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Transforming Education Through Integrating AI: A Systematic Mapping Review for Enhanced User Experience

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Proceedings of TEEM 2023 (TEEM 2023)

Abstract

This article presents a systematic mapping review that explores the integration of artificial intelligence (AI) technologies in education to enhance the user experience and investigates the utilization of AI-enabled tools in various domains and educational levels, with a specific focus on improving human-computer interaction between students and teachers. This review provides valuable insights into AI’s diverse applications and potential impacts on education by analyzing a wide range of literature. The findings underscore the transformative role of AI in reshaping teaching and learning methods, enabling personalized and adaptive educational experiences. The research highlights user-friendly AI tools’ significance in enhancing the learning environment. Educators, policymakers, and researchers can benefit from the comprehensive analysis and recommendations presented in this study, facilitating informed decision-making regarding integrating AI technologies in educational settings.

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References

  1. García-Peñalvo, F.J., Vázquez-Ingelmo, A.: What do we mean by Genai? A systematic mapping of the evolution, trends, and techniques involved in generative AI. Int. J. Interact. Multimed. Artif. Intell. (2023). In Press

    Google Scholar 

  2. Holmes, W., Bialik, M., Fadel, C.: Artificial Intelligence in Education. Globethics Publications (2023)

    Google Scholar 

  3. Human-centered artificial intelligence in education: seeing the invisible through the visible. Comput. Educ.: Artif. Intell. 2, 100008 (2021)

    Google Scholar 

  4. García-Peñalvo, F.J., Llorens-Largo, F., Vidal, J.: The new reality of education in the face of advances in generative artificial intelligence. RIED: Rev. Iberoamericana Educ. Dist. 27(1) (2024)

    Google Scholar 

  5. Marín-Morales, J., Llinares, C., Guixeres, J., Alcañiz, M.: Emotion recognition in immersive virtual reality: From statistics to affective computing. Sensors 20(18), 5163 (2020)

    Article  Google Scholar 

  6. Elmqaddem, N.: Augmented reality and virtual reality in education. Myth or reality? Int. J. Emerg. Technol. Learn. 14(3) (2019)

    Google Scholar 

  7. Deniz, S., et al.: Computer vision for attendance and emotion analysis in school settings. In: 2019 IEEE 9th Annual Computing and Communication Workshop and Conference (CCWC), pp. 0134–0139. IEEE (2019)

    Google Scholar 

  8. King, M.R., ChatGPT: A conversation on artificial intelligence, chatbots, and plagiarism in higher education. Cell. Mol. Bioeng. 16(1), 1–2 (2023)

    Google Scholar 

  9. Manikandan, S., Dhanalakshmi, P., Priya, S., Teena, A.M.O.: Intelligent and deep learning collaborative method for e-learning educational platform using TensorFlow. Turk. J. Comput. Math. Educ. 12(10), 2669–2676 (2021)

    Google Scholar 

  10. Luan, H., Tsai, C.-C.: A review of using machine learning approaches for precision education. Educ. Technol. Soc. 24(1), 250–266 (2021)

    Google Scholar 

  11. Mathew, A.N., Rohini, V., Paulose, J.: NLP-based personal learning assistant for school education. Int. J. Electr. Comput. Eng. (2088–8708) 11, 4522–4530 (2021)

    Google Scholar 

  12. Jiang, Y., Li, X.: Intelligent online education system based on speech recognition with specialized analysis on quality of service. Int. J. Speech Technol. 23, 489–497 (2020)

    Article  Google Scholar 

  13. Chassignol, M., Khoroshavin, A., Klimova, A., Bilyatdinova, A.: Artificial intelligence trends in education: a narrative overview. Procedia Comput. Sci. 136, 16–24 (2018)

    Article  Google Scholar 

  14. García-Peñalvo, F.J.: The perception of artificial intelligence in educational contexts after the launch of ChatGPT: disruption or panic? Educ. Knowl. Soc. 24, e31279 (2023)

    Article  Google Scholar 

  15. Kitchenham, B., Brereton, O.P., Budgen, D., Turner, M., Bailey, J., Linkman, S.: Systematic literature reviews in software engineering - a systematic literature review. Inf. Softw. Technol. 51(1), 7–15 (2009). Special Section - Most Cited Articles in 2002 and Regular Research Papers

    Article  Google Scholar 

  16. Petticrew, M., Roberts, H.: Systematic Reviews in the Social Sciences: A Practical Guide, vol. 11 (2006)

    Google Scholar 

  17. García-Peñalvo, F.J.: Developing robust state-of-the-art reports: systematic literature reviews. Educ. Knowl. Soc. 23, e28600 (2022)

    Article  Google Scholar 

  18. Page, M.J., et al.: statement: an updated guideline for reporting systematic reviews. Int. J. Surg. 88(105906), 2021 (2020)

    Google Scholar 

  19. He, J.: An exploratory study on the application of artificial intelligence technology in the teaching of Japanese language in university. In: 2021 2nd International Conference on Information Science and Education (ICISE-IE), pp. 1454–1457. IEEE (2021)

    Google Scholar 

  20. Renzella, J., Cain, A., Schneider, J.-G.: An intelligent tool for combatting contract cheating behaviour by facilitating scalable student-tutor discussions. In: Proceedings of the ACM/IEEE 42nd International Conference on Software Engineering: Companion Proceedings, pp. 298–299 (2020)

    Google Scholar 

  21. Pan, Z., Sun, Y., Yao, Z.W., Li, M.: Application of virtual reality in English teaching. In: 2021 3rd World Symposium on Artificial Intelligence (WSAI), pp. 64–71. IEEE (2021)

    Google Scholar 

  22. Bouktif, S., Manzoor, A.: Artificial intelligence as a gear to preserve effectiveness of learning and educational systems in pandemic time. In: 2021 IEEE Global Engineering Education Conference (EDUCON), pp. 1703–1711. IEEE (2021)

    Google Scholar 

  23. Yang, Y., Sun, J., Huang, L.: Artificial intelligence teaching methods in higher education. In: Bi, Y., Bhatia, R., Kapoor, S. (eds.) IntelliSys 2019. AISC, vol. 1037, pp. 1044–1053. Springer, Cham (2020). https://doi.org/10.1007/978-3-030-29516-5_78

    Chapter  Google Scholar 

  24. Jiang, Y.: Artificial intelligence technology for python test simulation of oral English teaching evaluation. In: 2022 Sixth International Conference on I-SMAC (IoT in Social, Mobile, Analytics and Cloud) (I-SMAC), pp. 654–657. IEEE (2022)

    Google Scholar 

  25. Sakon, H., Yamamoto, T.: Body movements for communication in group work classified by deep learning. In: Kurosu, M. (ed.) HCII 2019. LNCS, vol. 11567, pp. 388–396. Springer, Cham (2019). https://doi.org/10.1007/978-3-030-22643-5_30

    Chapter  Google Scholar 

  26. Gotoda, N., Kometani, Y., Yaegashi, R., Hayashi, T.: Educational environment of video system using superimposing symbols to support for skill training. In: Yamamoto, S., Mori, H. (eds.) HCII 2020, Part II. LNCS, vol. 12185, pp. 164–174. Springer, Cham (2020). https://doi.org/10.1007/978-3-030-50017-7_11

    Chapter  Google Scholar 

  27. Bjorn, M., Ravyse, W., Villafruella, D.S., Luimula, M., Leivo, S.: Higher education learner experience with fuzzy feedback in a digital learning environment. In: 2018 9th IEEE International Conference on Cognitive Infocommunications (CogInfoCom), pp. 000253–000260. IEEE (2018)

    Google Scholar 

  28. Murrell, S., Wang, F., Aldrich, E., Xu, X.: MeteorologyAR: a mobile AR app to increase student engagement and promote active learning in a large lecture class. In: 2020 IEEE Conference on Virtual Reality and 3D User Interfaces Abstracts and Workshops (VRW), pp. 848–849. IEEE (2020)

    Google Scholar 

  29. Pears, M., et al.: Prototype for crowd-based co-creation of artificial intelligence natural language conversational agents. In: 2022 IEEE Global Engineering Education Conference (EDUCON), pp. 2013–2021. IEEE (2022)

    Google Scholar 

  30. Lai, C., Gao, Q., Zheng, Z., Yuan, D., Zhou, B., Hong, R.: Research on head-up and down behavior computer detection by deep learning and artificial intelligence. In: 2021 IEEE 3rd International Conference on Civil Aviation Safety and Information Technology (ICCASIT), pp. 597–600. IEEE (2021)

    Google Scholar 

  31. Benedetto, L., Cremonesi, P.: Rexy, a configurable application for building virtual teaching assistants. In: Lamas, D., Loizides, F., Nacke, L., Petrie, H., Winckler, M., Zaphiris, P. (eds.) INTERACT 2019. LNCS, vol. 11747, pp. 233–241. Springer, Cham (2019). https://doi.org/10.1007/978-3-030-29384-0_15

    Chapter  Google Scholar 

  32. Liu, T., Yuizono, T., Lu, Y., Wang, Z.: Application of human-machine dialogue in foreign language teaching at universities. In: IOP Conference Series: Materials Science and Engineering, vol. 573, pp. 012047. IOP Publishing (2019)

    Google Scholar 

  33. Shin, S., Cho, J., Kim, S.-W.: Jumple: Interactive contents for the virtual physical education classroom in the pandemic era. In: 2021 Augmented Humans Conference, pp. 268–270 (2021)

    Google Scholar 

  34. Wang, C., Liu, X.: Affective computing oriented to intelligent education-reflection and prospect. In: 2019 International Joint Conference on Information, Media and Engineering (IJCIME), pp. 241–245. IEEE (2019)

    Google Scholar 

  35. Yu, D.D., Ding, M.R., Li, W.J., Wang, L., Liang, B.: Designing an artificial intelligence platform to assist undergraduate in art and design to develop a personal learning plans. In: Marcus, A., Wang, W. (eds.) HCII 2019, Part III. LNCS, vol. 11585, pp. 528–538. Springer, Cham (2019). https://doi.org/10.1007/978-3-030-23538-3_41

    Chapter  Google Scholar 

  36. Divekar, R.R., et al.: Foreign language acquisition via artificial intelligence and extended reality: design and evaluation. Comput. Assist. Lang. Learn. 1–29 (2021)

    Google Scholar 

  37. Ni, L., Wang, L.: Model study of VR technology in the professional teaching of preschool education. In: 2021 2nd International Conference on Information Science and Education (ICISE-IE), pp. 1490–1493. IEEE (2021)

    Google Scholar 

  38. Gu, Y., Hu, J., Zhou, Y., Lu, L.: Online teaching gestures recognition model based on deep learning. In: 2020 International Conference on Networking and Network Applications (NaNA), pp. 410–416. IEEE (2020)

    Google Scholar 

  39. Hamam, D.: The new teacher assistant: a review of chatbots’ use in higher education. In: Stephanidis, C., Antona, M., Ntoa, S. (eds.) HCII 2021. CCIS, vol. 1421, pp. 59–63. Springer, Cham (2021). https://doi.org/10.1007/978-3-030-78645-8_8

    Chapter  Google Scholar 

  40. Hasnine, M.N., Flanagan, B., Akcapinar, G., Ogata, H., Mouri, K., Uosaki, N.: Vocabulary learning support system based on automatic image captioning technology. In: Streitz, N., Konomi, S. (eds.) HCII 2019. LNCS, vol. 11587, pp. 346–358. Springer, Cham (2019). https://doi.org/10.1007/978-3-030-21935-2_26

    Chapter  Google Scholar 

  41. Perez-Ortiz, M., et al.: X5learn: a personalised learning companion at the intersection of AI and HCI. In: 26th International Conference on Intelligent User Interfaces-Companion, pp. 70–74 (2021)

    Google Scholar 

  42. Retnanto, A., Fadlelmula, M., Alyafei, N., Sheharyar, A.: Active student engagement in learning-using virtual reality technology to develop professional skills for petroleum engineering education. In: SPE Annual Technical Conference and Exhibition. OnePetro (2019)

    Google Scholar 

  43. Schlippe, T., Sawatzki, J.: AI-based multilingual interactive exam preparation. In: Guralnick, D., Auer, M.E., Poce, A. (eds.) TLIC 2021. LNNS, vol. 349, pp. 396–408. Springer, Cham (2022). https://doi.org/10.1007/978-3-030-90677-1_38

    Chapter  Google Scholar 

  44. Zheng, H., Dai, D.: Construction and optimization of artificial intelligence-assisted interactive college music performance teaching system. Sci. Program. 2022 (2022)

    Google Scholar 

  45. Almufarreh, A.: Performance evaluation and measurement of learning management system through usability, user interface, and user experience. Int. J. Comput. Sci. Netw. Secur. (2022)

    Google Scholar 

  46. Guo, L., Wang, J.: A framework for the design of plant science education system for China’s botanical gardens with artificial intelligence. In: Stephanidis, C., Antona, M., Ntoa, S. (eds.) HCII 2020, Part II. CCIS, vol. 1294, pp. 267–271. Springer, Cham (2020). https://doi.org/10.1007/978-3-030-60703-6_34

    Chapter  Google Scholar 

  47. Wang, X., Han, Q., Gao, F.: Design of sports training simulation system for children based on improved deep neural network. Comput. Intell. Neurosci. 2022 (2022)

    Google Scholar 

  48. Weng, T.-S., Li, C.-K., Hsu, M.-H.: Development of robotic quiz games for self-regulated learning of primary school children. In: 2020 3rd Artificial Intelligence and Cloud Computing Conference, pp. 58–62 (2020)

    Google Scholar 

  49. Jing, S., Tang, Y., Liu, X., Gong, X., Cui, W., Liang, J.: A parallel education based intelligent tutoring systems framework. In: 2020 IEEE International Conference on Networking, Sensing and Control (ICNSC), pp. 1–6. IEEE (2020)

    Google Scholar 

  50. Xu, Y., Ji, Y., Tan, P., Zhong, Q., Ma, M.: Intelligent painting education mode based on individualized learning under the internet vision. In: Russo, D., Ahram, T., Karwowski, W., Di Bucchianico, G., Taiar, R. (eds.) IHSI 2021. AISC, vol. 1322, pp. 253–259. Springer, Cham (2021). https://doi.org/10.1007/978-3-030-68017-6_38

    Chapter  Google Scholar 

  51. Al-Hiyari, N., Jusoh, S.: The current trends of virtual reality applications in medical education. In: 2020 12th International Conference on Electronics, Computers and Artificial Intelligence (ECAI), pp. 1–6. IEEE (2020)

    Google Scholar 

  52. Yang, S., Yu, K., Lammers, T., Chen, F.: Artificial intelligence in pilot training and education – towards a machine learning aided instructor assistant for flight simulators. In: Stephanidis, C., Antona, M., Ntoa, S. (eds.) HCII 2021. CCIS, vol. 1420, pp. 581–587. Springer, Cham (2021). https://doi.org/10.1007/978-3-030-78642-7_78

    Chapter  Google Scholar 

  53. Tao, S.: Big data system for dragon boat rowing action training based on multidimensional stereo vision. Math. Probl. Eng. 2022 (2022)

    Google Scholar 

  54. Xia, P.: Design of personalized intelligent learning assistant system under artificial intelligence background. In: MacIntyre, J., Zhao, J., Ma, X. (eds.) SPIOT 2020. AISC, vol. 1282, pp. 194–200. Springer, Cham (2021). https://doi.org/10.1007/978-3-030-62743-0_27

    Chapter  Google Scholar 

  55. Sang, Y., Chen, X.: Human-computer interactive physical education teaching method based on speech recognition engine technology. Front. Public Health 10 (2022)

    Google Scholar 

  56. Nelson, M.J., Hoover, A.K.: Notes on using google colaboratory in AI education. In: Proceedings of the 2020 ACM Conference on Innovation and Technology in Computer Science Education, pp. 533–534 (2020)

    Google Scholar 

  57. Resch, O., Yankova, A.: Open knowledge interface: a digital assistant to support students in writing academic assignments. In: Proceedings of the 1st ACM SIGSOFT International Workshop on Education through Advanced Software Engineering and Artificial Intelligence, pp. 13–16 (2019)

    Google Scholar 

  58. Gu, S., Song, X., Wu, L.: Optimization of English language and literature teaching management system based on artificial intelligence and computer-aided design (2022)

    Google Scholar 

  59. Ahajjam, T., Moutaib, M., Aissa, H., Azrour, M., Farhaoui, Y., Fattah, M.: Predicting students’ final performance using artificial neural networks. Big Data Min. Anal. 5(4), 294–301 (2022)

    Article  Google Scholar 

  60. Zhen, R., Song, W., Cao, J.: Research on the application of virtual human synthesis technology in human-computer interaction. In: 2022 IEEE/ACIS 22nd International Conference on Computer and Information Science (ICIS), pp. 199–204. IEEE (2022)

    Google Scholar 

  61. Novellino, A., Bonofiglio, L., Cimmino, V., Napoletani, L.: STEP-SmarT education platform. In: Proceedings of the 13th International Multi-Conference on Complexity, Informatics and Cybernetics (IMCIC 2022) (2022)

    Google Scholar 

  62. Tian, X., Cui, S., et al.: The application of scientific games by artificial intelligence in preschool education under the smart city. Secur. Commun. Netw. 2022 (2022)

    Google Scholar 

  63. Chen, C.-C., Chen, M.-Y., Waheed, S., Chien, W.-C., Xu, W.: The teaching pattern of law majors using artificial intelligence and deep neural network under educational psychology. In: Deep Learning in Adaptive Learning: Educational Behavior and Strategy (2022)

    Google Scholar 

  64. Sunday, K., Oyelere, S.S., Agbo, F.J., Aliyu, M.B., Balogun, O.S., Bouali, N.: Usability evaluation of Imikode virtual reality game to facilitate learning of object-oriented programming. Technol. Knowl. Learn. 1–32 (2022)

    Google Scholar 

  65. Al-mandhari, I.S., Guan, L., Edirisinghe, E.A.: Advances in information and communication networks (2019)

    Google Scholar 

  66. Weiss, A., Vrecar, R., Zamiechowska, J., Purgathofer, P.: Using the design of adversarial chatbots as a means to expose computer science students to the importance of ethics and responsible design of AI technologies. In: Ardito, C., et al. (eds.) INTERACT 2021, Part III. LNCS, vol. 12934, pp. 331–339. Springer, Cham (2021). https://doi.org/10.1007/978-3-030-85613-7_24

    Chapter  Google Scholar 

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Shoeibi, N., García-Peñalvo, F.J., Therón Sánchez, R. (2024). Transforming Education Through Integrating AI: A Systematic Mapping Review for Enhanced User Experience. In: Gonçalves, J.A.d.C., Lima, J.L.S.d.M., Coelho, J.P., García-Peñalvo, F.J., García-Holgado, A. (eds) Proceedings of TEEM 2023. TEEM 2023. Lecture Notes in Educational Technology. Springer, Singapore. https://doi.org/10.1007/978-981-97-1814-6_17

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