10.71922/jee.2024.1128924

Presenting the model of intelligent sales learning agent in sports start-ups According to the foundation's data method

  1. رئیس دانشگاه آزاد اسلامی واحد فیروزآباد

Revised: 2024-08-12

Accepted: 2024-11-22

Published in Issue 2025-04-12

How to Cite

Rastegari, M. (2025). Presenting the model of intelligent sales learning agent in sports start-ups According to the foundation’s data method. Journal of Education Experiences, 7(2), 132-157. https://doi.org/10.71922/jee.2024.1128924

PDF views: 139

Abstract

Sports startups have positive effects on the society by providing innovative solutions and will improve sports facilities and services in the future with the development of technology and innovation. The sports startup can be considered a fledgling startup that aims to achieve big goals with the aim of developing sports and supporting domestic manufacturers. One of the great advantages of this site is the free registration of advertisements for the sale of sports goods, as well as the scope of this site. You can know the whole country because you can register ads and buy and sell in all cities. This article is organized in order to present the model of the intelligent agent learning sales in sports start-ups using the foundation data method, which is a qualitative research in terms of its purpose, application and in terms of how to collect information. The statistical community includes experts and knowledgeable people about sports. The sample volume was estimated with theoretical saturation of 16 people using snowball sampling. The data collection tool in the qualitative section was a semi-structured interview. The validity and reliability of the work was used from Guba and Linkin's criteria, which consists of four more detailed concepts of credibility, transferability, verifiability, and reliability. Max Kyoda 20 software was used for coding. To analyze the data, the systematic method of Strauss and Corbin was done with open, axial and selective coding. In this research, the intelligent sales learning agent was identified as the central category. The most important causal factors affecting it include smart digital sensors, smart digital actors, augmented and virtual reality technology, Internet of Things, cross-linguistic information retrieval, intelligent information retrieval, cloud computing, machine learning, big data, knowledge architecture, information/content/ organization Knowledge, smart digital support, digital structure, knowledge, knowledge and network attitude were smart contract platforms. The present research led to the presentation of the model of the intelligent sales learning agent in sports start-ups using the data base method.

Keywords

  • intelligent learning,
  • agent/artificial intelligence,
  • foundational data theory