Construction of an Evaluation System for Participation and Innovation Ability in Agricultural Master's Practical Classroom Based on AI Multidimensional Affective Computing.
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| Title: | Construction of an Evaluation System for Participation and Innovation Ability in Agricultural Master's Practical Classroom Based on AI Multidimensional Affective Computing. |
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| Authors: | HUANG, Wei1, LIU, Zhaoliang1, GAN, Binjun1, ZHAO, Na1, WANG, Daobo1, LAO, Guoren1 |
| Source: | Meteorological & Environmental Research. Jun2026, Vol. 17 Issue 2/3, p86-89. 4p. |
| Subject Terms: | *Affective computing, *Agricultural education, *Active learning, *Multiple criteria decision making, *Deep learning, *Creative ability, *Talent development, *Student engagement |
| Abstract: | The evaluation of agricultural master's practice teaching has long suffered from issues such as a heavy focus on outcomes over processes, single-dimensional criteria, and strong subjectivity, making it difficult to effectively measure students' classroom engagement and innovation capabilities. Addressing the limitations of traditional evaluation models, by introducing AI affective computing technology into the field of agricultural master's practice teaching evaluation, a comprehensive evaluation system based on multi-dimensional affective computing is constructed. In this paper, the evaluation index system is deconstructed from three core dimensions: focus, collaboration, and innovative behavior, establishing a mapping relationship between affective computing technology and evaluation dimensions. Building on this, a multimodal data collection scheme is designed, employing deep learning algorithms to extract key features of engagement and innovative behavior, thereby constructing a comprehensive evaluation model. Finally, implementation pathways for the evaluation system are proposed. It demonstrates that this system can dynamically track and accurately characterize students' practical processes, providing scientific and data-driven support for improving the quality of agricultural master's talent cultivation. [ABSTRACT FROM AUTHOR] |
| Database: | Energy & Power Source |
| FullText | Links: – Type: pdflink Text: Availability: 0 |
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| Header | DbId: enr DbLabel: Energy & Power Source An: 194828789 AccessLevel: 6 PubType: Academic Journal PubTypeId: academicJournal PreciseRelevancyScore: 0 |
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| PLink | https://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=enr&AN=194828789 |
| RecordInfo | BibRecord: BibEntity: Identifiers: – Type: doi Value: 10.19547/j.issn2152-3940.2026.02-03.019 Languages: – Code: eng Text: English PhysicalDescription: Pagination: PageCount: 4 StartPage: 86 Subjects: – SubjectFull: Affective computing Type: general – SubjectFull: Agricultural education Type: general – SubjectFull: Active learning Type: general – SubjectFull: Multiple criteria decision making Type: general – SubjectFull: Deep learning Type: general – SubjectFull: Creative ability Type: general – SubjectFull: Talent development Type: general – SubjectFull: Student engagement Type: general Titles: – TitleFull: Construction of an Evaluation System for Participation and Innovation Ability in Agricultural Master's Practical Classroom Based on AI Multidimensional Affective Computing. Type: main BibRelationships: HasContributorRelationships: – PersonEntity: Name: NameFull: HUANG, Wei – PersonEntity: Name: NameFull: LIU, Zhaoliang – PersonEntity: Name: NameFull: GAN, Binjun – PersonEntity: Name: NameFull: ZHAO, Na – PersonEntity: Name: NameFull: WANG, Daobo – PersonEntity: Name: NameFull: LAO, Guoren IsPartOfRelationships: – BibEntity: Dates: – D: 01 M: 06 Text: Jun2026 Type: published Y: 2026 Identifiers: – Type: issn-print Value: 21523940 Numbering: – Type: volume Value: 17 – Type: issue Value: 2/3 Titles: – TitleFull: Meteorological & Environmental Research Type: main |
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