Retrieval-augmented generation for educational application: A systematic survey

Survey of Hallucination in Natural Language Generation

Ji, Z., Lee, N., Frieske, R., Yu, T., Su, D., Xu, Y., Ishii, E., Bang, Y. J., Madotto, A., & Fung, P. (2023) · ACM Computing Surveys · doi:10.1145/3571730 · Cited by 5,025 · see citing works

Billion-scale similarity search with GPUs

Johnson, J., Douze, M., & Jegou, H. (2021) · IEEE Transactions on Big Data · doi:10.1109/tbdata.2019.2921572 · Cited by 4,228 · see citing works

Dense passage retrieval for open-domain question answering

Karpukhin, V., Oguz, B., Min, S., Lewis, P., Wu, L., Edunov, S., Chen, D., & Yih, W.-T. (2020) · Proceedings of the 2020 Conference on Empirical Methods in Natural Language Processing (EMNLP) · doi:10.18653/v1/2020.emnlp-main.550 · Cited by 3,575 · see citing works

The probabilistic relevance framework: BM25 and beyond

Robertson, S., & Zaragoza, H. (2009) · Foundations and Trends® in Information Retrieval · doi:10.1561/1500000019 · Cited by 3,374 · see citing works

Conceptualizing AI literacy: An exploratory review

Ng, D. T. K., Leung, J. K. L., Chu, S. K. W., & Qiao, M. S. (2021) · Computers and Education: Artificial Intelligence · doi:10.1016/j.caeai.2021.100041 · Cited by 2,205 · see citing works

Vision, challenges, roles and research issues of Artificial Intelligence in Education

Hwang, G.-J., Xie, H., Wah, B. W., & Gašević, D. (2020) · Computers and Education: Artificial Intelligence · doi:10.1016/j.caeai.2020.100001 · Cited by 1,435 · see citing works

Retrieval-Augmented Generation for Knowledge-Intensive NLP Tasks

Lewis, P., Perez, E., Piktus, A., Petroni, F., Karpukhin, V., Goyal, N., Küttler, H., Lewis, M., Yih, W.-T., Rocktäschel, T., et al. (2020) · UCL Discovery (University College London) · Cited by 1,187 · see citing works

Leveraging Passage Retrieval with Generative Models for Open Domain Question Answering

Izacard, G., & Grave, E. (2021) · Proceedings of the 16th Conference of the European Chapter of the Association for Computational Linguistics: Main Volume · doi:10.18653/v1/2021.eacl-main.74 · Cited by 1,109 · see citing works

Application and theory gaps during the rise of artificial intelligence in education

Chen, X., Xie, H., Zou, D., & Hwang, G.-J. (2020) · Computers and Education: Artificial Intelligence · doi:10.1016/j.caeai.2020.100002 · Cited by 1,003 · see citing works

A Survey on RAG Meeting LLMs: Towards Retrieval-Augmented Large Language Models

Fan, W., Ding, Y., Ning, L., Wang, S., Li, H., Yin, D., Chua, T.-S., & Li, Q. (2024) · Proceedings of the 30th ACM SIGKDD Conference on Knowledge Discovery and Data Mining · doi:10.1145/3637528.3671470 · Cited by 827 · see citing works

Large language models in education: a focus on the complementary relationship between human teachers and ChatGPT

Jeon, J., & Lee, S. (2023) · Education and Information Technologies · doi:10.1007/s10639-023-11834-1 · Cited by 696 · see citing works

Explainability for Large Language Models: A Survey

Zhao, H., Chen, H., Yang, F., Liu, N., Deng, H., Cai, H., Wang, S., Yin, D., & Du, M. (2024) · ACM Transactions on Intelligent Systems and Technology · doi:10.1145/3639372 · Cited by 681 · see citing works

Active Retrieval Augmented Generation

Jiang, Z., Xu, F., Gao, L., Sun, Z., Liu, Q., Dwivedi-Yu, J., Yang, Y., Callan, J., & Neubig, G. (2023) · Proceedings of the 2023 Conference on Empirical Methods in Natural Language Processing · doi:10.18653/v1/2023.emnlp-main.495 · Cited by 497 · see citing works

In-Context Retrieval-Augmented Language Models

Ram, O., Levine, Y., Dalmedigos, I., Muhlgay, D., Shashua, A., Leyton-Brown, K., & Shoham, Y. (2023) · Transactions of the Association for Computational Linguistics · doi:10.1162/tacl_a_00605 · Cited by 449 · see citing works

Security and Privacy Challenges of Large Language Models: A Survey

Das, B. C., Amini, M. H., & Wu, Y. (2025) · ACM Computing Surveys · doi:10.1145/3712001 · Cited by 445 · see citing works

Improving language models by retrieving from trillions of tokens

Borgeaud, S., Mensch, A., Hoffmann, J., Cai, T., Rutherford, E., Millican, K., Driessche, G. V. D., Lespiau, J.-B., Damoc, B., Clark, A., et al. (2021) · arXiv · doi:10.48550/arxiv.2112.04426 · Cited by 382 · see citing works

Untitled work

(2020) · International Conference on Machine Learning · Cited by 358 · see citing works

ColBERTv2: Effective and Efficient Retrieval via Lightweight Late Interaction

Santhanam, K., Khattab, O., Saad-Falcon, J., Potts, C., & Zaharia, M. (2022) · Proceedings of the 2022 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies · doi:10.18653/v1/2022.naacl-main.272 · Cited by 353 · see citing works

When not to trust language models: Investigating effectiveness of parametric and non-parametric memories

Mallen, A., Asai, A., Zhong, V., Das, R., Khashabi, D., & Hajishirzi, H. (2023) · Proceedings of the 61st Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers) · doi:10.18653/v1/2023.acl-long.546 · Cited by 340 · see citing works

Improving the domain adaptation of retrieval augmented generation (RAG) models for open domain question answering

Siriwardhana, S., Weerasekera, R., Wen, E., Kaluarachchi, T., Rana, R., & Nanayakkara, S. (2023) · Transactions of the Association for Computational Linguistics · doi:10.1162/tacl_a_00530 · Cited by 337 · see citing works

A multi-perspective study on Artificial Intelligence in Education: grants, conferences, journals, software tools, institutions, and researchers

Chen, X., Xie, H., & Hwang, G. (2020) · Computers and Education Artificial Intelligence · doi:10.1016/j.caeai.2020.100005 · Cited by 306 · see citing works

Locating and Editing Factual Associations in GPT

Meng, K., Bau, D., Andonian, A., & Belinkov, Y. (2022) · arXiv · doi:10.48550/arxiv.2202.05262 · Cited by 230 · see citing works

Atlas: Few-shot Learning with Retrieval Augmented Language Models

Izacard, G., Lewis, P., Lomeli, M., Hosseini, L., Petroni, F., Schick, T., Dwivedi-Yu, J., Joulin, A., Riedel, S., & Grave, E. (2022) · arXiv · doi:10.48550/arxiv.2208.03299 · Cited by 213 · see citing works

An LLM-Driven Chatbot in Higher Education for Databases and Information Systems

Neumann, A. T., Yin, Y., Sowe, S. K., Decker, S., & Jarke, M. (2024) · IEEE Transactions on Education · doi:10.1109/te.2024.3467912 · Cited by 187 · see citing works

Teaching CS50 with AI: Leveraging Generative Artificial Intelligence in Computer Science Education

Liu, R., Zenke, C., Liu, C., Holmes, A., Thornton, P., & Malan, D. J. (2024) · Proceedings of the 55th ACM Technical Symposium on Computer Science Education V. 1 · doi:10.1145/3626252.3630938 · Cited by 185 · see citing works

Unsupervised Dense Information Retrieval with Contrastive Learning

Izacard, G., Caron, M., Hosseini, L., Riedel, S., Bojanowski, P., Joulin, A., & Grave, E. (2021) · arXiv · doi:10.48550/arxiv.2112.09118 · Cited by 172 · see citing works

Seven Failure Points When Engineering a Retrieval Augmented Generation System

Barnett, S., Kurniawan, S., Thudumu, S., Brannelly, Z., & Abdelrazek, M. (2024) · Proceedings of the IEEE/ACM 3rd International Conference on AI Engineering - Software Engineering for AI · doi:10.1145/3644815.3644945 · Cited by 155 · see citing works

An Unsupervised Sentence Embedding Method by Mutual Information Maximization

Zhang, Y., He, R., Liu, Z., Lim, K. H., & Bing, L. (2020) · Conference on Empirical Methods in Natural Language Processing (EMNLP) · doi:10.18653/v1/2020.emnlp-main.124 · Cited by 152 · see citing works

Locating and Editing Factual Associations in GPT

Meng, K., Bau, D., Andonian, A., & Belinkov, Y. (2022) · Advances in Neural Information Processing Systems 35 · doi:10.52202/068431-1262 · Cited by 149 · see citing works

Advances in Sentiment Analysis - Techniques, Applications, and Challenges

Li, J. (2023) · Artificial intelligence · doi:10.5772/intechopen.111293 · Cited by 137 · see citing works

Understanding EFL students’ use of self-made AI chatbots as personalized writing assistance tools: A mixed methods study

Guo, K., & Li, D. (2024) · System · doi:10.1016/j.system.2024.103362 · Cited by 129 · see citing works

Mobile Assisted Language Learning

Stockwell, G. (2021) · Cambridge University Press eBooks · doi:10.1017/9781108652087 · Cited by 124 · see citing works

Re2G: Retrieve, Rerank, Generate

Glass, M., Rossiello, G., Chowdhury, M. F. M., Naik, A., Cai, P., & Gliozzo, A. (2022) · Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies (NAACL-HLT) · doi:10.18653/v1/2022.naacl-main.194 · Cited by 122 · see citing works

MCQGen: A Large Language Model-Driven MCQ Generator for Personalized Learning

Hang, C. N., Tan, C. W., & Yu, P.-D. (2024) · IEEE Access · doi:10.1109/access.2024.3420709 · Cited by 112 · see citing works

Information fusion and artificial intelligence for smart healthcare: a bibliometric study

Chen, X., Xie, H., Li, Z., Cheng, G., Leng, M., & Wang, F. L. (2022) · Information Processing & Management · doi:10.1016/j.ipm.2022.103113 · Cited by 101 · see citing works

Exploring generative AI in higher education: a RAG system to enhance student engagement with scientific literature

Thüs, D., Malone, S., & Brünken, R. (2024) · Frontiers in Psychology · doi:10.3389/fpsyg.2024.1474892 · Cited by 87 · see citing works

Effect of an AI-based chatbot on students’ learning performance in alternate reality game-based museum learning

Liang, H., Hwang, G., Hsu, T., & Yeh, J. (2024) · British Journal of Educational Technology · doi:10.1111/bjet.13448 · Cited by 78 · see citing works

LAMB: An open-source software framework to create artificial intelligence assistants deployed and integrated into learning management systems

Alier, M., Pereira, J., García‐Peñalvo, F. J., Guerrero, M. J. C., & Cabré, J. (2024) · Computer Standards & Interfaces · doi:10.1016/j.csi.2024.103940 · Cited by 76 · see citing works

End-to-End Training of Neural Retrievers for Open-Domain Question Answering

Sachan, D. S., Patwary, M. A., Shoeybi, M., Kant, N., Ping, W., Hamilton, W. L., & Catanzaro, B. (2021) · Annual Meeting of the Association for Computational Linguistics · doi:10.18653/v1/2021.acl-long.519 · Cited by 74 · see citing works

Jill Watson: A Virtual Teaching Assistant Powered by ChatGPT

Taneja, K., Maiti, P., Kakar, S., Guruprasad, P., Rao, S., & Goel, A. K. (2024) · Lecture notes in computer science · doi:10.1007/978-3-031-64302-6_23 · Cited by 70 · see citing works

ChatGPT versus a customized AI chatbot (Anatbuddy) for anatomy education: A comparative pilot study

Arun, G., Perumal, V., Urias, F. P. J. B., Ler, Y. E., Tan, B. W. T., Vallabhajosyula, R., Tan, E., Ng, O., Ng, K. B., & Mogali, S. R. (2024) · Anatomical Sciences Education · doi:10.1002/ase.2502 · Cited by 68 · see citing works

Enhancing student engagement in online collaborative writing through a generative AI-based conversational agent

Hu, W., Tian, J., & Li, Y. (2024) · The Internet and Higher Education · doi:10.1016/j.iheduc.2024.100979 · Cited by 66 · see citing works

Chain-of-Note: Enhancing Robustness in Retrieval-Augmented Language Models

Yu, W., Zhang, H., Pan, X., Cao, P., Ma, K., Li, J., Wang, H., & Yu, D. (2024) · Conference on Empirical Methods in Natural Language Processing (EMNLP) · doi:10.18653/v1/2024.emnlp-main.813 · Cited by 56 · see citing works

Lift Yourself Up: Retrieval-augmented Text Generation with Self-Memory

Chen, X., Luo, D., Chen, X., Liu, L., Zhao, D., & Yan, R. (2023) · neural information processing systems · doi:10.52202/075280-1899 · Cited by 53 · see citing works

Can Small Language Models With Retrieval-Augmented Generation Replace Large Language Models When Learning Computer Science?

Liu, S., Yu, Z., Huang, F., Bulbulia, Y., Bergen, A., & Liut, M. (2024) · ACM Conference on Innovation and Technology in Computer Science Education (ITiCSE) · doi:10.1145/3649217.3653554 · Cited by 48 · see citing works

Cross-Data Knowledge Graph Construction for LLM-enabled Educational Question-Answering System: A Case Study at HCMUT

Bui, T. V., Tran, O., Nguyen, P. H., Ho, B., Nguyen, L., Bui, T., & Quan, T. (2024) · doi:10.1145/3643479.3662055 · Cited by 40 · see citing works

VizChat: Enhancing Learning Analytics Dashboards with Contextualised Explanations Using Multimodal Generative AI Chatbots

Yan, L., Zhao, L., Echeverria, V., Jin, Y., Alfredo, R., Li, X., Gaševi’c, D., & Martinez-Maldonado, R. (2024) · Lecture Notes in Computer Science · doi:10.1007/978-3-031-64299-9_13 · Cited by 40 · see citing works

Developing a computer-based tutor utilizing Generative Artificial Intelligence (GAI) and Retrieval-Augmented Generation (RAG)

Lee, Y. (2024) · Education and Information Technologies · doi:10.1007/s10639-024-13129-5 · Cited by 40 · see citing works

Evaluating Students’ Open-ended Written Responses with LLMs: Using the RAG Framework for GPT-3.5, GPT-4, Claude-3, and Mistral-Large

Jauhiainen, J. S., & Guerra, A. G. (2024) · Advances in Artificial Intelligence and Machine Learning · doi:10.54364/aaiml.2024.44177 · Cited by 38 · see citing works

RHO: Reducing Hallucination in Open-domain Dialogues with Knowledge Grounding

Ji, Z., Liu, Z., Lee, N., Yu, T., Wilie, B., Zeng, M., & Fung, P. (2023) · Findings of the Association for Computational Linguistics: ACL 2023 · doi:10.18653/v1/2023.findings-acl.275 · Cited by 37 · see citing works

Enlarged Education – Exploring the Use of Generative AI to Support Lecturing in Higher Education

Hennekeuser, D., Vaziri, D. D., Golchinfar, D., Schreiber, D., & Stevens, G. (2024) · International Journal of Artificial Intelligence in Education · doi:10.1007/s40593-024-00424-y · Cited by 35 · see citing works

Neuro-Symbolic Language Modeling with Automaton-augmented Retrieval

Alon, U., Xu, F. F., He, J., Sengupta, S., Roth, D., & Neubig, G. (2022) · arXiv · doi:10.48550/arxiv.2201.12431 · Cited by 32 · see citing works

Effects of a concept mapping-guided virtual laboratory learning approach on students’ science process skills and behavioral patterns

Chen, K., Hwang, G., & Chen, M. A. (2024) · Educational Technology Research and Development · doi:10.1007/s11423-024-10348-y · Cited by 29 · see citing works

Virtual Reality and Language Models, a New Frontier in Learning.

Izquierdo-Domenech, J., Linares-Pellicer, J., & Ferri-Molla, I. (2024) · International Journal of Interactive Multimedia and Artificial Intelligence · doi:10.9781/ijimai.2024.02.007 · Cited by 28 · see citing works

Investigating the utilization and impact of large language model-based intelligent teaching assistants in flipped classrooms

Teng, D., Wang, X., Xia, Y., Zhang, Y., Tang, L., Chen, Q., Zhang, R., Xie, S., & Yu, W. (2024) · Education and Information Technologies · doi:10.1007/s10639-024-13264-z · Cited by 27 · see citing works

Mitigating risks, embracing potential: a framework for integrating generative artificial intelligence in geographical and environmental education

Lane, R. (2025) · International Research in Geographical and Environmental Education · doi:10.1080/10382046.2025.2458561 · Cited by 26 · see citing works

Knowledge-Augmented Language Model Verification

Baek, J., Jeong, S., Kang, M., Park, J. C., & Hwang, S. (2023) · Conference on Empirical Methods in Natural Language Processing (EMNLP) · doi:10.18653/v1/2023.emnlp-main.107 · Cited by 21 · see citing works

Faculty Perspectives on the Potential of RAG in Computer Science Higher Education

Dakshit, S. (2024) · Conference on Information Technology Education · doi:10.1145/3686852.3686864 · Cited by 21 · see citing works

CHATED: A CHATBOT LEVERAGING CHATGPT FOR AN ENHANCED LEARNING EXPERIENCE IN HIGHER EDUCATION

Wang, K., Ramos, J., & Lawrence, R. (2024) · INTED proceedings · doi:10.21125/inted.2024.1722 · Cited by 20 · see citing works

HiTA: A RAG-Based Educational Platform that Centers Educators in the Instructional Loop

Liu, C., Hoang, L., Stolman, A., & Wu, B. (2024) · Lecture notes in computer science · doi:10.1007/978-3-031-64299-9_37 · Cited by 19 · see citing works

Addressing Technical Challenges in Large Language Model-Driven Educational Software System

Chondamrongkul, N., Hristov, G., & Temdee, P. (2025) · IEEE Access · doi:10.1109/access.2025.3531380 · Cited by 18 · see citing works

Comparing Different Approaches to Generating Mathematics Explanations Using Large Language Models

Prihar, E., Lee, M., Hopman, M., Kalai, A. T., Vempala, S., Wang, A., Wickline, G., Murray, A., & Heffernan, N. (2023) · Communications in Computer and Information Science · doi:10.1007/978-3-031-36336-8_45 · Cited by 18 · see citing works

Automatic Feedback Generation on K-12 Students' Data Science Education by Prompting Cloud-based Large Language Models

Fung, S. C. E., Wong, M. F., & Tan, C. W. (2024) · ACM Conference on Learning @ Scale (L@S) · doi:10.1145/3657604.3664673 · Cited by 18 · see citing works

Improving Assessment of Tutoring Practices using Retrieval-Augmented GenerationPreprint

Zifei, Lin, J., Gurung, A., Thomas, D. R., Chen, E., Borchers, C., Gupta, S., & Koedinger, K. R. (2024) · arXiv (Cornell University) · doi:10.48550/arxiv.2402.14594 · Cited by 17 · see citing works

Personalized Pedagogy Through a LLM-Based Recommender System

Dehbozorgi, N., Kunuku, M. T., & Pouriyeh, S. (2024) · Communications in computer and information science · doi:10.1007/978-3-031-64312-5_8 · Cited by 16 · see citing works

Security and Privacy Challenges of AIGC in Metaverse: A Comprehensive Survey

Zhang, S., Li, H., Sun, K., Chen, H., Wang, Y., & Li, S. (2025) · ACM Computing Surveys · doi:10.1145/3729419 · Cited by 16 · see citing works

Automatic Lesson Plan Generation via Large Language Models with Self-critique Prompting

Zheng, Y., Li, X., Huang, Y., Liang, Q., Guo, T., Hou, M., Gao, B., Tian, M., Liu, Z., & Luo, W. (2024) · Communications in computer and information science · doi:10.1007/978-3-031-64315-6_13 · Cited by 15 · see citing works

Supporting Teaching-to-the-Curriculum by Linking Diagnostic Tests to Curriculum Goals: Using Textbook Content as Context for Retrieval-Augmented Generation with Large Language Models

Li, X., Henriksson, A., Duneld, M., Nouri, J., & Wu, Y. (2024) · Lecture notes in computer science · doi:10.1007/978-3-031-64302-6_9 · Cited by 15 · see citing works

Leveraging GPT-4 for Accuracy in Education: A Comparative Study on Retrieval-Augmented Generation in MOOCs

Miladi, F., Psyché, V., & Daniel Lemire, A. (2024) · Communications in computer and information science · doi:10.1007/978-3-031-64315-6_40 · Cited by 14 · see citing works

Leveraging Lecture Content for Improved Feedback: Explorations with GPT-4 and Retrieval Augmented Generation

Jacobs, S., & Jaschke, S. (2024) · 2024 36th International Conference on Software Engineering Education and Training (CSEE&T) · doi:10.1109/cseet62301.2024.10663001 · Cited by 13 · see citing works

SteLLA: A Structured Grading System Using LLMs with RAG

Qiu, H., White, B. F., Ding, A., da Costa, R. F., Hachem, A., Ding, W., & Chen, P. (2024) · IEEE International Conference on Big Data (BigData) · doi:10.1109/bigdata62323.2024.10825385 · Cited by 12 · see citing works

The Potential Clinical Utility of the Customized Large Language Model in Gastroenterology: A Pilot Study

Gong, E. J., Bang, C. S., Lee, J. J., Park, J., Kim, E., Kim, S., Kimm, M., & Choi, S.-H. (2024) · Bioengineering · doi:10.3390/bioengineering12010001 · Cited by 11 · see citing works

Investigating the Predictive Potential of Large Language Models in Student Dropout Prediction

Aboukacem, A., Berrada, I., Bergou, E. H., Iraqi, Y., & Mekouar, L. (2024) · Lecture notes in computer science · doi:10.1007/978-3-031-64299-9_34 · Cited by 10 · see citing works

From Queries to Courses: SKYRAG’s Revolution in Learning Path Generation via Keyword-Based Document Retrieval

Soekamto, Y. S., Limanjaya, L. C., Purwanto, Y. K., & Kang, D.-K. (2025) · IEEE Access · doi:10.1109/access.2025.3535618 · Cited by 9 · see citing works

Enhancing Python Learning Through Retrieval-Augmented Generation: A Theoretical and Applied Innovation in Generative AI Education

Ko, H.-T., Liu, Y.-K., Tsai, Y.-C., & Suen, S. (2024) · Lecture notes in computer science · doi:10.1007/978-3-031-65884-6_17 · Cited by 9 · see citing works

Retrieval-augmented Generation to Improve Math Question-Answering: Trade-offs Between Groundedness and Human Preference

Henkel, O., Levonian, Z., Li, C., & Postle, M. (2024) · Zenodo (CERN European Organization for Nuclear Research) · doi:10.5281/zenodo.12729823 · Cited by 9 · see citing works

Evaluating a GPT-4 and Retrieval-Augmented Generation-Based Conversational Agent to Enhance Learning Experience in a MOOC

Miladi, F., Psyché, V., Diattara, A., Mawas, N. E., & Daniel Lemire, A. (2025) · International Conference on Computer Supported Education · doi:10.5220/0013366100003932 · Cited by 7 · see citing works

SyllabusQA: A Course Logistics Question Answering Dataset

Fernandez, N., Scarlatos, A., & Lan, A. (2024) · Proceedings of the conference - Association for Computational Linguistics. Meeting · doi:10.18653/v1/2024.acl-long.557 · Cited by 7 · see citing works

A RAG-based Feedback Tool to Augment UML Class Diagram Learning

Ardimento, P., Bernardi, M. L., Cimitile, M., & Scalera, M. (2024) · ACM/IEEE International Conference on Model Driven Engineering Languages and Systems (MODELS) · doi:10.1145/3652620.3687784 · Cited by 7 · see citing works

Integrating Generative Artificial Intelligence into Supply Chain Management Education Using the SCOR Model

Ehrenthal, J. C. F., Gachnang, P., Loran, L., Rahms, H., & Schenker, F. (2024) · Lecture notes in business information processing · doi:10.1007/978-3-031-61003-5_6 · Cited by 6 · see citing works

Comparative Performance of GPT-4, RAG-Augmented GPT-4, and Students in MOOCs

Miladi, F., Psyché, V., & Daniel Lemire, A. (2024) · Communications in computer and information science · doi:10.1007/978-3-031-65996-6_7 · Cited by 5 · see citing works

Shaping Programming and Data Science Education: Insights from GenAI Technical Book Trends

Bakharia, A., & Abdi, S. (2024) · IEEE International Conference on Advanced Learning Technologies (ICALT) · doi:10.1109/icalt61570.2024.00040 · Cited by 5 · see citing works

Examining the Feasibility of AI-Generated Questions in Educational Settings

Zeghouani, O., Ali, Z., van Dijkhuizen, W. S., Hong, J., & Clos, J. (2024) · International Symposium on Trustworthy Autonomous Systems (TAS) · doi:10.1145/3686038.3686652 · Cited by 5 · see citing works

ScienceDirect Topic Pages: A Knowledge Base of Scientific Concepts Across Various Science Domains

Capari, A., Azarbonyad, H., Tsatsaronis, G., Afzal, Z., & Dunham, J. (2024) · International ACM SIGIR Conference on Research and Development in Information Retrieval (SIGIR) · doi:10.1145/3626772.3661353 · Cited by 5 · see citing works

HICON AI: Higher Education Counseling Bot

Singla, A. D., Tripathi, S., & Victoria, A. H. (2024) · International Conference on Pervasive Computing and Social Networking (ICPCSN) · doi:10.1109/icpcsn62568.2024.00131 · Cited by 4 · see citing works

Scalable Mentoring Support with a Large Language Model Chatbot

Soliman, H., Kravčík, M., Neumann, A. T., Yin, Y., Pengel, N., & Haag, M. (2024) · Lecture notes in computer science · doi:10.1007/978-3-031-72312-4_37 · Cited by 4 · see citing works

Facilitating university admission using a chatbot based on large language models with retrieval-augmented generation

Chen, Z., Zou, D., Xie, H., Lou, H., & Pang, Z. (2024) · Rare & Special e-Zone (The Hong Kong University of Science and Technology) · doi:10.30191/ets.202410_27(4).tp02 · Cited by 4 · see citing works

Semantic Search Engine Within Anatomy Books: A BERT-Based Model for Medical Students

Malhi, M. E., Talbi, M., Lamti, S., & Kerzazi, N. (2024) · Information systems engineering and management · doi:10.1007/978-3-031-66850-0_12 · Cited by 2 · see citing works

RAG for Question-Answering for Vocal Training Based on Domain Knowledge Base

Leung, C.-H. J., Yi, Y., Kuai, L., Li, Z., Yeung, S.-K. A., Lee, K.-W. J., Ho, K.-H. K., & Hung, K. (2024) · International Conference on Behavioral, Economic, and Socio-Cultural Computing · doi:10.1109/besc64747.2024.10780718 · Cited by 2 · see citing works

Custom Generative Artificial Intelligence Tutors in Action: An Experimental Evaluation of Prompt Strategies in STEM Education

Gabrovšek, R., & Rihtaršič, D. (2025) · Sustainability · doi:10.3390/su17219508 · Cited by 17 · see citing works

NOVA: A Retrieval-Augmented Generation Assistant in Spanish for Parallel Computing Education with Large Language Models

León-Paredes, G. A., Alba-Narváez, L. A., & Paltin-Guzmán, K. D. (2025) · Applied Sciences · doi:10.3390/app15158175 · Cited by 6 · see citing works

Artificial intelligence reliability in implant dentistry: A comparative analysis of clinical accuracy and hallucination patterns across multiple language models

Hooshiar, M. H. (2026) · The Journal of Prosthetic Dentistry · doi:10.1016/j.prosdent.2025.11.005 · Cited by 5 · see citing works

Comparing traditional AI, agentic ai and agentic rag for dialogic online education

English, V. (2025) · Asian Journal of Education and Training · doi:10.20448/edu.v11i4.7926 · Cited by 5 · see citing works

Transforming Applied Behavior Analysis Therapy: An Internet of Things-Guided, Retrieval-Augmented Large Language Model Framework

Qi, H., Chung-Ho, S., Chan, R. Y.-Y., & Wong, C. M. V. (2025) · IEEE Access · doi:10.1109/access.2025.3600316 · Cited by 5 · see citing works

Evaluation of Chunking Strategies in RAG Application for Explicit Retrieval on Indonesian Language Scientific Papers

Haviana, S. F. C., Riyadi, M. A., & Kusumaningrum, R. (2025) · Proceeding of the Electrical Engineering Computer Science and Informatics · doi:10.1109/eecsi67060.2025.11290624 · Cited by 4 · see citing works

Food additive lens: an on-device AI application for real-time science-based consumer education on food additives using retrieval-augmented generation

Feng, Y., Wang, Y.-C., Wang, X., Zhao, B., Bi, J., Han, S., & Luo, Y. (2026) · Digital Discovery · doi:10.1039/d5dd00444f · Cited by 4 · see citing works

AI for All: Adaptive, Accessible, and Inclusive Learning Experiences in the Age of Intelligent LMSs

Angeioplastis, A., Konstantakis, M., Aliprantis, J., Ordoumpozanis, K., Varsamis, D., & Tsimpiris, A. (2026) · Information · doi:10.3390/info17020216 · Cited by 3 · see citing works

KAG: A Scalable Knowledge-Augmented Generation System for Educational Content Management

Hasan, H., Ismail, A., Mohanna, A., & Chehab, A. (2025) · International Conference on Foundation and Large Language Models (FLLM) · doi:10.1109/fllm67465.2025.11391105 · Cited by 3 · see citing works

A Hybrid TF-IDF and Knowledge Graph-Enhanced Retrieval-Augmented Generation Framework with Large Language Models for Domain-Aware Question Answering

Utami, L. A. (2026) · Journal of Applied Data Sciences · doi:10.47738/jads.v7i2.1136 · Cited by 3 · see citing works

Can large language models generate exam questions comparable to humans? A systematic review and meta-analysis study in medical education

Saleem, N. H., Amaranathan, J., Dandoush, A., Rye, S., King, P. T., & Chin, M. H. (2026) · Medical Teacher · doi:10.1080/0142159x.2026.2691072 · Cited by 3 · see citing works

Large Language Models for Future Internet Ecosystems: A Taxonomy-Based Review of Smart IoT, Edge Intelligence, and Autonomous AI

Ahmadzadeh, S., Karthick, G., & Alsafi, T. (2026) · Future Internet · doi:10.3390/fi18080393 · Cited by 3 · see citing works

Designing Reliable LLM Systems for AI-Assisted Engineering Education

Venkatachalapathy, R. (2026) · IEEE International Conference on Innovation, Ethics & Emerging Tech in Engineering and Computing Education (IE2C) · doi:10.1109/ie2c69620.2026.11663036 · Cited by 3 · see citing works

Large Language Model Failures in Higher Education: Causes and Prevention

Ternikov, A. (2025) · Computer · doi:10.1109/mc.2025.3595485 · Cited by 2 · see citing works

A Scalable and Low-Cost Mobile RAG Architecture for AI-Augmented Learning in Higher Education

Bojorque, R., Plaza, A., Morquecho, P., & Moscoso, F. (2026) · Applied Sciences · doi:10.3390/app16020963 · Cited by 2 · see citing works

Educational Application of RAG-based LLMs

Khan, A., Chandekar, S., Baikar, A., Kanade, A., Kadam, S., & Kadam, V. (2025) · International Conference on Evolutionary Computing and Mobile Sustainable Networks (ICECMSN) · doi:10.1109/icecmsn68058.2025.11383555 · Cited by 2 · see citing works

CLARE: A Category-Aware RAG-Based Framework for Recommending Learning Objects in Education and Professional Training

Ennaceur, I., Elghazel, H., Aussem, A., Lefebvre, G., & Sonnati, M. O. (2026) · Lecture notes in computer science · doi:10.1007/978-981-95-7394-3_6 · Cited by 2 · see citing works

From automation to augmentation: a retrieval-augmented large language model framework for reshaping learning experiences in higher education

Lingling, W., Sun, S., & Liu, X. (2026) · Frontiers in Psychology · doi:10.3389/fpsyg.2026.1870870 · Cited by 2 · see citing works

A systematic review of generative AI in higher education learning analytics and decision support

Razami, H. H., Singh, A. D., Sampedro, G. A. R., Kovilpillai, J. J. S., Raza, F. A., Anwar, R., Hamdan, A., & Konno, F. (2026) · Discover Artificial Intelligence · doi:10.1007/s44163-026-01888-8 · Cited by 2 · see citing works

Retrieval‐Augmented Generation for Large Language Models: Evolution, Architectures, Applications, and Challenges (2020–2025)

Faridi, A. R., Masood, F., Keshvi, & Yunus, T. (2026) · Wiley Interdisciplinary Reviews Data Mining and Knowledge Discovery · doi:10.1002/widm.70122 · Cited by 2 · see citing works

Utilizing Retrieval Augmented Generation (RAG)-Based Chatbots as an Innovative Learning Tool in Higher Education: A Case Study on the Use of Digital Learning Resources

Murti, Y. R., Ramadhani, D. P., & Irawan, H. (2025) · IJOEM Indonesian Journal of E-learning and Multimedia · doi:10.58723/ijoem.v4i3.510 · Cited by 2 · see citing works

A Retrieval-Augmented Generation System for Automated Mind Map Creation and Enhanced Learning in Higher Education

Arifin, M. L., Nugroho, M. Y., Irsyad, A. Z., & Rabiha, S. G. (2025) · IEEE Information Technology International Seminar (ITIS) · doi:10.1109/itis67966.2025.11308750 · Cited by 1 · see citing works

Retrieval-Augmented Large Language Models for Computer Architecture Learning and Design Assistance

de Souza, W. J., Neto, H. T. M., & de Freitas, H. C. (2025) · International Journal of Computer Architecture Education. · doi:10.5753/ijcae.2025.6540 · Cited by 1 · see citing works

Generative Artificial Intelligence Student Feedback in Large University Accounting Classes: Prompting Techniques

Madwe, M. C. (2026) · International Journal of Sustainability in Business and Economics · doi:10.51137/wrp.ijsbe.575 · Cited by 1 · see citing works

Revolutionizing Education

Thomas, A. A., Baby, R., Davidson, B. G. J., & George, J. P. (2026) · Advances in computational intelligence and robotics book series · doi:10.4018/979-8-3373-4521-5.ch014 · Cited by 1 · see citing works

Research on Retrieval-Augmented Generation Method Based on Dynamic Knowledge Indexing and Semantic Alignment Optimization

Shao, Y., Du, Z. Y., Liu, B., Wen, H., Zhang, X., & Zhang, C. (2026) · International Conference on Artificial Intelligence and Social Network Systems (AISNS) · doi:10.1109/aisns67921.2026.11440489 · Cited by 1 · see citing works

Minds versus machines: ten axioms for planning practice and research in the age of large language models

Abusaada, H., & Elshater, A. M. (2026) · Planning Practice and Research · doi:10.1080/02697459.2026.2646633 · Cited by 1 · see citing works

An LLM-Based Multi-Path Question Answering System with XGBoost Routing and Threshold-Based Refusal

Dai, B., Li, C., Cao, Y., Ling, J., & Liu, X. (2026) · Electronics · doi:10.3390/electronics15091845 · Cited by 1 · see citing works

Pengembangan Chatbot WhatsApp Berbasis Retrieval-Augmented Generation (RAG) dan OpenAI untuk Penyediaan Jawaban Akurat dari Dokumen Aturan Organisasi

Imaduddin, M., Susanto, R., & Pradana, A. I. (2026) · Adopsi Teknologi dan Sistem Informasi (ATASI) · doi:10.30872/atasi.v5i1.3472 · Cited by 1 · see citing works

EduMSRA: A Multi-Source Educational Research Agent Integrating Retrieval-Augmented Generation and Model Context Protocol for Adaptive Intelligent Tutoring Systems

Ho, T.-L., & Lam, T.-P. (2026) · Applied Sciences · doi:10.3390/app16094400 · Cited by 1 · see citing works

Retrieval-Augmented Generation (RAG): Architecture, Ethical Challenges, and Optimization Strategies

Gade, S. R., Ponna, D., Shah, J., & Patel, K. A. (2026) · International Conference on Machine Learning and Autonomous Systems (ICMLAS) · doi:10.1109/icmlas67792.2026.11483907 · Cited by 1 · see citing works

Designing an AI assistant to support independent learning in first -and second-year students

Zakharov, A. A., Zakharova, I. G., Шабалин, А. М., & Nguyen, Q. H. (2026) · The Education and science journal · doi:10.17853/1994-5639-2026-6-163-200 · Cited by 1 · see citing works

BanglaRAG: Building a Low-Cost Multilingual Knowledge Backbone for an Agentic LMS Assistant

Khandaker, S., Hasan, M. M., Roy, S. K., Pranto, F. S., Mamun, A. A., & Haque, A. (2026) · IEEE International Conference on Quantum Photonics, Artificial Intelligence & Networking (QPAIN) · doi:10.1109/qpain69676.2026.11545902 · Cited by 1 · see citing works

GamifiedLM: Co-Designing an LLM-Driven Gamified Learning App with University Students to Mitigate Learning Difficulties

Tang, K., Chen, K.-W., Gopi, S., Xie, L., Quinlan, M., & Cho, Y. (2026) · Designing Interactive Systems Conference · doi:10.1145/3800645.3812916 · Cited by 1 · see citing works

Responsible generative AI in higher education: Expert validation of a compact RAG for technical and pedagogical robustness

Debets, T., Banihashem, S. K., Wenniger, G. M. D. B., Brinke, D. J.-T., Vos, T. E. J., & Camp, G. (2026) · Innovations in Education and Teaching International · doi:10.1080/14703297.2026.2686372 · Cited by 1 · see citing works

Design and Evaluation of a RAG-Based Educational Assistant Grounded in Course Materials: A Case Study in Vocational Training

Burillo, J. D., Neira, R. B. H., & Borrás-Gené, O. (2026) · Big Data and Cognitive Computing · doi:10.3390/bdcc10090299 · Cited by 1 · see citing works

Student-designed educational resources for Lean: exploring ChatGPT and Retrieval-Augmented Generation

Cooper, B., Fujita, T., Marasingha, G., & Thoma, A. (2026) · ZDM · doi:10.1007/s11858-026-01808-1 · Cited by 1 · see citing works

Comparing FAQ-Based and Retrieval-Augmented Generation Chatbots for Academic Service Question Answering

Suherwin, S., Zainuddin, M., & Rachmat, R. (2026) · Jurnal Teknologi Terapan G-Tech · doi:10.70609/g-tech.v10i3.10019 · Cited by 1 · see citing works

RESEARCH INTO THE APPLICATION OF VECTOR DATABASES IN GENERATIVE ARTIFICIAL INTELLIGENCE

Smirnov, O. A., Tkachuk, R., Kozirova, N., Konstantynova, L., Конопліцька-Слободенюк, О. К., Якименко, Н. М., & Smirnov, S. A. (2026) · Cybersecurity Education Science Technique · doi:10.28925/2663-4023.2026.33.1248 · Cited by 1 · see citing works

Designing a Local RAG-Based Intelligent Tutoring System for Domain-Specific Education

Gala, A. D. C. O. S., Marcondes, F. S., Machado, J. M., & Nováis, P. (2026) · Lecture notes in computer science · doi:10.1007/978-981-92-2891-1_13 · Cited by 1 · see citing works

Cog-CoT: A Cognitive Chain-of-Thought Framework for Bloom's Taxonomy-Aligned Educational Question Answering

Muzli, A., Anggraini, R. N. E., & Purwitasari, D. (2026) · Journal of Computing Theories and Applications · doi:10.62411/jcta.17084 · Cited by 1 · see citing works

A Criteria-Governed Human-in-the-Loop Information System Architecture for Explainable AI-Assisted Learning and Preliminary Assessment

Жакыпбеков, С. Ж., Bykov, A. A., Yеrmakova, V. A., Zhuginissova, A., & Vasquez, M. (2026) · Informatics · doi:10.3390/informatics13110179 · Cited by 1 · see citing works

Citation-Enforced RAG for Fiscal Document Intelligence: Cited, Explainable Knowledge Retrieval in Tax Compliance

Shanivendra, A. C. (2026) · arXiv · doi:10.48550/arxiv.2603.14170

A REVIEW OF MODERN APPROACHES TO AUTOMATING THE REVIEW OF TEXTS OF COMPLEX ACADEMIC PAPERS BY STUDENTS AND YOUNG SCIENTISTS

Bondarev, Y. A., Tereschenko, V. V., Martsinkevich, V., & Dukhanov, A. V. (2025) · Современные наукоемкие технологии (Modern High Technologies) · doi:10.17513/snt.40424

Improved Deep Learning-Based Optical Mark Recognition for Automated Correction

Labrassi, M., & Ouaarab, A. (2025) · Lecture notes in computer science · doi:10.1007/978-3-032-10486-1_30

Aduvia: A Multi-Purpose AI-Powered Learning Management System (LMS)

Megahed, A. A., Ibrahim, A. M., Moussa, A., Arnous, M. F., Elmoataz, Y., Aslan, H. K., Abu-Krisha, I. A., & Abdelsattar, M. M. (2025) · Novel Intelligent and Leading Emerging Sciences Conference (NILES) · doi:10.1109/niles68063.2025.11231978

Adaptive Fashion Recommendation Using Retrieval-Augmented Generation and Real-Time Vector Search

Saranya, E., Sabarinathan, B., Mohaideen Arsath., M., C, S. K. J., & Sri Gurusankar., R. (2025) · International Conference on Intelligent Communication Networks and Computational Techniques (ICICNCT) · doi:10.1109/icicnct66124.2025.11232834

A RAG-ASAG HYBRID MODEL FOR FORMATIVE ASSESSMENT IN INFORMATICS EDUCATION AT UNIVERSITY

Aliyeva, A. (2025) · Cybernetics and Systems Analysis · doi:10.1007/s10559-025-00838-z

Optimizing Document Retrieval in Digital Learning Through Multi-Strategy Chunking and Hybrid Relevance Scoring

Tiwari, K., Chowdhury, A. R., & Lee, A. (2025) · IEEE Digital Education and MOOCS Conference (DEMOcon) · doi:10.1109/democon65705.2025.11282550

A Hybrid Semantic Question Answering System for the History of Sumedang Larang: Integrating Retrieval-Augmented Generation, Knowledge Graph, and Ontology

Rahman, F., Baizal, Z. K. A., & Wiharja, K. R. S. (2025) · International Conference on Software Engineering and Information Technology (ICoSEIT) · doi:10.1109/icoseit67010.2025.11290830

WIP: Context-Aware AI in Learning Management Systems for Computer Science Courses

Simmons, A., de Holanda, M. T., & Silva, D. D. (2025) · IEEE Frontiers in Education Conference (FIE) · doi:10.1109/fie63693.2025.11328241

Sim-Stu: A Multi-Agent System for Simulating Learning Processes

Zhang, W., Du, X., Dong, T., Ren, W., Tan, J. Y., & Ma, B. (2025) · IEEE International Conference on Agents (ICA) · doi:10.1109/ica67499.2025.00019

A Customized AI Chatbot for Educational Environments: Integrating Retrieval-Augmented Generation with Curriculum-Aligned Responses

Trang, T., Tran, P., Le, T. M., Le, L., Maheshwari, G., Do, N., & Dao, S. V. T. (2025) · RIVF International Conference on Computing and Communication Technologies (RIVF) · doi:10.1109/rivf68649.2025.11365126

Enhancing Digital Literacy Through Retrieval-Augmented Generation

Cabras, M., Boratto, L., Carta, S., & Marras, M. (2026) · Lecture notes in computer science · doi:10.1007/978-3-032-17604-2_22

Capisa: A Case-Augmented AI System for Personalized U.S. College Admissions Planning

Liao, X. R., Steven, X., Nie, P., & Li, Z. (2025) · International Conference on Educational Technology (ICET) · doi:10.1109/icet67421.2025.11380422

An Intelligent Question Paper Generator System Using Blockchain Technology

Raj, G. V., Lokeswari, G., Likitha, B., Veni, A. N., & Kumar, P. S. (2026) · International Research Journal on Advanced Engineering Hub (IRJAEH) · doi:10.47392/irjaeh.2026.0086

Automatic item generation for reading comprehension in Portuguese literature

da Cunha, F. L., Mota, E., & Araújo, S. (2025) · International Conference on Foundation and Large Language Models (FLLM) · doi:10.1109/fllm67465.2025.11390998

Cipherbot: An AI-Powered Educational Assistant for Conversational Q&A About Course Material

Azem, J. Y., Jung, S., Medina, J., Aldous, K. K., Salminen, J. O., & Jansen, B. J. (2025) · International Conference on Foundation and Large Language Models (FLLM) · doi:10.1109/fllm67465.2025.11390928

LEAP: Learning Enhanced by AI Personalization for Customized Student Support

Zhang, S., Hussain, S., & Zoha, A. (2025) · International Conference on AI-Driven STEM Education and Learning Technologies (AISTEMEDU) · doi:10.1109/aistemedu67077.2025.11403909

AutoEER: Large Language Model Agent Framework for Automated English Exam Report

Xie, D., Li, X., Xiong, Q., Wang, S., Jiang, Y., Liang, Y., & Jin, A. (2025) · International Academic Exchange Conference on Science and Technology Innovation (IAECST) · doi:10.1109/iaecst68792.2025.11415007

Centinela Meets Agents: Agentic RAG for Academic Information in Ecuador

Aguirre, M., Ayala-Tipan, C., Chuncho, A., Recalde, L., Suntaxi, G., Martínez-Mosquera, D., & Andrade-Cabrera, A. (2025) · Latin American Computer Conference (CLEI) · doi:10.1109/clei67442.2025.11420412

Development of a Virtual Mentor Integrated with Retrieval-Augmented Generation Artificial Intelligence for Project-Based Learning

Baskara, D. S., Muttaqin, N., & Purwodani, D. L. (2026) · SMATIKA JURNAL · doi:10.32664/smatika.v16i01.2258

A Multimodal RAG and ArXiv-Integrated Conversational Framework for Automated Research Discovery

Dalvi, A., Sawant, S., Syed, A., Siddavatam, I. N. A., & Venkataramanan, V. (2026) · International Research Journal of Multidisciplinary Technovation · doi:10.54392/irjmt2626

Design and Implementation of a RAG Chatbot System for Scientific Research Institutes

Radulovic, I., Mitric, J., Kovijanić, K., Ljuka, M., Merdović, N., Hiyari, M. H., & Badnjević, A. (2026) · doi:10.1109/it67293.2026.11435604

Teaching the Machine, and Trusting the Machine: Unpacking the Pitfalls of LLMs in Education

Patias, I. (2025) · International Conference on Artificial Intelligence and Teacher Education (ICAITE) · doi:10.1109/icaite68636.2025.11442521

Knowledge Grounded Conversational Access to Heterogeneous Institutional Documents via OCR Enabled Hybrid RAGPreprint

Reddy, V., Kaki, K., Kesineni, B., Annapureddy, I., Kanna, H., & Chalamala, G. (2026) · Research Square · doi:10.21203/rs.3.rs-9287246/v1

Smart College Helpdesk Assistant Using Machine Learning & NLP

Muthukumar, D. S., Vendhan, D., Achari, P. H., Sakam, M., Reddy, P. M. M., & Kumar, P. Y. (2026) · International Conference on Intelligent Sustainable Systems (ICISS) · doi:10.1109/iciss67859.2026.11453598

Leveraging Graph RAG Model for Academic Transcript Analysis: A Comprehensive Study

Ali, U. S. (2026) · Journal of Physics Conference Series · doi:10.1088/1742-6596/3191/1/012091

µCap: Instrumental Music Captions for Deaf and Hard-of-Hearing Individuals

Ahn, S., Baek, I.-C., Kim, K., Truong, K. N., & Hong, J.-H. (2026) · CHI Conference on Human Factors in Computing Systems · doi:10.1145/3772318.3790729

Semantic Search-Enhanced Policy Review Models Using Azure Cognitive Services and Power Apps

Koduri, N. K., Piridi, S., Asundi, S., & Kamineni, S. (2025) · International Conference on Data Science and Geoinformatics (ICDSG) · doi:10.1109/icdsg67714.2025.11381317

TSQA: Integrating Text Summarization and Question Answering to Improve Information Retrieval from Documents Using Retrieval-Augmented Generation

Jaddoa, A. S., Karimpour, J., & Salehpour, P. (2026) · Information · doi:10.3390/info17040372

GRAIL-RAG: A Multi-Layer Guardrails Architecture with Session-Aware Memory and Multi-Stage Retrieval for Document-Grounded QA

Divya, A., Lakshmi, D. S., Anusha, Y., Afzal, S. M., Sumanth, V., & Srija, D. V. (2026) · International Conference on Visual Analytics and Data Visualization (ICVADV) · doi:10.1109/icvadv67766.2026.11470472

Designing metaverse interaction systems for the Turkish language enhanced by fine-tuning and retrieval-augmented generation (RAG)

Özkal, İ., & Başçi̇ftçi̇, F. (2026) · Scientific Reports · doi:10.1038/s41598-026-35392-x

Architectural Frameworks and Strategic Selection of AI-Driven Administrative Chatbots in Educational Environments

Nikiforova-Ilieva, K., & Georgiev, T. S. (2026) · International Symposium INFOTEH-JAHORINA (INFOTEH) · doi:10.1109/infoteh68759.2026.11477638

The Semantic Design Space of Retrieval-Augmented Recommender Systems: A Systematic Review of LLM-Based Approaches

Choi, M., Ahsan, I., Yu, H., Choe, T., & Kim, M. (2026) · Computers, materials & continua/Computers, materials & continua (Print) · doi:10.32604/cmc.2026.079504

AI-Powered Student Learning Assistant

Kalal, A., Patil, A., Patil, P., Bandewar, V., Kumar, S., & Patil, V. (2026) · International Conference on Emerging Technologies and Future Innovations (ETFI) · doi:10.1109/etfi68128.2026.11484083

Lead HeatScore: An AI-Driven Lead Classification and Outreach Recommendation System

Victoria, D. R. S., Roshika, P., Padmavarshini, B., Kumar, S., & Gunasekar, K. (2026) · International Conference on Electronic Systems and Intelligent Computing (ICESIC) · doi:10.1109/icesic67389.2026.11496464

When to Hash and When to Learn: A Systematic Performance Analysis of Deterministic Indexing versus Neural Inference for Text Retrieval

Kumar, B., Verma, Y., & Dhasarathan, C. (2026) · IEEE International Conference on AI Engineering and Innovations (AIEI) · doi:10.1109/aiei69164.2026.11497442

An Evidence-Grounded Multi-Stage Retrieval-Augmented Framework for Multimodal Medical Question Answering

Sharma, K., Srivastava, S., -, S. S., & Singhal, A. (2026) · IEEE International Conference on AI Engineering and Innovations (AIEI) · doi:10.1109/aiei69164.2026.11497629

Towards Developing a Multimodal Chat Assistant for University Stakeholders: RAG-Based Approach

Shaikh, M. A. H., & Shafi, A. A. (2025) · International Conference on Computer and Information Technology (ICCIT) · doi:10.1109/iccit68739.2025.11490128

Source Code Error Categorization and Explanation by Retrieval Augmented Generation

Amin, M. F. I., Watanobe, Y., Rahman, M. M., Mia, M. S., & Muepu, D. M. (2026) · International Conference on Advances in Artificial Intelligence and Machine Learning (AAIML) · doi:10.1109/aaiml67890.2026.11498214

VoiceEdu: A Retrieval-Augmented Voice Tutoring System for Course Instruction with Retrieval Strategy Evaluation

Gu, J., You, F., Pang, X., Tang, Y., Shao, S., & Jiang, J. (2026) · International Conference on AI in Education Technology and Applications (AIETA) · doi:10.1109/aieta69357.2026.11508671

Design and Evaluation of a Competency-Grounded RAG Pipeline for Role-Based Software Engineering Education

Septama, H. D., Ferdiana, R., & Permanasari, A. E. (2026) · International Conference on Current Research in Artificial Intelligence and Data Science (ICCRAIDS) · doi:10.1109/iccraids67816.2026.11519677

Development of Automated Essay Scoring Using Retrieval Augmented Generation in SAGE

Wiguna, I. G. N. S., Pascima, I. B. N., & Damayanthi, L. P. E. (2026) · RIGGS Journal of Artificial Intelligence and Digital Business · doi:10.31004/riggs.v5i2.8979

Mitigating LLM Limitations in Learning Environments through Retrieval-Based Knowledge Integration*

Bezerra, R., Gala, A. D. C. O. S., Marcondes, F. S., Durães, D. A., & Nováis, P. (2026) · IEEE Conference on Artificial Intelligence (CAI) · doi:10.1109/cai68641.2026.11536367

Retrieval-Augmented AI Feedback to Support Metacognition and Accessible Feedback in STEM Education

Bhati, D., Le, T., Guercio, A., Auman, C., & Bandaru, D. S. (2026) · IEEE Conference on Artificial Intelligence (CAI) · doi:10.1109/cai68641.2026.11536256

EduAI Helper: A Retrieval-Augmented LLM–Knowledge Graph Framework for Teacher-Centered Pedagogical Support

Douidi, L., Megouache, L., Djoudi, M., & Zitouni, A. (2026) · Ingénierie des systèmes d information · doi:10.18280/isi.310410

C-RAG: Case-Evidence Grounded Generation for Teacher-Facing Instructional Design in International Chinese Education

Zang, Z. (2026) · International Conference on Big Data and Informatization Education (ICBDIE) · doi:10.1145/3806980.3807002

A mesterséges intelligencia szerepe az étrend-kiegészítők fejlesztésében

Háber, A. Z., Figler, M., & Szabó, Z. R. (2026) · Magyar Tudomány · doi:10.1556/2065.187.2026.6.9

Quantum dot-functionalized nanocomposite scaffolds with retrieval-augmented generation for explainable AI-guided regenerative medicine

Lalitha, R. V. S., Krishnan, S. B., Kshirsagar, P. R., Polamurı, S. R., & Sree, S. R. (2026) · Journal of Materials Science · doi:10.1007/s10853-026-13081-4

Semantic–Sequential Educational Recommendation with Collaborative Enhancement and Parameter-Efficient Language Model Adaptation

Majjate, H., Bellarhmouch, Y., Jeghal, A., Yahyaouy, A., Laaouina, L., Tairi, H., & Zidani, K. A. (2026) · Technologies · doi:10.3390/technologies14060342

Generative Artificial Intelligence and Chatbots: Profiles and Uses in Chilean Distance Education

González, E. A., Machado, R. P., Alario‐Hoyos, C., & Hormazábal, P. Á. (2026) · IEEE World Engineering Education Conference (EDUNINE) · doi:10.1109/edunine62390.2026.11546855

From Tool Literacy to Workflow Fluency: Designing AI-agent Exemplary Cases for the Professional Development of Early-career University Faculty

Zhang, P., & Zhu, J. (2026) · Global Education Bulletin · doi:10.71052/grb2025/bxjn3424

The Semantic Layer as Contextual Foundation of Retrieval-Augmented Automated Assessment

Vangelova, A., & Aleksieva-Petrova, A. (2026) · Information · doi:10.3390/info17060604

Research Query Nest: A Rag-Enhanced Insightbot for Research and Development Queries

Padma, T., Sreedharan, C., & Pradhap, R. H. (2026) · International Conference on Inventive Research in Computing Applications (ICIRCA) · doi:10.1109/icirca69024.2026.11570341

Energy-Aware Edge–Cloud Collaboration for Learning Varieties of English: Cache-Assisted Inference and Evidence-Grounded Feedback

You, C., 张世伟, Qi, L., Wei, M., Wang, X. Y., & Lu, H. (2026) · AI Engineering · doi:10.53941/aieng.2026.100006

LearnForge: An AI-Powered Intelligent Learning Assistant with RAG-Based Document Intelligence

Nitishkumar, R. J., & Ranjini, R. (2026) · International Conference on Intelligent Systems and Computational Networks (ICISCN) · doi:10.1109/iciscn67954.2026.11566245

CLARA: An AI-Augmented Analytics Dashboard for Collaboration Literacy

Xie, D., Anderson, K., Eze, T. D., Lin, C., Shin, B., & Worsley, M. B. (2026) · Lecture notes in computer science · doi:10.1007/978-3-032-29755-6_23

MisEdu-RAG: A Misconception-Aware Dual-Hypergraph RAG for Novice Math Teachers

Guo, Z., Xue, R., Lu, Y., & Lin, J. (2026) · Lecture notes in computer science · doi:10.1007/978-3-032-29755-6_10

From Large Language Models to Retrieval-Augmented Generation: A Systematic Review of AI-Powered Educational Systems From Large Language Models to Retrieval-Augmented Generation: A Systematic Review of AI-Powered Educational Systems

(2026) · International Journal of Research in Advent Technology · doi:10.32622/ijrat.1401202613

A Survey on Retrieval-Augmented Generation in Applications of Education and Teaching

Pan, F., Zhou, Q., Guo, W., & Yang, H. (2025) · International Conference on Computer Science and Technologies in Education (CSTE) · doi:10.1109/cste64638.2025.11092120 · Cited by 11 · see citing works

A Systematic Literature Review of Retrieval-Augmented Generation Implementation for Enhancing Large Language Models in Education

Arthana, I. K. R., Gunantara, N., Sudarma, M., & Sukarsa, M. (2026) · Jurnal Nasional Pendidikan Teknik Informatika (JANAPATI) · doi:10.23887/janapati.v15i1.112281 · Cited by 3 · see citing works

Mitigating LLM Limitations in Learning Environments through Retrieval-Based Knowledge Integration*

Bezerra, R., Gala, A. D. C. O. S., Marcondes, F. S., Durães, D. A., & Nováis, P. (2026) · IEEE Conference on Artificial Intelligence (CAI) · doi:10.1109/cai68641.2026.11536367

RAG augmented Large Language Models as a tool for Education

Teixeira, S., Sonkaya, M., & Georgieva, P. (2025) · International Conference Automatics and Informatics (ICAI) · doi:10.1109/icai67591.2025.11324994 · Cited by 1 · see citing works