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1713505 Vol 9 · Issue 7 Download Paper

Integrating Deep Learning and NLP in AI Chatbots for Education and Mental Health: A State-of-the-Art Review

Navjot Kaur Dr. Rajinder Kumar (Associate Professor)

Subject area: Science,Engineering and Technology  ·  Area of research: Artificial Intelligence

DOI: https://doi.org/10.64388/IREV9I7-1713505

Abstract

Artificial Intelligence (AI)?based chatbot?solutions have been capturing increasing attention as tools from which to re-imagine education and mental health support infrastructures. Through a combination of Natural Language Processing (NLP) and deep learning methods, such agents are able?to deliver personalized learning support as well as administrative assistance and initial mental health counseling. The present survey reviews the most recent work (mainly in years 2023?2025) on AI-based chatbots for education and psychology, covering architectures, datasets,?evaluation measures as well as pros and cons and ethical issues. This review highlights research gaps and suggests future work aimed?at building integrated, ethical and human-centered chatbot systems in higher education.

Keywords

AI Chatbots, Natural Language Processing, Deep Learning, Education, Mental Health, Conversational Agents.

References

[1] Altamimi, I., Altamimi, A., Alhumimidi, A. S., Altamimi, A., & Temsah, M.-H. (2023). Artificial Intelligence (AI) Chatbots in Medicine: A Supplement, Not a Substitute. Cureus, 15(6). https://doi.org/10.7759/cureus.40922.

[2] Basharat, I., & Shahid, S. (2024). AI-enabled chatbots healthcare systems: an ethical perspective on trust and reliability. Journal of Health Organization and Management. https://doi.org/10.1108/jhom-10-2023-0302.

[3] Bhatt, S. (2024). Artificial intelligence in digital mental health interventions. Journal of Mental Health Technology.

[4] Cho, J., Kim, S., & Park, H. (2023). Conversational agents for mental health support: A systematic review. Journal of Medical Internet Research.

[5] Davar, P., Dewan, M., & Zhang, Y. (2025). AI chatbots in education: Challenges and opportunities. Information, 16(3), 235.

[6] Fitzpatrick, K. K., Darcy, A., & Vierhile, M. (2017). Delivering cognitive behavior therapy using a fully automated conversational agent. JMIR Mental Health, 4(2), e19.

[7] Gupta, M. (2024). ChatGPT-A Generative Pre-Trained Transformer. International Journal of Advanced Research in Science, Communication and Technology, 590–595. https://doi.org/10.48175/ijarsct-15087.

[8] Jiang, L., Numtong, P., & Asavaratana, S. (2025). Sustained interaction with AI chatbots for language learning. Frontiers in Education.

[9] Kumar, R. (2025, March–April). Transforming student evaluation and feedback through AI-driven automated assessment. International Journal for Multidisciplinary Research (IJFMR), 7(2). https://doi.org/10.36948/ijfmr.2025.v07i02.42212.

[10] Kumar, R. (2025, September). Mental health and social media: Reviewing recent research on students with psychiatric issues. GKU Journal of Multidisciplinary Research (GKUJMR), 1(1), 93–97. https://doi.org/10.5281/zenodo.17200033.

[11] Lee, D., Kim, J., & Park, S. (2024). Digital transformation in mental healthcare using AI technologies. Healthcare Informatics Research.

[12] Musundire, A. (2025). Integrating Chatbots Into Educational Management Systems in the Global Intuitions of Higher Learning (pp. 53–72). Igi Global. https://doi.org/10.4018/979-8-3693-8734-4.ch003.

[13] Sharma, R., & Malik, A. (2024). AI-powered virtual mentors in Indian higher education. Education and Information Technologies.

[14] Tiwari, P., Singh, R., & Kaur, N. (2023). Data privacy challenges in AI-based educational systems. International Journal of Information Management.

[15] Vasudevan, K., Nair, S., & Menon, P. (2024). Enhancing student engagement through AI-powered chatbots. Computers & Education.

[16] Winkler, R., & Söllner, M. (2023). Unleashing the potential of chatbots in education: A meta-analysis. Computers & Education.

[17] World Health Organization (WHO). (2023). Ethics and governance of artificial intelligence for health. World Health Organization.

[18] Yigci, D., Eryilmaz, M., Ozcan, A., Yetisen, A. K., & Tasoglu, S. (2024). Large Language Model‐Based Chatbots in Higher Education. Advanced Intelligent Systems, 7(3). https://doi.org/10.1002/aisy.202400429.

How to cite this paper

Navjot Kaur, Dr. Rajinder Kumar (Associate Professor) "Integrating Deep Learning and NLP in AI Chatbots for Education and Mental Health: A State-of-the-Art Review" Iconic Research And Engineering Journals Volume 9 Issue 7 2026 Page 864-868 https://doi.org/10.64388/IREV9I7-1713505
Navjot Kaur, Dr. Rajinder Kumar (Associate Professor) "Integrating Deep Learning and NLP in AI Chatbots for Education and Mental Health: A State-of-the-Art Review" Iconic Research And Engineering Journals, vol. 9, no. 7, Jan. 2026, doi: https://doi.org/10.64388/IREV9I7-1713505
Navjot Kaur, Dr. Rajinder Kumar (Associate Professor) (2026). Integrating Deep Learning and NLP in AI Chatbots for Education and Mental Health: A State-of-the-Art Review. Iconic Research And Engineering Journals, 9(7). doi: https://doi.org/10.64388/IREV9I7-1713505
Navjot Kaur, Dr. Rajinder Kumar (Associate Professor) "Integrating Deep Learning and NLP in AI Chatbots for Education and Mental Health: A State-of-the-Art Review" Iconic Research And Engineering Journals, vol. 9, no. 7, Jan. 2026. Crossref, https://doi.org/10.64388/IREV9I7-1713505
@article{1713505,
      author = {Navjot Kaur, Dr. Rajinder Kumar (Associate Professor)},
      title = {Integrating Deep Learning and NLP in AI Chatbots for Education and Mental Health: A State-of-the-Art Review},
      journal = {Iconic Research And Engineering Journals},
      year = {2026},
      volume = {9},
      number = {7},
      pages = {864-868},
      issn = {2456-8880},
      url = {https://www.irejournals.com/formatedpaper/1713505.pdf},
      abstract = {Artificial Intelligence (AI)?based chatbot?solutions have been capturing increasing attention as tools from which to re-imagine education and mental health support infrastructures. Through a combination of Natural Language Processing (NLP) and deep learning methods, such agents are able?to deliver personalized learning support as well as administrative assistance and initial mental health counseling. The present survey reviews the most recent work (mainly in years 2023?2025) on AI-based chatbots for education and psychology, covering architectures, datasets,?evaluation measures as well as pros and cons and ethical issues. This review highlights research gaps and suggests future work aimed?at building integrated, ethical and human-centered chatbot systems in higher education.},
      keywords = {AI Chatbots, Natural Language Processing, Deep Learning, Education, Mental Health, Conversational Agents.},
      month = {January},
      doi = {https://doi.org/10.64388/IREV9I7-1713505}
  }