AIGC-Assisted Evaluation of Teachers' Tour-Guide Scripts: Construction and Practice of the Six-Step Method
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| Title: | AIGC-Assisted Evaluation of Teachers' Tour-Guide Scripts: Construction and Practice of the Six-Step Method |
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| Language: | English |
| Authors: | Lingman Zhou (ORCID |
| Source: | Asian Journal of Education and Training. 2025 11(4):224-232. |
| Availability: | Asian Online Journal Publishing Group. 244 Fifth Avenue Suite D42, New York, NY 10001. Fax: 212-591-6094; e-mail: info@asianonlinejournals.com; Web site: http://www.asianonlinejournals.com |
| Peer Reviewed: | Y |
| Page Count: | 9 |
| Publication Date: | 2025 |
| Document Type: | Journal Articles Reports - Research |
| Education Level: | Secondary Education |
| Descriptors: | Artificial Intelligence, Scripts, Pedagogical Content Knowledge, Technological Literacy, Writing Evaluation, Career and Technical Education, Secondary School Students, Tourism, Computer Uses in Education, Foreign Countries, Career and Technical Education Teachers, Secondary School Teachers, Teacher Attitudes, Interrater Reliability |
| Geographic Terms: | China |
| ISSN: | 2519-5387 |
| Abstract: | Artificial Intelligence Generated Content (AIGC) has garnered significant attention in education due to itsstrengthsin language processing and content creation. It offers a novel technical approach to enhance tools for evaluating tour-guide scripts, which are inherently contextual, audienceoriented, and focused on cultural expression. This paper proposes a six-step method for AIGC-assisted evaluation of teachers' tour-guide scripts within the framework of Technological Pedagogical Content Knowledge (TPACK). The approach leverages the integration of technological knowledge, pedagogical knowledge, and content knowledge to establish a clear human-AI workflow. The six steps include Standard Setting, Standardized Input, AIGC Check, Guided Modification, Comparative Analysis, and Summary and Sharing. The study utilizes vocational students as the research group and employs a combination of teacher-AIGC comparison and mixed methods for evaluation. The focus is on the quantity and types of comments, the focus dimensions, and students' performance in second-round writing. Results indicate that AIGC is effective in ensuring language accuracy and structural completeness. Teachers demonstrate stronger professional judgment in areas related to context and cultural expression. Their collaboration within the six-step process significantly enhances evaluation efficiency. This method provides a clear, repeatable process model and offers practical support for integrating AIGC into tour-guide script teaching. |
| Abstractor: | As Provided |
| Entry Date: | 2026 |
| Accession Number: | EJ1494643 |
| Database: | ERIC |
| Abstract: | Artificial Intelligence Generated Content (AIGC) has garnered significant attention in education due to itsstrengthsin language processing and content creation. It offers a novel technical approach to enhance tools for evaluating tour-guide scripts, which are inherently contextual, audienceoriented, and focused on cultural expression. This paper proposes a six-step method for AIGC-assisted evaluation of teachers' tour-guide scripts within the framework of Technological Pedagogical Content Knowledge (TPACK). The approach leverages the integration of technological knowledge, pedagogical knowledge, and content knowledge to establish a clear human-AI workflow. The six steps include Standard Setting, Standardized Input, AIGC Check, Guided Modification, Comparative Analysis, and Summary and Sharing. The study utilizes vocational students as the research group and employs a combination of teacher-AIGC comparison and mixed methods for evaluation. The focus is on the quantity and types of comments, the focus dimensions, and students' performance in second-round writing. Results indicate that AIGC is effective in ensuring language accuracy and structural completeness. Teachers demonstrate stronger professional judgment in areas related to context and cultural expression. Their collaboration within the six-step process significantly enhances evaluation efficiency. This method provides a clear, repeatable process model and offers practical support for integrating AIGC into tour-guide script teaching. |
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| ISSN: | 2519-5387 |
