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- Technological ecosystems for enhancing multiculturality (TEEM)(2023-10-25) Pacheco Velazquez, Ernesto Armando; Rodés Paragarino, Virginia; Instituto para el Futuro de la Educación; https://ror.org/03ayjn504; Polytechnic Institute of BragançaGame-based learning is an effective approach to developing learning skills, and simulations play a crucial role in the logistics field by providing realistic and hands-on training. This article presents the findings of a four-year study that investigated students' experiences and perceptions of a Logistics Simulator, known as LOST, used in a logistics undergraduate course for engineering education in Mexico. LOST simulated supply chain operations and aimed to enhance the development of logistical concepts and complex skills. Qualitative data was collected through open-ended questions to assess students' experiences with LOST, involving a total of 216 students across different course cohorts. The responses were analyzed using axial coding to identify the most valued elements of the game-based learning experience with the logistics simulator. The results indicate that students highly valued elements such as the Real World, Decision-Making, Theory in Practice, Learning, Knowledge, Complexity, Experimentation, and Strategies. These findings emphasize the transformative potential of game-based experiences with the simulator, offering innovative and engaging learning opportunities for educational communities, equipping students with crucial decision-making skills, and providing decision-makers with insights into the effectiveness of simulation-based approaches for enhancing learning outcomes and preparing individuals for real-world complex challenges.
- Financial inclusion of vulnerable sectors with a gender perspective: risk analysis model with artificial intelligence based on complex thinking(Research Square, 2023-01-03) Medina Vidal, Adriana; Alonso Galicia, Patricia Esther; González Mendoza, Miguel; Ramírez Montoya, María SoledadThe objective is to present a proposal for a gender-sensitive risk analysis model using artificial intelligence (AI) within the framework of complex thinking, specifically for impoverished and vulnerable women. This international non-parametric study analyzed business and entrepreneurial activity in a sample of 2,787 women. The methodological design included data analysis, the postulation of a proposed model, and a validation method for the credit risk analysis model. There is a correlation between the level of schooling of impoverished and vulnerable women with the possibility of self-employment and selling a product or service. In the framework of complex thinking, the perception of innovative thinking is related to the level of education and innovative decision-making in professional projects. Women with a higher level of schooling tend to think about their professional projects systematically. Promoting complex thinking involves innovative educational practices to encourage critical, systemic, scientific, and innovative thinking in entrepreneurship and sustainable development. Integrating reasoning for complexity benefits women and contributes to economic and social growth in vulnerable regions. In contrast to other models, our credit risk analysis model uses AI and variables for gender, vulnerability, and complex thinking to detect patterns in women's behaviors and attitudes in the venture start-up process.