Revista de la Academia de Emprendimiento

1528-2686

Abstracto

Creation of Automated Content With Embedded Artificial Intelligence A Study on Learning Management System for Educational Entrepreneurship

Alim Al Ayub Ahmed and Apoorva Ganapathy

These days, typical content creation media are facing a digital transformation. The downfall of content-based streams concerning learning and educational entrepreneur has constrained distributors to focus their approaches on restructuring the values of online content distributed on the internet by refining the traditional learning management systems. Also, if we emphasize small-sized learning content, we can track down the extra challenge of the lack of entrepreneurs, significant to appropriately display reference systems that increase the number of clicks and advertising effects of content. To train novice teachers to be leaders with entrepreneurship skills and efficacy, educational entrepreneurship is of recent origin and is a relatively new phenomenon. In modern times, social media platforms have an incredible influence in strengthening organizations to plan multimedia-oriented and intelligent content. However, then again, there is a lot more to achieve for intelligent content generation approaches. In this situation, this research aims to focus on intellectual content creation methods that strengthen learning management and should be possible by using embedded artificial intelligence. Artificial intelligence is perhaps one of the most exceptional fields, and it can be utilized effectively. Thus, this study is expected to talk about its potential in improving learning management. In this work, we present a methodology for producing automated content with the assistance of embedded artificial intelligence and semantic strategies. We have focused our examination on modular engineering to offer adaptability to the making of elements that take advantage of learning management systems and with incredible recommendation mechanics. Results for educational entrepreneurs in real-time conditions are promising, improving outcomes concerning traffic redirection and automated content creation.

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