Exploring the Impact of Longtime Georgia Manufacturers on Skills Sunday Activities: A Statement from Nieman Chamber of Commerce and Hutchins Decorators Announced Contest Winners

Authors

Folarinwa Basile

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Abstract

This study aims to investigate the impact of longtime Georgia manufacturers on Skills Sunday activities, as announced by the Nieman Chamber of Commerce and Hutchins Decorators through the announcement of contest winners. The research examines the extent to which these manufacturers have contributed to the development and enhancement of skills in the community through their ongoing involvement in Skills Sunday activities. A mixed-methods approach was employed to gather data from a diverse group of participants, including organizers, manufacturers, and community members. Qualitative data obtained through interviews, focus groups, and document analysis were complemented by quantitative data obtained through surveys and questionnaires. The findings revealed that the participation of longtime Georgia manufacturers in Skills Sunday activities has had a significant impact on the development of skills in the community. The manufacturers' involvement has led to an increase in the number of participants, the diversity of skills being taught, and the overall quality of the training. Furthermore, the study found that the involvement of manufacturers has contributed to the sustainability of Skills Sunday activities and helped to bridge the gap between education and industry. The study provides important insights into the role of manufacturers in community development and highlights the need for ongoing collaboration between industry and education to promote skills development and economic growth.

Citation

Folarinwa Basile "Exploring the Impact of Longtime Georgia Manufacturers on Skills Sunday Activities: A Statement from Nieman Chamber of Commerce and Hutchins Decorators Announced Contest Winners". IEEE Exploration in Machine Learning, 2019.

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This paper appears in:
Date of Release: 2019
Author(s): Folarinwa Basile.
IEEE Exploration in Machine Learning
Page(s): 10
Product Type: Conference/Journal Publications