The role of students' higher-order thinking skills in the relationship between academic achievements and machine learning using generative AI chatbots.
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| Title: | The role of students' higher-order thinking skills in the relationship between academic achievements and machine learning using generative AI chatbots. |
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| Authors: | Pellas, Nikolaos1 nikolaospellas@gmail.com |
| Source: | Research & Practice in Technology Enhanced Learning. 2025, Vol. 20, p1-28. 28p. |
| Subject Terms: | *Generative artificial intelligence, *Machine learning, *Student attitudes, *Artificial intelligence, Language models, Chatbots |
| Abstract: | Students' perspectives on using generative artificial intelligence (AI) chatbots and machine learning are crucial in shaping the design, development, and implementation of their learning projects across various disciplines. Cognitive thinking, a key aspect of AI-related machine learning, aims to replicate human intelligence and behavior. However, the relation between cognitive thinking and knowledge acquisition is often overlooked. This cross-sectional study empirically examines the relationship between academic achievement and students' attitudes toward machine learning, particularly through the use of generative AI chatbots. It specifically focuses on the role of higher-order thinking skills--such as problemsolving, critical thinking, and creativity--as both mediators and moderators in this relationship. A total of four hundred sixteen undergraduate students (n=416) from diverse academic backgrounds voluntarily took part in a project, in which they designed and developed generative AI chatbots in media and information literacy courses. The findings indicate that creativity mediated the relationship between academic achievements and attitudes toward machine learning, but its moderating impact was not significant. Problem-solving and critical thinking did not show significant mediating effects on attitudes toward machine learning, while they showed significant moderating effects in the connection between academic performance and attitudes toward machine learning. This study contributes by elucidating the interrelationships between students' higher-order thinking skills, academic performance, and attitudes on the use of AI and machine learning technologies. By highlighting the mediating role of creativity and the moderating effects of problem-solving and critical thinking, this study offers a deeper understanding of how these skills shape students' perceptions of AI. [ABSTRACT FROM AUTHOR] |
| Copyright of Research & Practice in Technology Enhanced Learning is the property of Asia-Pacific Society for Computers in Education (APSCE) 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.) | |
| Database: | Education Research Complete |
| FullText | Links: – Type: pdflink Text: Availability: 0 |
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| Header | DbId: ehh DbLabel: Education Research Complete An: 184656799 AccessLevel: 6 PubType: Academic Journal PubTypeId: academicJournal PreciseRelevancyScore: 0 |
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| Items | – Name: Title Label: Title Group: Ti Data: The role of students' higher-order thinking skills in the relationship between academic achievements and machine learning using generative AI chatbots. – Name: Author Label: Authors Group: Au Data: <searchLink fieldCode="AR" term="%22Pellas%2C+Nikolaos%22">Pellas, Nikolaos</searchLink><relatesTo>1</relatesTo><i> nikolaospellas@gmail.com</i> – Name: TitleSource Label: Source Group: Src Data: <searchLink fieldCode="JN" term="%22Research+%26+Practice+in+Technology+Enhanced+Learning%22">Research & Practice in Technology Enhanced Learning</searchLink>. 2025, Vol. 20, p1-28. 28p. – Name: Subject Label: Subject Terms Group: Su Data: *<searchLink fieldCode="DE" term="%22Generative+artificial+intelligence%22">Generative artificial intelligence</searchLink><br />*<searchLink fieldCode="DE" term="%22Machine+learning%22">Machine learning</searchLink><br />*<searchLink fieldCode="DE" term="%22Student+attitudes%22">Student attitudes</searchLink><br />*<searchLink fieldCode="DE" term="%22Artificial+intelligence%22">Artificial intelligence</searchLink><br /><searchLink fieldCode="DE" term="%22Language+models%22">Language models</searchLink><br /><searchLink fieldCode="DE" term="%22Chatbots%22">Chatbots</searchLink> – Name: Abstract Label: Abstract Group: Ab Data: Students' perspectives on using generative artificial intelligence (AI) chatbots and machine learning are crucial in shaping the design, development, and implementation of their learning projects across various disciplines. Cognitive thinking, a key aspect of AI-related machine learning, aims to replicate human intelligence and behavior. However, the relation between cognitive thinking and knowledge acquisition is often overlooked. This cross-sectional study empirically examines the relationship between academic achievement and students' attitudes toward machine learning, particularly through the use of generative AI chatbots. It specifically focuses on the role of higher-order thinking skills--such as problemsolving, critical thinking, and creativity--as both mediators and moderators in this relationship. A total of four hundred sixteen undergraduate students (n=416) from diverse academic backgrounds voluntarily took part in a project, in which they designed and developed generative AI chatbots in media and information literacy courses. The findings indicate that creativity mediated the relationship between academic achievements and attitudes toward machine learning, but its moderating impact was not significant. Problem-solving and critical thinking did not show significant mediating effects on attitudes toward machine learning, while they showed significant moderating effects in the connection between academic performance and attitudes toward machine learning. This study contributes by elucidating the interrelationships between students' higher-order thinking skills, academic performance, and attitudes on the use of AI and machine learning technologies. By highlighting the mediating role of creativity and the moderating effects of problem-solving and critical thinking, this study offers a deeper understanding of how these skills shape students' perceptions of AI. [ABSTRACT FROM AUTHOR] – Name: AbstractSuppliedCopyright Label: Group: Ab Data: <i>Copyright of Research & Practice in Technology Enhanced Learning is the property of Asia-Pacific Society for Computers in Education (APSCE) 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.</i> (Copyright applies to all Abstracts.) |
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| RecordInfo | BibRecord: BibEntity: Identifiers: – Type: doi Value: 10.58459/rptel.2025.20036 Languages: – Code: eng Text: English PhysicalDescription: Pagination: PageCount: 28 StartPage: 1 Subjects: – SubjectFull: Generative artificial intelligence Type: general – SubjectFull: Machine learning Type: general – SubjectFull: Student attitudes Type: general – SubjectFull: Artificial intelligence Type: general – SubjectFull: Language models Type: general – SubjectFull: Chatbots Type: general Titles: – TitleFull: The role of students' higher-order thinking skills in the relationship between academic achievements and machine learning using generative AI chatbots. Type: main BibRelationships: HasContributorRelationships: – PersonEntity: Name: NameFull: Pellas, Nikolaos IsPartOfRelationships: – BibEntity: Dates: – D: 01 M: 01 Text: 2025 Type: published Y: 2025 Identifiers: – Type: issn-print Value: 17932068 Numbering: – Type: volume Value: 20 Titles: – TitleFull: Research & Practice in Technology Enhanced Learning Type: main |
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