Λεπτομέρειες βιβλιογραφικής εγγραφής
| Τίτλος: |
COLLABORATIVE MULTI-AGENT CHATBOT FRAMEWORK FOR INTELLIGENT TUTORING AND FEEDBACK. |
| Συγγραφείς: |
Zhibek, Myrzaliyeva1, Cankurt, Selcuk1 |
| Πηγή: |
German International Journal of Modern Science / Deutsche Internationale Zeitschrift für Zeitgenössische Wissenschaft. Apr2026, Issue 126, p141-146. 6p. |
| Θεματικοί όροι: |
*Modular design, Multiagent systems, Java programming language, Intelligent tutoring systems, Educational counseling, Computer software testing |
| Περίληψη: |
However, traditional single-agent chatbots are susceptible to technological hallucination, non-consistent pedagogical depth, and lack of a verification system, as they usually offer ready-made answers without promoting conceptual thinking. This paper suggests a Collaborative Multi-Agent Chatbot Framework that will facilitate intelligent tutoring and feedback of high quality for Java programming. In particular, we propose to use a modular design with specialized agents, such as a generative tutor agent and a verification agent who is tasked with verifying the generated answers. The verifier uses real-time execution of JUnit 5 tests to validate hints generated by other agents. As far as we know, this is one of the first attempts to use test-based verification in the process of LLM tutoring. The proposed system was tested using 15 selected Java programming problems that covered basic algorithms and object-oriented programming principles. The experimental findings indicate that the new method is considerably superior to the single-agent models, with 90% success rate. Although the multi-agent architecture may result in longer response times, it requires fewer interaction iterations, thus providing a more productive and educational experience. [ABSTRACT FROM AUTHOR] |
|
Copyright of German International Journal of Modern Science / Deutsche Internationale Zeitschrift für Zeitgenössische Wissenschaft is the property of Artmedia24 and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.) |
| Βάση Δεδομένων: |
Business Source Index |