The Effectiveness of Using Artificial Intelligence in Folk Tale Learning
DOI:
https://doi.org/10.24256/ideas.v13i2.6310Keywords:
Artificial Intelligence, Folk Tale Learning, Adaptive StorytellingAbstract
The integration of artificial intelligence (AI) in folk tale learning represents a transformative educational approach, enhancing engagement, understanding, and accessibility. AI-driven platforms facilitate narrative comprehension by providing adaptive and interactive learning environments. Computational models of narrative ability enable AI systems to simulate human-like comprehension, adjusting storytelling elements based on learners' responses. Interactive storytelling tools further support language acquisition and critical thinking by allowing learners to influence narrative outcomes. Additionally, AI fosters inclusive education through accessibility features, such as audio descriptions and scaffolding strategies for diverse learners. AI-driven adaptive learning methodologies also enhance personalized learning experiences, catering to individual needs. Moreover, intelligent tutoring systems (ITS) provide real-time feedback, optimizing instructional strategies while allowing educators to focus on pedagogical development. By revolutionizing folk tale learning, AI enhances narrative engagement, supports second-language learning, and assists educators in instructional design. This study explores the effectiveness of AI in folk tale learning by analyzing engagement levels, comprehension improvements, and accessibility benefits. Findings suggest that AI enhances folk tale learning through personalized, interactive, and adaptive storytelling experiences, fostering greater learner participation and comprehension.
References
Abbas, N., Ali, I., Manzoor, R., Hussain, T., & Hussain, M. (2023). Role of artificial intelligence tools in enhancing students' educational performance at higher levels. Journal of Artificial Intelligence Machine Learning and Neural Network, (35), 36-49. https://doi.org/10.55529/jaimlnn.35.36.49
Abduh, N. K., & Masruddin, M. (2023). Structural Studies of Robert Stanton in The Folklore of Luwu (Worongporong dan Pariama). IDEAS: Journal on English Language Teaching and Learning, Linguistics and Literature, 11(1), 117-126.
Aggarwal, D., Sharma, D., & Saxena, A. (2023). Exploring the role of artificial intelligence for augmentation of adaptable sustainable education. Asian Journal of Advanced Research and Reports, 17(11), 179-184. https://doi.org/10.9734/ajarr/2023/v17i11563
Ai-jun, Y. (2024). On the influence of artificial intelligence on foreign language learning and suggested learning strategies. International Journal of Education and Humanities, 4(2), 107-120. https://doi.org/10.58557/(ijeh).v4i2.214
Akavova, A., Temirkhanova, Z., & Lorsanova, Z. (2023). Adaptive learning and artificial intelligence in the educational space. E3s Web of Conferences, 451, 06011. https://doi.org/10.1051/e3sconf/202345106011
Akimoto, T. (2016). Exploratory approach to the computational modeling of narrative ability for artificial intelligence. International Journal of Knowledge Engineering, 2(4), 170-176. https://doi.org/10.18178/ijke.2016.2.4.074
AlAfnan, M. (2024). Artificial intelligence and language: bridging arabic and english with technology. Journal of Ecohumanism, 3(8). https://doi.org/10.62754/joe.v3i8.4961
Al-Ajmi, N. (2016). Innovative applications for presenting heritage in the visual arts medium: a case study of the omani legends and stories exhibition. Journal of Arts and Social Sciences [Jass], 7(2), 83. https://doi.org/10.24200/jass.vol7iss2pp83-98
Alam, J. (2024). Folk media: preserving cultural narratives in the modern era. International Journal of Research Publication and Reviews, 5(1), 2838-2840. https://doi.org/10.55248/gengpi.5.0124.0306
Alkan, A. (2024). Artificial intelligence: its role and potential in education. İnsan Ve Toplum Bilimleri Araştırmaları Dergisi, 13(1), 483-497. https://doi.org/10.15869/itobiad.1331201
Aparicio-Gómez, O., Aparicio-Gómez, C., & Feigenblatt, v. (2024). Tejiendo conexiones: la simbiosis transformadora entre aprendizaje e inteligencia artificial. Hachetetepé Revista Científica De Educación Y Comunicación, (28). https://doi.org/10.25267/hachetetepe.2024.i28.1103
Awad, S., Mohamed, Y., & Shaheen, R. (2022). Applications of artificial intelligence in education. Al-Azkiyaa - Jurnal Antarabangsa Bahasa Dan Pendidikan, 1(1), 71-81. https://doi.org/10.33102/alazkiyaa.v1i1.10
Bahri, N., Itahriouan, Z., Abtoy, A., & Belhaouari, S. (2023). Using students’ digital written text in moroccan dialect for the detection of student personality factors. International Journal of Cognitive Research in Science Engineering and Education, 11(3), 389-400. https://doi.org/10.23947/2334-8496-2023-11-3-389-400
Cao, W., Wang, Q., Sbeih, A., & Shibly, F. (2020). Artificial intelligence based efficient smart learning framework for education platform. Inteligencia Artificial, 23(66). https://doi.org/10.4114/intartif.vol23iss66pp112-123
Castro, G., Chiappe, A., Rodriguez, D., & Sepúlveda, F. (2024). Harnessing ai for education 4.0: drivers of personalized learning. The Electronic Journal of E-Learning, 22(5), 01-14. https://doi.org/10.34190/ejel.22.5.3467
Chembe, C., Nasilele, N., & Msendo, R. (2023). The fuss about artificial intelligence in education sector: should we worry? Zambia Ict Journal, 7(2), 30-35. https://doi.org/10.33260/zictjournal.v7i2.269
d’Huy, J. (2019). Folk-tale networks: a statistical approach to combinations of tale types. Journal of Ethnology and Folkloristics, 13(1), 29-49. https://doi.org/10.2478/jef-2019-0003
Demianenko, O. and Moroz, T. (2024). Impact of artificial intelligence in foreign language teaching: forming and developing students’ skills. Věda a Perspektivy, (4(35)). https://doi.org/10.52058/2695-1592-2024-4(35)-191-199
Dewi, D. (2019). The representation of patriarchy in indonesian children’s folk tales from sumatra island. Lingua Cultura, 13(3), 167. https://doi.org/10.21512/lc.v13i3.5646
Estupiñán, S., Andkjær, K., & Szilas, N. (2018). Engagement in interactive digital storytelling: sampling without spoiling., 248-253. https://doi.org/10.1007/978-3-319-99426-0_25
Galagedarage, T. (2021). Use of traditional forms of communication for honey gathering in rural sri lanka. International Journal of Media and Communication Research, 3(1), 01-09. https://doi.org/10.25299/ijmcr.v3i1.8120
Gapiuk, L., Estupiñán, S., & Szilas, N. (2019). Effects of higher interactivity on the interactive narrative experience: an experimental study., 379-388. https://doi.org/10.1007/978-3-030-33894-7_40
Grimm, J., Grimm, W., & Dezsö, A. (2014). The original folk and fairy tales of the brothers grimm.. https://doi.org/10.1515/9781400851898
Hagedorn, J. and Darányi, S. (2022). Bearing a bag-of-tales: an open corpus of annotated folktales for reproducible research. Journal of Open Humanities Data, 8. https://doi.org/10.5334/johd.78
Hashim, S., Omar, M., Jalil, H., & Sharef, N. (2022). Trends on technologies and artificial intelligence in education for personalized learning: systematic literature review. International Journal of Academic Research in Progressive Education and Development, 11(1). https://doi.org/10.6007/ijarped/v11-i1/12230
Jian, M. (2023). Personalized learning through ai. AEI, 5(1), 16-19. https://doi.org/10.54254/2977-3903/5/2023039
Jin, C. (2023). On the effective integration of folk art and art design education. Frontiers in Art Research, 5(3). https://doi.org/10.25236/far.2023.050304
Lai, S., Huang, B., & Sun, M. (2023). Innovative development of cross-cultural communication of folk art and resource personalized recommendation algorithm in the context of intangible cultural heritage. Frontiers in Art Research, 5(14). https://doi.org/10.25236/far.2023.051417
Li, J. (2023). Advancing personalized learning with multi-modal embedding open learner model and gpt prompt. https://doi.org/10.36227/techrxiv.24087288.v1
Lô, G., Boer, V., & Aart, C. (2020). Exploring west african folk narrative texts using machine learning. Information, 11(5), 236. https://doi.org/10.3390/info11050236
Moulieswaran, N. and S, P. (2022). Amelioration of google assistant – a review of artificial intelligence stimulated second language learning and teaching. World Journal of English Language, 13(1), 86. https://doi.org/10.5430/wjel.v13n1p86
Naumovska, O., Rudakova, N., & Naumovska, N. (2021). “life/death” binary opposition in folk prose narratives. Linguistics and Culture Review, 5(S4), 540-558. https://doi.org/10.21744/lingcure.v5ns4.1589
Onesi-Ozigagun, O., Ololade, Y., Eyo-Udo, N., & Ogundipe, D. (2024). Revolutionizing education through ai: a comprehensive review of enhancing learning experiences. International Journal of Applied Research in Social Sciences, 6(4), 589-607. https://doi.org/10.51594/ijarss.v6i4.1011
Qin, L. (2024). Adaptive system of english-speaking learning based on artificial intelligence. jes, 20(6s), 267-275. https://doi.org/10.52783/jes.2637
Quý, N. and Phương, ư. (2023). The importance of fairy tales in communication, education, and cultural preservation. International Journal of Social Science and Human Research, 6(10). https://doi.org/10.47191/ijsshr/v6-i10-14
Salam, M., Fitri, S., & Zulan, H. (2024). Educational technology based on artificial intelligence in supporting distance learning in arabic language learning in higher education. Journal International of Lingua and Technology, 3(1), 134-145. https://doi.org/10.55849/jiltech.v3i1.485
Saxena, M. and Bajotra, V. (2024). Potential of artificial intelligence in education and ethical issues. Far Western J. Educ., 1(1), 1-18. https://doi.org/10.3126/fwje.v1i1.68773
Setiawan, E. I., Masruddin, M., & Zainuddin, Z. (2023). Semiotic Analysis and Ethnography Study on the Implementation of Local Wisdom in Economic Field at Luwu Society. IDEAS: Journal on English Language Teaching and Learning, Linguistics and Literature, 11(2), 1912-1925.
Shi, W. and Nicolas, A. (2023). Enhancing education and literacy through the transmission of tibetan folk music performing art in qinghai province, china. International Journal of Education and Literacy Studies, 11(4), 151-158. https://doi.org/10.7575/aiac.ijels.v.11n.4p.151
Shiukashvili, T. (2020). Comparative – contrastive analyze of anthropomorphic figures of evil in english and georgian languages. International Journal of Linguistics Literature and Culture, 6(1), 24-31. https://doi.org/10.21744/ijllc.v6n1.810
Siminto, S., Akib, A., Hasmirati, H., & Widianto, D. (2023). Educational management innovation by utilizing artificial intelligence in higher education. Al-Fikrah Jurnal Manajemen Pendidikan, 11(2), 284. https://doi.org/10.31958/jaf.v11i2.11860
Sugihartono, R. and Purnomo, S. (2023). The potential of theriantrophic characters in folk stories for animation. ADS. https://doi.org/10.7176/ads/106-05
Svalastog, A. and Allgaier, J. (2016). Hollywood heroes in high tech risk societies: modern fairy tales and emerging technologies. Journal of Science Communication, 15(02), C05. https://doi.org/10.22323/2.15020305
Ulfa, K. (2023). The transformative power of artificial intelligence (ai) to elevate english language learning. Majalah Ilmiah Methoda, 13(3), 307-313. https://doi.org/10.46880/methoda.vol13no3.pp307-313
Wójcicka, M. (2013). Urban legends in poland., 43-58. https://doi.org/10.7592/ep.2.wojcicka
Wu, M. and Bhengsri, T. (2023). Educational and literacy dimensions of putian coastal folk songs in fujian province, china. International Journal of Education and Literacy Studies, 11(3), 244-250. https://doi.org/10.7575/aiac.ijels.v.11n.3p.244
Wu, W., Wang, L., & Mihalcea, R. (2023). Cross-cultural analysis of human values, morals, and biases in folk tales. https://doi.org/10.18653/v1/2023.emnlp-main.311
Yang, K. (2024). Research on personalized english language learning based on artificial intelligence. Applied Mathematics and Nonlinear Sciences, 9(1). https://doi.org/10.2478/amns-2024-2151
Zhao, T. (2023). Ai in educational technology. https://doi.org/10.20944/preprints202311.0106.v1
Zhou, B. (2024). The comprehensive investigation of the role related to artificial intelligence in education. Applied and Computational Engineering, 36(1), 215-219. https://doi.org/10.54254/2755-2721/36/20230449
Downloads
Published
Issue
Section
Citation Check
License
Copyright (c) 2025 Qoriana Kiki, Hary Soedarto, Priyanto
This work is licensed under a Creative Commons Attribution-ShareAlike 4.0 International License.
Authors retain copyright and grant the journal right of first publication with the work simultaneously licensed under an Attribution-ShareAlike 4.0 International (CC BY-SA 4.0) that allows others to share the work with an acknowledgement of the work's authorship and initial publication in this journal.
Authors are able to enter into separate, additional contractual arrangements for the non-exclusive distribution of the journal's published version of the work (e.g., post it to an institutional repository or publish it in a book), with an acknowledgement of its initial publication in this journal.
Authors are permitted and encouraged to post their work online (e.g., in institutional repositories or on their website) prior to and during the submission process, as it can lead to productive exchanges, as well as earlier and greater citation of published work (See the Effect of Open Access)
