A Case Study on SAL-Based Teaching and Learning in a Functional Clothing and Materials Course Using Generative AI
With the rapid development of big data and generative artificial intelligence (AI), education in the apparel industry is evolving beyond traditional theoretical instruction. This study explores the application of Smart Action Learning (SAL) and generative AI tools in the “Functional Cloth...
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| Format: | Article |
| Language: | English |
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IEEE
2025-01-01
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| Series: | IEEE Access |
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| Online Access: | https://ieeexplore.ieee.org/document/10967260/ |
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| author | Hyun Ah Kim |
| author_facet | Hyun Ah Kim |
| author_sort | Hyun Ah Kim |
| collection | DOAJ |
| description | With the rapid development of big data and generative artificial intelligence (AI), education in the apparel industry is evolving beyond traditional theoretical instruction. This study explores the application of Smart Action Learning (SAL) and generative AI tools in the “Functional Clothing and Materials” course to enhance student engagement, problem-solving abilities, and practical skill acquisition. SAL, a student-centered learning approach, incorporates blended learning, flipped learning, and problem-based learning (PBL) methodologies to foster self-directed and cooperative learning. The study was conducted over an eight-week period with second-year students in an apparel major, integrating AI-based problem-solving techniques into coursework. The course design included a five-stage instructional framework: instructor-led lectures, problem identification, AI-assisted research, collaborative solution development, and final presentations. The effectiveness of this approach was evaluated through surveys measuring self-directed learning ability, cooperative learning ability, problem-solving ability, and academic achievement. Results indicate that students demonstrated high levels of engagement, improved problem-solving abilities, and increased learning satisfaction through AI-assisted collaborative projects. The findings suggest that incorporating generative AI into fashion education enhances creative thinking, industry readiness, and adaptability to emerging trends. |
| format | Article |
| id | doaj-art-92b9efd417684bf09c73486a4786f2cc |
| institution | DOAJ |
| issn | 2169-3536 |
| language | English |
| publishDate | 2025-01-01 |
| publisher | IEEE |
| record_format | Article |
| series | IEEE Access |
| spelling | doaj-art-92b9efd417684bf09c73486a4786f2cc2025-08-20T03:11:05ZengIEEEIEEE Access2169-35362025-01-0113734307343910.1109/ACCESS.2025.356183810967260A Case Study on SAL-Based Teaching and Learning in a Functional Clothing and Materials Course Using Generative AIHyun Ah Kim0https://orcid.org/0000-0003-0834-6076Department of Clothing and Textiles, Changwon National University, Changwon-si, South KoreaWith the rapid development of big data and generative artificial intelligence (AI), education in the apparel industry is evolving beyond traditional theoretical instruction. This study explores the application of Smart Action Learning (SAL) and generative AI tools in the “Functional Clothing and Materials” course to enhance student engagement, problem-solving abilities, and practical skill acquisition. SAL, a student-centered learning approach, incorporates blended learning, flipped learning, and problem-based learning (PBL) methodologies to foster self-directed and cooperative learning. The study was conducted over an eight-week period with second-year students in an apparel major, integrating AI-based problem-solving techniques into coursework. The course design included a five-stage instructional framework: instructor-led lectures, problem identification, AI-assisted research, collaborative solution development, and final presentations. The effectiveness of this approach was evaluated through surveys measuring self-directed learning ability, cooperative learning ability, problem-solving ability, and academic achievement. Results indicate that students demonstrated high levels of engagement, improved problem-solving abilities, and increased learning satisfaction through AI-assisted collaborative projects. The findings suggest that incorporating generative AI into fashion education enhances creative thinking, industry readiness, and adaptability to emerging trends.https://ieeexplore.ieee.org/document/10967260/Generative artificial intelligence (GAI)smart action learning (SAL)self-directed learning abilitycollaborative learning capabilitiestroubleshooting skillsacademic performance |
| spellingShingle | Hyun Ah Kim A Case Study on SAL-Based Teaching and Learning in a Functional Clothing and Materials Course Using Generative AI IEEE Access Generative artificial intelligence (GAI) smart action learning (SAL) self-directed learning ability collaborative learning capabilities troubleshooting skills academic performance |
| title | A Case Study on SAL-Based Teaching and Learning in a Functional Clothing and Materials Course Using Generative AI |
| title_full | A Case Study on SAL-Based Teaching and Learning in a Functional Clothing and Materials Course Using Generative AI |
| title_fullStr | A Case Study on SAL-Based Teaching and Learning in a Functional Clothing and Materials Course Using Generative AI |
| title_full_unstemmed | A Case Study on SAL-Based Teaching and Learning in a Functional Clothing and Materials Course Using Generative AI |
| title_short | A Case Study on SAL-Based Teaching and Learning in a Functional Clothing and Materials Course Using Generative AI |
| title_sort | case study on sal based teaching and learning in a functional clothing and materials course using generative ai |
| topic | Generative artificial intelligence (GAI) smart action learning (SAL) self-directed learning ability collaborative learning capabilities troubleshooting skills academic performance |
| url | https://ieeexplore.ieee.org/document/10967260/ |
| work_keys_str_mv | AT hyunahkim acasestudyonsalbasedteachingandlearninginafunctionalclothingandmaterialscourseusinggenerativeai AT hyunahkim casestudyonsalbasedteachingandlearninginafunctionalclothingandmaterialscourseusinggenerativeai |