Hybrid Intelligence Feedback: A Model Proposal and Preliminary Study

Date

2026-04-01

Author

Coskun, Atakan
Er, Erkan

Metadata

Show full item record

This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.

Item Usage Stats

105
views

0
downloads

Cite This

Background: Although existing studies suggest that AI chatbots hold potential as feedback tools in educational settings, there remains a significant gap in the literature regarding pedagogically grounded frameworks or guidelines for their effective implementation. Therefore, there is very little experimental research on how to use an AI chatbot based on a pedagogical approach. Objectives: This study proposed a conceptual framework grounded in a hybrid intelligence feedback model for the use of AI chatbots as pedagogical feedback tools and aimed to examine its applicability and effectiveness within a higher education programming course. Method: An experimental pre-test/post-test study involving 36 undergraduate students was conducted to evaluate the effectiveness of the proposed model and its underlying design principles for integrating AI chatbots as pedagogically grounded feedback tools in educational settings. Results and Conclusions: Theory-grounded AI chatbots based on the proposed hybrid intelligence feedback model and its design principles significantly improved learning more than the general-purpose AI chatbot in programming class. Theory-grounded AI chatbots can be an effective feedback tool in improving students' skills in self-evaluation, critical thinking, and regulating learning strategies. General-purpose AI chatbot feedback may cause “metacognitive laziness,” harming learning performance. Implications: The article indicates the need for further research and validation to ensure effective implementation and address challenges associated with AI's potential inaccuracies.

Subject Keywords

chatbot, feedback, human-computer interface, hybrid intelligence, large language models (LLMs)

URI

https://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=105031491797&origin=inward
https://hdl.handle.net/11511/118982

Collections

Graduate School of Informatics, Article