# Retrieval-Augmented Generation (RAG) Chatbots for Education: A Survey of Applications
## 2 Materials and Methods  
The search for the relevant publications has been performed using three bibliographic data access platforms: Scopus, Web of Science, and Google Scholar. The first two platforms feature a reliable search procedure based on multiple user-defined criteria that can be combined in various ways and a large database of quality publication venues. Their inclusion is motivated by the assumption that, if there is a high-quality work on the chosen topic, it can highly probably be found by an exact search in either of these two sources. The third (Google Scholar) uses a black-box search procedure based on relevancy (so an exact match with the search phrase is not necessary to qualify a paper for the results) and includes various web sources, regardless of their quality. Its inclusion is motivated by the novelty of the covered topic (in the context of the long publication times of many publication venues) and strives to identify relevant works that were not captured by the query on the first two platforms because of, e.g., not being indexed (e.g., preprints, Master's theses, or local journals and conference proceedings) or not matching the search criteria (e.g., unusual wording used by their authors or their keywords being defined using completely different schemes).  
In all three analyzed sources, we considered only publications written in English for two practical reasons: English is currently the lingua franca of scientific writing in which most papers are published and our command of other languages is not sufficient to reliably survey all non-English papers.  
The Scopus search term has been defined to target all original publications in English from 2022 onward that featured the terms _education_*, _chatbot_, and _Retrieval-Augmented Generation_ or _RAG_ in their titles, abstracts, or keywords specified by their respective authors:  
TITLE-ABS-KEY ( \"education*\" ) AND TITLE-ABS-KEY ( \"chatbot\" ) AND ( TITLE-ABS-KEY ( \"RAG\" ) OR TITLE-ABS-KEY ( \"Retrieval Augmented Generation\" ) ) AND ( LIMIT-TO ( DOCTYPE, \"ar\" ) OR LIMIT-TO ( DOCTYPE, \"cp\" ) ) AND PUBYEAR > 2021 AND ( LIMIT-TO ( LANGUAGE, \"English\" ) )  
A similar approach was used to define the search term for Web of Science:  
((((TI=(education*)) OR AK=(education*))) OR (AB=(education*))) AND ((((TI=(chatbot) OR AK=(chatbot))) OR (AB=(chatbot)))) AND ((((TI=(\"Retrieval Augmented Generation\")) OR AK=(\"Retrieval Augmented Generation\"))) OR (AB=(\"Retrieval Augmented Generation\"))) OR ((((TI=(RAG) OR (AK=(RAG)))) OR (AB=RAG)))) AND (PY2021)  
As for querying Google Scholar, the Publish or Perish software version 8.17 has been used with the following search terms: _education_ and _rag chatbot_, excluding citations and patents.  
Both bibliographic data providers were queried on 17 February 2025. Figure 1 shows the flow of the data collection and qualification process. The Scopus query yielded 24 results and Web of Science provided only 8 results, whereas 83 results were obtained from Google Scholar. While seven out of eight Web of Science results were also present in Scopus, only four works found in Scholar were duplicated in the results from Scopus, which indicates the mutual complementarity of Google Scholar with the classic bibliographic data sources, confirming the rationale for including the former data source in the query. After screening the titles and abstracts, only 1 of the 24 works found in Scopus but as many as 59 of the 83 works found in Scholar were assessed as unrelated to the area of education. Furthermore, nine works found in Scholar and one in Web of Science were excluded for being written in a language other than English.  
A snowballing procedure was then performed on the resulting set of 34 identified papers, whose references provided 13 additional relevant papers, resulting in a total of 47 research papers that were qualified for further analysis.  
Figure 1: Data collection and qualification.