Application and optimization of digital situated teaching in university finance courses from a constructivist perspective: An analysis based on machine learning algorithms.
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| Title: | Application and optimization of digital situated teaching in university finance courses from a constructivist perspective: An analysis based on machine learning algorithms. |
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| Authors: | Liu, Zebin1 (AUTHOR), Zhang, Xiaoheng2 (AUTHOR) zhang.xiaoheng@foxmail.com, Liu, Wende1 (AUTHOR), Chen, Wanxue1 (AUTHOR), Li, Yongjun1 (AUTHOR), Zhou, Yi1 (AUTHOR) |
| Source: | Education & Information Technologies. Aug2025, Vol. 30 Issue 13, p18059-18088. 30p. |
| Subject Terms: | *Finance education, *Constructivism (Education), *Experiential learning, *Educational change, *Machine learning, *Situated learning theory, *Higher education, *Student engagement |
| Abstract: | The rapid advancement of digital technologies is prompting a necessary shift in traditional educational models, particularly in finance education. This study introduces the "Multi-Dimensional Situated Learning Model" (MD-SLM), which is rooted in constructivist theory and aims to enhance teaching strategies in university finance courses. The MD-SLM incorporates digital tools like simulation software and online learning platforms to create a dynamic and authentic learning environment that fosters active student engagement and the development of practical skills. The model is designed with a tiered structure of situational tasks—categorized as foundational, extended, and integrative—paired with a comprehensive teacher support system that helps educators transition from traditional teaching roles to facilitators of learning. To assess the model's effectiveness, machine learning algorithms, such as cluster analysis, decision tree analysis, and Gradient Boosting Machine (GBM), were used on a dataset of 514 students over three years. The results demonstrated significant improvements in student learning behaviors and outcomes. The study's findings highlight the MD-SLM's potential to revolutionize digital finance education by aligning with constructivist principles and providing customized learning experiences. The research concludes with recommendations for applying this model more broadly across various educational contexts, aiming to contribute to the ongoing digital transformation in higher education. [ABSTRACT FROM AUTHOR] |
| Copyright of Education & Information Technologies is the property of Springer Nature 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 | Text: Availability: 0 |
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| Header | DbId: ehh DbLabel: Education Research Complete An: 187434383 AccessLevel: 6 PubType: Academic Journal PubTypeId: academicJournal PreciseRelevancyScore: 0 |
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| Items | – Name: Title Label: Title Group: Ti Data: Application and optimization of digital situated teaching in university finance courses from a constructivist perspective: An analysis based on machine learning algorithms. – Name: Author Label: Authors Group: Au Data: <searchLink fieldCode="AR" term="%22Liu%2C+Zebin%22">Liu, Zebin</searchLink><relatesTo>1</relatesTo> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Zhang%2C+Xiaoheng%22">Zhang, Xiaoheng</searchLink><relatesTo>2</relatesTo> (AUTHOR)<i> zhang.xiaoheng@foxmail.com</i><br /><searchLink fieldCode="AR" term="%22Liu%2C+Wende%22">Liu, Wende</searchLink><relatesTo>1</relatesTo> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Chen%2C+Wanxue%22">Chen, Wanxue</searchLink><relatesTo>1</relatesTo> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Li%2C+Yongjun%22">Li, Yongjun</searchLink><relatesTo>1</relatesTo> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Zhou%2C+Yi%22">Zhou, Yi</searchLink><relatesTo>1</relatesTo> (AUTHOR) – Name: TitleSource Label: Source Group: Src Data: <searchLink fieldCode="JN" term="%22Education+%26+Information+Technologies%22">Education & Information Technologies</searchLink>. Aug2025, Vol. 30 Issue 13, p18059-18088. 30p. – Name: Subject Label: Subject Terms Group: Su Data: *<searchLink fieldCode="DE" term="%22Finance+education%22">Finance education</searchLink><br />*<searchLink fieldCode="DE" term="%22Constructivism+%28Education%29%22">Constructivism (Education)</searchLink><br />*<searchLink fieldCode="DE" term="%22Experiential+learning%22">Experiential learning</searchLink><br />*<searchLink fieldCode="DE" term="%22Educational+change%22">Educational change</searchLink><br />*<searchLink fieldCode="DE" term="%22Machine+learning%22">Machine learning</searchLink><br />*<searchLink fieldCode="DE" term="%22Situated+learning+theory%22">Situated learning theory</searchLink><br />*<searchLink fieldCode="DE" term="%22Higher+education%22">Higher education</searchLink><br />*<searchLink fieldCode="DE" term="%22Student+engagement%22">Student engagement</searchLink> – Name: Abstract Label: Abstract Group: Ab Data: The rapid advancement of digital technologies is prompting a necessary shift in traditional educational models, particularly in finance education. This study introduces the "Multi-Dimensional Situated Learning Model" (MD-SLM), which is rooted in constructivist theory and aims to enhance teaching strategies in university finance courses. The MD-SLM incorporates digital tools like simulation software and online learning platforms to create a dynamic and authentic learning environment that fosters active student engagement and the development of practical skills. The model is designed with a tiered structure of situational tasks—categorized as foundational, extended, and integrative—paired with a comprehensive teacher support system that helps educators transition from traditional teaching roles to facilitators of learning. To assess the model's effectiveness, machine learning algorithms, such as cluster analysis, decision tree analysis, and Gradient Boosting Machine (GBM), were used on a dataset of 514 students over three years. The results demonstrated significant improvements in student learning behaviors and outcomes. The study's findings highlight the MD-SLM's potential to revolutionize digital finance education by aligning with constructivist principles and providing customized learning experiences. The research concludes with recommendations for applying this model more broadly across various educational contexts, aiming to contribute to the ongoing digital transformation in higher education. [ABSTRACT FROM AUTHOR] – Name: AbstractSuppliedCopyright Label: Group: Ab Data: <i>Copyright of Education & Information Technologies is the property of Springer Nature 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: 10.1007/s10639-025-13496-7 Languages: – Code: eng Text: English PhysicalDescription: Pagination: PageCount: 30 StartPage: 18059 Subjects: – SubjectFull: Finance education Type: general – SubjectFull: Constructivism (Education) Type: general – SubjectFull: Experiential learning Type: general – SubjectFull: Educational change Type: general – SubjectFull: Machine learning Type: general – SubjectFull: Situated learning theory Type: general – SubjectFull: Higher education Type: general – SubjectFull: Student engagement Type: general Titles: – TitleFull: Application and optimization of digital situated teaching in university finance courses from a constructivist perspective: An analysis based on machine learning algorithms. Type: main BibRelationships: HasContributorRelationships: – PersonEntity: Name: NameFull: Liu, Zebin – PersonEntity: Name: NameFull: Zhang, Xiaoheng – PersonEntity: Name: NameFull: Liu, Wende – PersonEntity: Name: NameFull: Chen, Wanxue – PersonEntity: Name: NameFull: Li, Yongjun – PersonEntity: Name: NameFull: Zhou, Yi IsPartOfRelationships: – BibEntity: Dates: – D: 20 M: 08 Text: Aug2025 Type: published Y: 2025 Identifiers: – Type: issn-print Value: 13602357 Numbering: – Type: volume Value: 30 – Type: issue Value: 13 Titles: – TitleFull: Education & Information Technologies Type: main |
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