Conceptual model of technology for developing an educational chatbot to support students’ practical training

The aim of the study is to build a conceptual model of the technology for developing an educational chatbot in a messenger to support the practical training of students. The article considers the organizational aspects associated with the creation of a chatbot as a teacher’s assistant, with an emphasis on the methodological and technological elements of its design. The scientific novelty of the work lies in the description of the technology for developing a tool to support the practical training of students in the format of a chatbot in a messenger. The results of the study include a description of the stages of developing an educational chatbot, the use of the functionality of generative neural networks at all stages of its creation, as well as examples of prompts designed to customize chatbots for the purpose of addressing responses to student requests. The article also presents demonstration examples of dialogical interaction with the bot by students of the Linguistics program, the Methodology of Teaching Russian as a Foreign Language profile, in 2nd, 3rd and 4th years. A conclusion was made about the feasibility of implementing the technology of engaging the teacher’s AI assistant “Digital Consultant Trainee” for information support of students during their educational and industrial practice in a specialized organization.

Authors

Institutions

Publication Details

Journal
Pedagogy Theory & Practice
Published
2025-02-27
DOI
https://doi.org/10.30853/ped20250029
Primary Topic
Foreign Language Teaching Methods
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Conceptual model of technology for developing an educational chatbot to support students’ practical training

Vera S. Fedotova, N. S. Fedotova
Pedagogy Theory & Practice
Foreign Language Teaching Methods
article

Conceptual model of technology for developing an educational chatbot to support students’ practical training

Vera S. Fedotova, N. S. Fedotova
article en

Abstract

The aim of the study is to build a conceptual model of the technology for developing an educational chatbot in a messenger to support the practical training of students. The article considers the organizational aspects associated with the creation of a chatbot as a teacher’s assistant, with an emphasis on the methodological and technological elements of its design. The scientific novelty of the work lies in the description of the technology for developing a tool to support the practical training of students in the format of a chatbot in a messenger. The results of the study include a description of the stages of developing an educational chatbot, the use of the functionality of generative neural networks at all stages of its creation, as well as examples of prompts designed to customize chatbots for the purpose of addressing responses to student requests. The article also presents demonstration examples of dialogical interaction with the bot by students of the Linguistics program, the Methodology of Teaching Russian as a Foreign Language profile, in 2nd, 3rd and 4th years. A conclusion was made about the feasibility of implementing the technology of engaging the teacher’s AI assistant “Digital Consultant Trainee” for information support of students during their educational and industrial practice in a specialized organization.

Pedagogy Theory & PracticeVol. 10(2)
Pushkin Leningrad State University (RU), Herzen University (RU)
Quality Education
Openalex Percentile: Top 96%
Foreign Language Teaching Methods
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.