Skip to main content

Current Trends in AI-Based Educational Processes—An Overview

  • Chapter
  • First Online:

Part of the book series: Learning and Analytics in Intelligent Systems ((LAIS,volume 29))

Abstract

Artificial intelligence (AI) is a rapidly developing research area, with immense influence on different areas of modern society and with numerous applications in real-life systems and environments. In this chapter we provide a brief overview of current state-of-the-art of developing intelligent educational systems. Particular attention is paid on the application of artificial intelligence methods in teaching and learning processes. Accordingly, we consider recent works that put light on different roles of AI in developing educational systems. Also, an overview of key educational domains that AI techniques influence, i.e.: adaptive personalization systems and intelligent tutoring systems, assessment and evaluation of students’ outcomes and learning performances, and benefits and challenges of educational data mining and learning analytics in educational processes is presented.

This is a preview of subscription content, log in via an institution.

Buying options

Chapter
USD   29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD   139.00
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD   179.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info
Hardcover Book
USD   179.99
Price excludes VAT (USA)
  • Durable hardcover edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Learn about institutional subscriptions

References

  1. DFKI, Intelligent Solutions for the Knowledge Society. The German Research Center for Artificial Intelligence (2015). http://www/dfki.de/web?set_language=en&cl=en. Accessed 30 Oct 2016

    Google Scholar 

  2. S. Somyürek, P. Brusilovsky, J. Guerra, Supporting knowledge monitoring ability: open learner modeling vs. open social learner modeling. Res. Pract. Technol. Enhanc. Learn. 15(1), 17 (2020)

    Google Scholar 

  3. M. Fahimirad, S.S. Kotamjani, A review on application of artificial intelligence in teaching and learning in educational contexts. Int. J. Learn. Dev. 8, 106–118 (2018)

    Article  Google Scholar 

  4. T. Baker, L. Smith, Educ-AI-tion rebooted? Exploring the future of artificial intelligence in schools and colleges (2019). Accessed from Nesta Foundation website: https://media.nesta.org.uk/documents/Future_of_AI_and_education_v5_WEB.pdf

  5. B. David, R. Chalon, B. Zhang, C. Yin, Design of a collaborative learning environment integrating emotions and virtual assistants (chatbots). In: 2019 IEEE 23rd International Conference on Computer Supported Cooperative Work in Design (CSCWD) (IEEE, 2019), pp. 51–56. https://doi.org/10.1109/CSCWD.2019.8791893

  6. S. El Alfy, G.J. Marx, A. Dani, Exploring the benefits and challenges of learning analytics in higher education institutions: a systematic literature review. Inf Discov Delivery (2019). https://doi.org/10.1108/IDD-06-2018-0018

    Article  Google Scholar 

  7. F. Grivokostopoulou, I. Perikos, I. Hatzilygeroudis, An educational system for learning search algorithms and automatically assessing student performance. Int. J. Artif. Intell. Educ. 27, 207–240 (2017). https://doi.org/10.1007/s40593-016-0116-x

    Article  Google Scholar 

  8. W. Holmes, M. Bialik, C. Fadel, Artificial Intelligence, in Education: Promises and Implications for Teaching and Learning (Center for Curriculum Redesign, Boston, 2019)

    Google Scholar 

  9. J.A. Kumar, Educational chatbots for project-based learning: investigating learning outcomes for a team-based design course. Int. J. Educ. Technol. High. Educ. 18(1), 1–28 (2021). https://doi.org/10.1186/s41239-021-00302-w

    Article  Google Scholar 

  10. O.P. Pardo, R. Martinez-Maldonado, S. Dawson, Provision of data-driven student feedback in LA&EDM. Handb. Learn. Anal. 163–174 (2017). https://doi.org/10.18608/hla17.014

  11. W.H. Dai, S. Huang, X. Zhou, X.E. Yu, M. Ivanovic, D.R. Xu, Emotional intelligence system for ubiquitous smart foreign language education based on neural mechanism. J. Inf. Technol. Appl. Manage. 21(3), 65–77 (2014). http://www.dbpia.co.kr/Journal/ArticleList/159833

  12. M. Ivanović, D. Mitrović, Z. Budimac, L. Jerinić, C. Bădică, HAPA: harvester and pedagogical agents in e-learning environments. Int. J. Comput. Commun. Control 10(2), 200–210 (2015). ISSN 1841-9836

    Google Scholar 

  13. M. Liu, Y. Wang, W. Xu, L. Liu, Automated scoring of Chinese engineering students’ English essays. Int. J. Distance Educ. Technol. 15, 52–68 (2017). https://doi.org/10.4018/IJDET.2017010104

    Article  Google Scholar 

  14. C.W. Okonkwo, A. Ade-Ibijola, Chatbots applications in education: a systematic review. Comput. Educ.: Artif. Intell. 2, 100033 (2021). https://doi.org/10.1016/j.caeai.2021.100033

  15. R. Luckin, W. Holmes, M. Griffiths, L.B. Forcier, Intelligence unleashed - an argument for AI in education (2016). Accessed from http://discovery.ucl.ac.uk/1475756/

  16. I. Tuomi, M. Cabrera Giraldez, R. Vuorikari, Y. Punie, The Impact of Artificial Intelligence on Learning, Teaching, and Education (Publications Office of the European Union, 2018). https://ec.europa.eu/jrc/en/publication/eur-scientific-and-technical-research-reports/impact-artificial-intelligence-learning-teaching-and-education

  17. J. Grove, TeachHigher “disbanded” ahead of campus protest. Times Higher Education, 2 June 2015. http://www.timeshighereducation.com/news/teachhigher-disbanded-ahead-campus-protest. Accessed 28 Apr 2017

  18. A. Klasnja-Milicevic, B. Vesin, M. Ivanovic, Z. Budimac, L.C. Jain, E-Learning Systems - Intelligent Techniques for Personalization. Intelligent Systems Reference Library vol. 112 (Springer, 2017), pp. 3–294. ISBN 978-3-319-41161-3

    Google Scholar 

  19. A. Klašnja-Milićevic, M. Ivanović, E-learning personalization systems and sustainable education. Sustainability 021(13), 6713 (2022). https://doi.org/10.3390/su13126713

    Article  Google Scholar 

  20. J. Barria-Pineda, K. Akhuseyinoglu, S. Zelem-Celap, P. Brusilovsky, A. Klasnja-Milicevic, M. Ivanovic, Explainable recommendations in a personalized programming practice system, in Artificial Intelligence in Education - 22nd International Conference, AIED 2021, Utrecht, The Netherlands, June 14–18, 2021, Proceedings, Part I. LNCS, vol 12748. (Springer, 2021), pp. 64–76. ISBN 978-3-030-78291-7

    Google Scholar 

  21. M.J. Laakso, E. Kaila, T. Rajala, ViLLE - collaborative education tool: designing and utilizing an exercise-based learning environment. Educ. Inf. Technol. 23(4), 1655–1676 (2018)

    Google Scholar 

  22. A. Rodriguez-Ascaso, J.G. Boticario, C. Finat, H. Petrie, Setting accessibility preferences about learning objects within adaptive elearning systems: user experience and organizational aspects. Expert Syst. 34, e12187 (2017). https://doi.org/10.1111/exsy.12187

  23. A.T. Quadri, N.A. Shukor, The benefits of learning analytics to higher education institutions: a scoping review. Int. J. Emerg. Technol. Learn. (iJET) 16(23), 4–15 (2021). https://doi.org/10.3991/ijet.v16i23.27471

    Article  Google Scholar 

  24. G. Denhiere, S. Baudet, Lecture, Comprehension de Texte et Science Cognitive (Presses Universitariesde France, 1992)

    Google Scholar 

  25. A. Collins, B. Beranek, A Sample Dialogue Based on a Theory on Inquiry Teaching, University of Illionosi at Urbana- Cpampaign (1986)

    Google Scholar 

  26. L. Jia-Jiunn, C. Ya-Chen, Y. Shiou-Wen, Designing an adaptive web-based learning system based on students’ cognitive styles identified online. Comput. Educ. 58(1), 209–222 (2012)

    Article  Google Scholar 

  27. A. Klasnja-Milicevic, M. Ivanovic, B. Vesin, Z. Budimac, Enhancing e-learning systems with personalized recommendation based on collaborative tagging techniques. Appl. Intell. 48(6), 1519–1535 (2018)

    Article  Google Scholar 

  28. G. Siemens, D. Gasevic, “Guest editorial-learning and knowledge analytics. Educ. Technol. Soc. 15(3), 1–2 (2012)

    Google Scholar 

  29. V. González-Calatayud, P. Prendes-Espinosa, R. Roig-Vila, Artificial intelligence for student assessment: a systematic review. Appl. Sci. 11, 5467 (2021) https://doi.org/10.3390/app11125467

  30. S. Janpla, P. Piriyasurawong, The development of an intelligent multilevel item bank model for the national evaluation of undergraduates. Univers. J. Educ. Res. 8, 4163–4172 (2020). https://doi.org/10.13189/ujer.2020.080942

    Article  Google Scholar 

  31. P. Rhienmora, P. Haddawy, S. Suebnukarn, M.N. Dailey, Intelligent dental training simulator with objective skill assessment and feedback. Artif. Intell. Med. 2011(52), 115–121 (2011). https://doi.org/10.1016/j.artmed.2011.04.003

    Article  Google Scholar 

  32. S. Popenici, S. Kerr, Exploring the impact of artificial intelligence on teaching and learning in higher education. Res. Pract. Technol. Enhanc. Learn. (2017). https://doi.org/10.1186/s41039-017-0062-8

    Article  Google Scholar 

  33. J. Maderer, Artificial Intelligence Course Creates AI Teaching Assistant, Georgia Tech News Center, 9 May 2016 (2016). https://news.gatech.edu/news/2016/05/09/artificial-intelligence-course-creates-ai-teaching-assistant, Accessed 10 Aug 2021

  34. M. Pérez-Sanagustín, I. Hilliger, C. Alario-Hoyos, C.D. Kloos, S. Rayyan, H-MOOC framework: reusing MOOCs for hybrid education. J. Comput. High. Educ. 29(1), 47–64 (2017)

    Article  Google Scholar 

  35. R. Luckin, Towards artificial intelligence-based assessment system, Nat. Human Behav. 1(0028) (2017)

    Google Scholar 

  36. E. Kaila, E. Kurvinen, E. Lokkila, M.-J. Laakso, Redesigning an object-oriented programming course. ACM Trans. Comput. Educ. 16, 1–21 (2016). https://doi.org/10.1145/2906362

    Article  Google Scholar 

  37. A.K. Goel, D.A. Joyner, Using AI to teach AI: lessons from an online AI class. AI Mag. 38, 48–59 (2017). https://doi.org/10.1609/aimag.v38i2.2732

    Article  Google Scholar 

  38. V. Triglianos, M. Labaj, R. Moro, J. Simko, M. Hucko, J. Tvarozek, C. Pautasso, M. Bielikova, Experiences using an interactive presentation platform in a functional and logic programming course, in Adjunct Publication of the 25th Conference on User Modeling, Adaptation and Personalization (ACM, New York, 2017), pp. 311–316

    Google Scholar 

  39. J. Kim, E.L. Glassman, A. Monroy-Hernández, M.R. Morris, Rimes: embedding interactive multimedia exercises in lecture videos, in Proceedings of the 33rd Annual ACM Conference on Human Factors in Computing Systems (ACM, New York, 2015), pp. 1535–1544

    Google Scholar 

  40. M. Samarakou, E.D. Fylladitakis, D. Karolidis, W.-G. Früh, A. Hatziapostolou, S.S. Athinaios, M. Grigoriadou, Evaluation of an intelligent open learning system for engineering education. Knowl. Manag. E-Learn. An Int. J. 2016(8), 496–513 (2016). https://doi.org/10.34105/j.kmel.2016.08.031

    Article  Google Scholar 

  41. P. Brusilovsky, S. Somyürek, J. Guerra, R. Hosseini, V. Zadorozhny, The value of social: Comparing open student modeling and open social student modeling, in International Conference on User Modeling, Adaptation, and Personalization (Springer, Cham, 2015), pp. 44–55

    Google Scholar 

  42. K.R. Maicher, L. Zimmerman, B. Wilcox, B. Liston, H. Cronau, A. Macerollo, L. Jin, E. Jaffe, M. White, E. Fosler-Lussier et al., Using virtual standardized patients to accurately assess information gathering skills in medical students. Med. Teach. 41, 1053–1059 (2019). https://doi.org/10.1080/0142159X.2019.1616683

    Article  Google Scholar 

  43. N. Bostrom, E. Yudkowsky, The ethics of artificial intelligence, in Cambridge handbook of artificial intelligence. ed. by K. Frankish, W.M. Ransey (Cambridge University Press, 2011), pp. 316–334

    Google Scholar 

  44. Deakin University, IBM Watson now powering Deakin. A new partnership that aim to exceed students’ needs (2016). http://archive.li/kEnXm. Accessed 30 Oct 2016

  45. M. Samarakou, E.D. Fylladitakis, W.G. Früh, A. Hatziapostolou, J.J. Gelegenis, An advanced elearning environment developed for engineering learners. iJET 10(3), 22–33 (2015)

    Google Scholar 

  46. N. Mirchi, V. Bissonnette, R. Yilmaz, N. Ledwos, A. Winkler-Schwartz, R.F. Del Maestro, The virtual operative assistant: an explainable artificial intelligence tool for simulation-based training in surgery and medicine. PLoS One 15, e0229596 (2020).https://doi.org/10.1371/journal.pone.0229596

  47. I. Tuomi, The use of Artificial Intelligence (AI) in education, May 2020 (2020). https://bit.ly/3lCMotK, Accessed July 15

  48. E. Wood, L. Zivcakova, P. Gentile, K. Archer, D. De Pasquale, A. Nosko, Examining the impact of off-task multi-tasking with technology on real-time classroom learning. Comput. Educ. 58(1), 365–374 (2012)

    Article  Google Scholar 

  49. O. Zawacki-Richter, V.I. Marín, M. Bond, F. Gouverneur, Systematic review of research on artificial intelligence applications in higher education–where are the educators? Int. J. Educ. Technol. High. Educ. 16(1), 1–27 (2019)

    Article  Google Scholar 

Recommended for Further Reading

  1. U.L. Uskov et al. (eds.), Smart Education and e-Learning, Conference Proceedings of the KES-SEEL International Conference, 2021 (Springer, Germany, 2021)

    Google Scholar 

  2. V.L. Uskov et al. (eds.), Smart Education and e-Learning, Conference Proceedings of the KES-SEEL International Conference, 2020 (Springer, Germany, 2020)

    Google Scholar 

  3. V.L. Uskov et al. (eds.), Smart Education and e-Learning, Conference Proceedings of the KES-SEEL International Conference, 2019 (Springer, Germany, 2019)

    Google Scholar 

  4. V.L. Uskov et al. (eds.), Smart Education and e-Learning, Conference Proceedings of the KES-SEEL International Conference, 2018 (Springer, Germany, 2018)

    Google Scholar 

  5. V.L. Uskov et al. (eds.), Smart Education and e-Learning, Conference Proceedings of the KES-SEEL International Conference, 2017 (Springer, Germany, 2017)

    Google Scholar 

  6. V.L. Uskov et al. (eds.), Smart Education and e-Learning, Conference Proceedings of the KES-SEEL International Conference, 2016 (Springer, Germany, 2016)

    Google Scholar 

  7. V.L. Uskov et al. (eds.), Smart Education and e-Learning, Conference Proceedings of the KES-SEEL International Conference, 2015 (Springer, Germany, 2015)

    Google Scholar 

  8. M. Ivanovic, L.C. Jain, (eds.), E-Learning Paradigms and Applications (Springer, Germany, 2014)

    Google Scholar 

  9. L.C. Jain et al. (eds.), Evolution of Teaching and Learning Paradigms in Intelligent environment (Springer, Germany, 2007)

    Google Scholar 

  10. C. Ghaoui et al. (eds.), Knowledge-Based Virtual Education (Springer, Germany, 2005)

    Google Scholar 

  11. L.C. Jain et al. (eds.), Virtual Environments for Teaching and Learning (World Scientific Publishing Company Singapore, 2002)

    Google Scholar 

  12. L.C. Jain (ed.), Innovations in Teaching and Learning (Springer, Germany, 2000)

    Google Scholar 

Download references

Acknowledgements

This work has been supported by the joint research project “Agent Technologies in Dynamics Environments” under the agreement on scientific cooperation between University of Novi Sad, University of Craiova, SRI PAS and Warsaw University of Technology, as well as Mirjana Ivanović and Aleksandra Klašnja-Milićević acknowledge financial support of the Ministry of Education, Science and Technological Development of the Republic of Serbia (Grant No. 451-03-68/2022-14/200125).‬‬‬‬‬‬‬‬‬‬‬‬‬

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Mirjana Ivanović .

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2022 The Author(s), under exclusive license to Springer Nature Switzerland AG

About this chapter

Check for updates. Verify currency and authenticity via CrossMark

Cite this chapter

Ivanović, M. et al. (2022). Current Trends in AI-Based Educational Processes—An Overview. In: Ivanović, M., Klašnja-Milićević, A., Jain, L.C. (eds) Handbook on Intelligent Techniques in the Educational Process. Learning and Analytics in Intelligent Systems, vol 29. Springer, Cham. https://doi.org/10.1007/978-3-031-04662-9_1

Download citation

  • DOI: https://doi.org/10.1007/978-3-031-04662-9_1

  • Published:

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-031-04661-2

  • Online ISBN: 978-3-031-04662-9

  • eBook Packages: EducationEducation (R0)

Publish with us

Policies and ethics