Some AI tools attached to learning management systems in education provide unparalleled opportunities to support students in the era of e-learning platforms. Learning management systems, through smart tools attached to them, allow recording the registered learner’s activity in order to explore unique types of data coming from the academic context in order to improve the learning experience. Therefore, this research aims to explore the possibility of adapting crochet to make outerwear using some AI tools attached to learning management systems. The sample included 136 female students from the fourth level in the Home Economics Department, who were randomly divided into two experimental groups with 68 students in each group. A product evaluation card was used as the main tool of the study. The results showed that using big data analysis technology as a smart tool attached to the Blackboard learning management system had a significant and positive impact on the possibility of adapting crochet to make outerwear, and the results provide important evidence of the advantages of AI tools attached to learning management systems in home economics studies.
Elbiyali, M., & Morsi, M. (2024). Adapting crochet to make outerwear using some artificial intelligence tools. Journal of Specific Education and Technology (Scientific and Applied Research), 31(1), 845-861. doi: 10.21608/maat.2024.339915.1185
MLA
Marwa Elbiyali; Marwa Morsi. "Adapting crochet to make outerwear using some artificial intelligence tools", Journal of Specific Education and Technology (Scientific and Applied Research), 31, 1, 2024, 845-861. doi: 10.21608/maat.2024.339915.1185
HARVARD
Elbiyali, M., Morsi, M. (2024). 'Adapting crochet to make outerwear using some artificial intelligence tools', Journal of Specific Education and Technology (Scientific and Applied Research), 31(1), pp. 845-861. doi: 10.21608/maat.2024.339915.1185
VANCOUVER
Elbiyali, M., Morsi, M. Adapting crochet to make outerwear using some artificial intelligence tools. Journal of Specific Education and Technology (Scientific and Applied Research), 2024; 31(1): 845-861. doi: 10.21608/maat.2024.339915.1185