasni informatsiini tekhnolohii ta innovatsiini metodyky navchannia v pidhotovtsi fakhivtsiv:metodolohiia, teoriia, dosvid, problem – Modern Information Technologies and Innovation Methodologies of Education in Professional Training Methodology Theory Experience Problems, vol. 59(1), pp. 14–22. DOI: https://doi.org/10.31652/2412-1142-2021-59-14-22 (accessed July 11, 2024)
Kilchenko A. V. (2023) Rol tekhnolohii shtuchnoho intelektu u naukovo-pedahohichnii diialnosti osvitnikh zakladiv The Role of Artificial Intelligence [Technologies in the scientific and pedagogical activities of educational institutions]. Tsyfrova osvita: suchasni realii ta perspektyvy rozvytku – 2023: Materialy Vseukrainskoi naukovo-praktychnoi konferentsii (Zaporizhzhia, October 26th, 2023). Zaporizhzhia: Zaporizhzhia Regional Institute of Postgraduate Pedagogical Education, pp. 1–9. Available at: https://lib.iitta.gov.ua/id/eprint/737700/1/%D0%9A%D1%96%D0%BB%D1%8C%D1%87%D0%B5%D0%BD%D0%BA%D0%BE%20%D0%90.%D0%92._%D1%82%D0%B5%D0%B7%D0%B8_%D0%97%D0%B0%D0%BF%D0%BE%D1%80%D1%96%D0%B6%D0%B6%D1%8F.pdf (accessed July 12, 2024)
Ali L., Sorrentino C., Martiniello L. (2023) Personalized learning in the era of digital learning and artificial intelligence: futuristic perspectives and challenges. Giornale Italiano di Educazione alla Salute, Sport eDidattica Inclusiva – Italian Journal of Health Education, Sports and Inclusive Didactics, vol. 7(1), pp. 1–20. DOI: http://dx.doi.org/10.32043/gsd.v7i1.856 (accessed July 12, 2024)
Drach, I., Petroye, O., Borodiyenko, O., Reheilo, I., Bazeliuk, O., Bazeliuk, N., & Slobodianiuk, O. (2023) Vykorystannia shtuchnoho intelektu u vyshchii osviti [The Use of Artificial Intelligence in Higher Education]. Mizhnarodnyi naukovyi zhurnal «Universytety i liderstvo» – International Scientific Journal of Universities and Leadership, vol. 15, pp. 66–82. DOI: https://doi.org/10.31874/2520-6702-2023-15-66-82 (accessed March 29, 2024)
Foltynek T., Bjelobaba S., Glendinning I., Khan Z. R., Santos R., Pavletic P., & Kravjar J. (2023) ENAI Recommendations on the ethical use of Artificial Intelligence in Education. International Journal for Educational Integrity, vol. 19(12). DOI: https://doi.org/10.1007/s40979-023-00133-4 (accessed April 12, 2024)
Chiu T. K. F., Xia, Q., Zhou X., Chai C. S., & Cheng M. (2023) Systematic literature review on opportunities, challenges, and future research recommendations of artificial intelligence in education. Computers and Education: Artificial Intelligence, vol. 4(100118), pp. 1–15. DOI: https://doi.org/10.1016/j.caeai.2022.100118 (accessed April 16, 2024)
Chan C. K.Y. (2023) A comprehensive AI policy education framework for university teaching and learning. International Journal of Educational Technology in Higher Education, vol. 20(38), pp. 1–25. DOI: https://doi.org/10.1186/s41239-023-00408-3 (accessed April 13, 2024)
Cardona M. A., Rodríguez R. J., & Ishmael K. (2023) Artificial Intelligence and the Future of Teaching and Learning. Washington: The U.S. Department of Education Office of Educational Technology’s, 67 p. Available at: https://tech.ed.gov/ai-future-of-teaching-and-learning/?trk=article-ssr-frontend-pulse_little-text-block (accessed April 02, 2024)
Marienko M., & Kovalenko V. (2023) Shtuchnyi intelekt ta vidkryta nauka v osviti [Artificial intelligence and open science in education]. Fizyko-matematychna osvita – Physical and Mathematical Education, vol. 38(1), pp. 48–53. DOI: https://doi.org/10.31110/2413-1571-2023-038-1-007 (accessed April 11, 2024)
Velibor B., & Indrasen P. (2023) Chat GPT and education. Pp. 1–8. DOI: https://doi.org/10.13140/RG.2.2.18837.40168 (accessed April 04, 2024)
Ushakova I. O., & Pedan O. A. (2020) Osoblyvosti vykorystannia shtuchnoho intelektu v osviti [Features of the use of artificial intelligence in education]. Informatsiini tekhnolohii ta systemy – 2020: Mizhnarodna naukovo-praktichna konferenciya (Kharkiv, April 9th-10th, 2020). Kharkiv: Simon Kuznets Kharkiv National University of Economics, p. 31. Available at: https://it.hneu.edu.ua/wp-content/uploads/2021/10/tezy-dopovidej-mizhnarodnoyi-naukovo-praktychnoyi-konferencziyi-informaczijni-tehnologiyi-ta-systemy-2020.pdf#page=31 (accessed March 14, 2024)
Sullivan M., Kelly A., & McLaughlan P. (2023) ChatGPT in higher education: Considerations for academic integrity and student learning. Journal of Applied Learning & Teaching, vol. 6(1), pp. 31–40. DOI: https://doi.org/10.37074/jalt.2023.6.1.17 (accessed April 04, 2024)
Palamar S., & Naumenko M. (2024) Shtuchnyi intelekt v osviti: vykorystannia bez porushennia pryntsypiv akademichnoi chesnosti [Artificial Intelligence in Education: Use Without Violating the Principles of Academic Integrity]. Osvitolohichnyi dyskurs – Educational discourse, vol. 1(44), pp. 68–83. DOI: https://doi.org/10.28925/2312-5829.2024.15 (accessed April 13, 2024)
Berdo R. S., Rasiun V. L., & Velychko V. A. (2023) Shtuchnyi intelekt ta yoho vplyv na etychni aspekty naukovykh doslidzhen v ukrainskykh zakladakh osvity [Artificial intelligence and its impact on ethical aspects of scientific research in Ukrainian educational institutions]. Akademichni vizii – Academic visions, vol. 22, pp. 1–10. DOI: https://doi.org/10.5281/zenodo.8174388 (accessed March 10, 2024)
Kulieshov S. O. (2023) Vplyv shtuchnoho intelektu na vyshchu osvitu Spoluchenykh Shtativ Ameryky [The impact of artificial intelligence on US higher education]. Tekhnolohii dobrochesnoho vykorystannia shtuchnoho intelektu u sferi osvity ta nauky – 2023: Vseukrainske naukovo-pedahohichne pidvyshchennia kvalifikatsii (Poltava, July 31st – September 10th, 2023). Odesa: Helvetyka, pp. 152–153. Available at: https://www.researchgate.net/profile/Nataliia-Furmanova/publication/377444350_VIKORISTANNA_STUCNOGO_INTELEKTU_DLA_PIDGOTOVKI_DO_ZANAT_NA_PRIKLADI_CHATGPT/links/65a7ab3dcc780a4b19c0019a/VIKORISTANNA-STUCNOGO-INTELEKTU-DLA-PIDGOTOVKI-DO-ZANAT-NA-PRIKLADI-CHATGPT.pdf#page=126 (accessed March 21, 2024)
Köbis L., & Mehner C. (2021) Ethical Questions Raised by AI-Supported Mentoring in Higher Education. Frontiers in Artificial Intelligence, vol. 4, pp. 1–9. DOI: https://doi.org/10.3389/frai.2021.624050 (accessed April 12, 2024)
Spivakovsky O. V., Omelchuk S. A., Kobets V. V., Valko N. V., & Malchykova D. S. (2023) Institutional policies on artificial intelligence in university learning, teaching and research. Information Technologies and Learning Tools, vol. 97(5), pp. 181–202. DOI: https://doi.org/10.33407/itlt.v97i5.5395 (accessed April 16, 2024)
Panukhnyk O. V. Shtuchnyi intelekt v osvitnomu protsesi ta naukovykh doslidzhenniakh zdobuvachiv vyshchoi osvity: vidpovidalni mezhi vmistu shtuchnoho intelektu [Artificial intelligence in the educational process and scientific research of higher education applicants: responsible boundaries of AI content]. Halytskyi ekonomichnyi visnyk – Galician economic journal, vol. 83(4), pp. 202–211. DOI: https://doi.org/10.33108/galicianvisnyk_tntu2023.04.202 (accessed March 09, 2024)
Bakhmat N. V. (2023) Shtuchnyi intelekt u vyshchii osviti: mozhlyvosti vykorystannia [Artificial intelligence in higher education: possibilities of using]. Pedahohichna osvita: teoriia i praktyka – Pedagogical Education: Theory and Practice, vol. 2(35), pp. 161–173. DOI: https://doi.org/10.32626/2309-9763.2023-161-173 (accessed April 12, 2024)
Jungherr A. (2023) Using ChatGPT and Other Large Language Model (LLM) Applications for Academic Paper Assignments. Bamberg: Otto-Friedrich-Universität, 48 p. Available at: https://nbn-resolving.org/urn:nbn:de:bvb:473-irb-589507 (accessed April 01, 2024)
Jürgen R., Samson T., & Shannon T. (2023) ChatGPT: Bullshit spewer or the end of traditional assessments in higher education?. Journal of Applied Learning & Teaching, vol. 6(1), pp. 342–363. DOI: https://doi.org/10.37074/jalt.2023.6.1.9 (accessed April 16, 2024)
Sodel O. (2023) Potentsial shtuchnoho intelektu u vyshchii osviti [The potential of AI in higher education]. Natsionalnyi universytet bioresursiv i pryrodokorystuvannia Ukrainy – National University of Life and Environmental Sciences of Ukraine. Available at: https://nubip.edu.ua/node/126807 (accessed March 16, 2024)
Mötteli C., Reusser K., Grob U., & Pauli C. (2023) The influence of personalized learning on the development of learning enjoyment. International Journal of Educational Research Open, vol. 5(100271), pp. 1–10. DOI: https://doi.org/10.1016/j.ijedro.2023.100271 (accessed July 14, 2024)
Dumont H., & Ready D. D. (2023) On the promise of personalized learning for educational equity. NPJ Sci Learn, vol. 8(26). DOI: https://doi.org/10.1038%2Fs41539-023-00174-x (accessed July 15, 2024)
Bruce F., Patrick S., Schneider C., & Ark T. V. (2017) What’s Possible with Personalized Learning? An Overview of Personalized Learning for Schools, Families & Communities. Vienna, VA: International Association for K-12 Online Learning (iNACOL), p. 28. Available at: https://aurora-institute.org/wp-content/uploads/iNACOL_Whats-Possible-with-Personalized-Learning.pdf (accessed July 15, 2024)
Çullhaj Dr. S. (2017) Key Features of Personalized Learning. European Journal of Multidisciplinary Studies, vol. 2(7), pp. 130–132. Available at: https://revistia.com/files/articles/ejms_v2_i7_17/Salian.pdf (accessed July 15, 2024)
Pane J. F., Steiner E. D., Baird M. D., & Hamilton L. S. (2015) Continued Progress: Promising Evidence on Personalized Learning. Santa Monica, CA: RAND Corporation, p. 52. Available at: https://www.rand.org/pubs/research_reports/RR1365.html (accessed July 15, 2024)
Johns S., Wolking M. (2018) The Core Four of Personalized Learning: The Elements You Need to Succeed. South San Francisco, California: Education Elements, p. 25. Available at: https://www.edelements.com/hubfs/Core_Four/Education_Elements_Core_Four_White_Paper.pdf (accessed July 15, 2024)
Yuyun I., & Suherdi D. (2023) Components and Strategies for Personalized Learning in Higher Education: A Systematic Review. ASIATEFL 2022, ASSEHR, vol. 749, pp. 271–290. DOI: http://dx.doi.org/10.2991/978-2-38476-054-1_23 (accessed July 15, 2024)
Hanover Research (2014) Best Practices in Personalized Learning Implementation. Arlington, VA: Hanover Research, p. 34. Available at: https://www.hanoverresearch.com/media/Best-Practices-in-Personalized-Learning-Implementation.pdf (accessed July 15, 2024)
Younas A., Subramanian K. P., Al-Haziazi M., Hussainy S. S., & Kindi A. N. S. A. (2023) A Review on Implementation of Artificial Intelligence in Education. International Journal of Research and Innovation in Social Science, vol. 7(8), pp. 1092–1100. DOI: https://doi.org/10.47772/ijriss.2023.7886 (accessed May 16, 2024)
Lake K. (2023) How To Personalize Learning Using AI. eLearning Industry. Available at: https://elearningindustry.com/how-to-personalize-learning-using-ai (accessed May 16, 2024)
Data Overload (2024) Personalized Learning and Skill Enhancement: Unleashing the Potential of AI in Education. Medium. Available at: https://medium.com/@data-overload/personalized-learning-and-skill-enhancement-unleashing-the-potential-of-ai-in-education-9b1f6af14bbd (accessed May 09, 2024)
AI transforms education industry. Data Science UA. Available at: https://data-science-ua.com/industries/ai-in-education/#pll_switcher (accessed July 16, 2024)
Shashank J. (2023) The Role of Technology in Education, Post Pandemic. eLearning Industry. Available at: https://elearningindustry.com/the-role-of-technology-in-education-post-pandemic (accessed May 16, 2024)
