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Hybrid Intelligence Feedback: A Model Proposal and Preliminary Study

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Title: Hybrid Intelligence Feedback: A Model Proposal and Preliminary Study
Language: English
Authors: Atakan Coskun (ORCID 0000-0002-0459-9677), Erkan Er (ORCID 0000-0002-9624-4055)
Source: Journal of Computer Assisted Learning. 2026 42(2).
Availability: Wiley. Available from: John Wiley & Sons, Inc. 111 River Street, Hoboken, NJ 07030. Tel: 800-835-6770; e-mail: cs-journals@wiley.com; Web site: https://www.wiley.com/en-us
Peer Reviewed: Y
Page Count: 18
Publication Date: 2026
Document Type: Journal Articles
Reports - Research
Education Level: Higher Education
Postsecondary Education
Descriptors: Feedback (Response), Models, Higher Education, Programming, Undergraduate Students, Instructional Effectiveness, Synchronous Communication, Technology Uses in Education, Artificial Intelligence
DOI: 10.1002/jcal.70212
ISSN: 0266-4909
1365-2729
Abstract: 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.
Abstractor: As Provided
Entry Date: 2026
Accession Number: EJ1500543
Database: ERIC
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  Data: Hybrid Intelligence Feedback: A Model Proposal and Preliminary Study
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  Data: <searchLink fieldCode="AR" term="%22Atakan+Coskun%22">Atakan Coskun</searchLink> (ORCID <externalLink term="https://orcid.org/0000-0002-0459-9677">0000-0002-0459-9677</externalLink>)<br /><searchLink fieldCode="AR" term="%22Erkan+Er%22">Erkan Er</searchLink> (ORCID <externalLink term="https://orcid.org/0000-0002-9624-4055">0000-0002-9624-4055</externalLink>)
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  Data: Wiley. Available from: John Wiley & Sons, Inc. 111 River Street, Hoboken, NJ 07030. Tel: 800-835-6770; e-mail: cs-journals@wiley.com; Web site: https://www.wiley.com/en-us
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  Data: Journal Articles<br />Reports - Research
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  Data: <searchLink fieldCode="EL" term="%22Higher+Education%22">Higher Education</searchLink><br /><searchLink fieldCode="EL" term="%22Postsecondary+Education%22">Postsecondary Education</searchLink>
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  Data: <searchLink fieldCode="DE" term="%22Feedback+%28Response%29%22">Feedback (Response)</searchLink><br /><searchLink fieldCode="DE" term="%22Models%22">Models</searchLink><br /><searchLink fieldCode="DE" term="%22Higher+Education%22">Higher Education</searchLink><br /><searchLink fieldCode="DE" term="%22Programming%22">Programming</searchLink><br /><searchLink fieldCode="DE" term="%22Undergraduate+Students%22">Undergraduate Students</searchLink><br /><searchLink fieldCode="DE" term="%22Instructional+Effectiveness%22">Instructional Effectiveness</searchLink><br /><searchLink fieldCode="DE" term="%22Synchronous+Communication%22">Synchronous Communication</searchLink><br /><searchLink fieldCode="DE" term="%22Technology+Uses+in+Education%22">Technology Uses in Education</searchLink><br /><searchLink fieldCode="DE" term="%22Artificial+Intelligence%22">Artificial Intelligence</searchLink>
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  Data: 10.1002/jcal.70212
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  Data: 0266-4909<br />1365-2729
– Name: Abstract
  Label: Abstract
  Group: Ab
  Data: 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.
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      – Text: English
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      – SubjectFull: Feedback (Response)
        Type: general
      – SubjectFull: Models
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      – SubjectFull: Higher Education
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      – SubjectFull: Programming
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      – SubjectFull: Instructional Effectiveness
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      – SubjectFull: Technology Uses in Education
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      – SubjectFull: Artificial Intelligence
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      – TitleFull: Hybrid Intelligence Feedback: A Model Proposal and Preliminary Study
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