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Permanent URI for this collectionhttps://hdl.handle.net/11285/636050
Artículos científicos o técnicos preliminares, sujeto a revisión de pares, pero tiene la intención de ser publicado en una publicación periódica, de manera independiente o como un capítulo de libro de naturaleza académica, tal como resultados preliminares de investigación publicados en cuadernillo separado.
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- Computational thinking assessment: Contributions to the development of complex thinking in higher education(2023-10-25) Suárez Brito, Paloma; Alfaro Ponce, Berenice; George Reyes, Carlos Enrique; López Caudana, Edgar Omar; https://ror.org/03ayjn504; Polytechnic Institute of Bragança, https://ror.org/00prsav78Computational thinking and complex thinking are two approaches of current importance in higher education today, since they seek to enhance trans- versal skills and contribute to solving complex problems effectively, as well as analyzing options from multiple perspectives. Both competencies are considered indispensable for the future, so that students can face life challenges in a better way and propose innovative solutions appropriate to each context. In this work, we present a rubric to measure the Computational Thinking (CT) competency in higher education contexts, designed based on Wing’s (2006) original definition which includes abstraction and automation processes. Our rubric produces quantitative measures about Computational Thinking skills from teachers’ observation. An expert validation procedure was carried out resulting in a tool with high levels of reliability and validity. Findings demonstrate realistic and practical use of the rubric in higher education scenarios and promote the development of trans- versal competencies (including Complex Thinking). Results are discussed in terms of the importance of the promotion of 21st century skills in higher education.
- Gender gap in perceived achievement of complex thinking in engineering students: A challenge for STEM inclusion(2023-10-25) Vázquez Parra, José Carlos; Suárez Brito, Paloma; López Caudana, Edgar OmarThis paper is part of the thematic axis Bridging the diversity gap in STEM, specifically in the themes Diversity and inclusion and Gender studies in STEM. Its objective is to share the results of a study conducted on engineering students in their last semester of training, regarding their perception of achievement of the competence of complex thinking. The intention is to have an insight into how students perceive their level of competence and cognitive skills, in order to assess whether there are significant differences based on gender. For this study, a representative convenience sample of graduating candidates from a university institution in western Mexico was taken. Methodologically, descriptive analyses were made considering a validated instrument. In conclusion, it is identified that the level of achievement perception of engineering and science students is high (4.29), being critical thinking the one that yielded the best perception and sys- temic thinking the lowest. In terms of gender, it is identified that men are those who yielded the best perception in all cases, being the students of Digital Trans- formation Engineering the best self-evaluated.
- 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.
- A stacking ensemble machine learning method for early identification of students at risk of dropout(Springer, 2023-03-07) Talamás Carvajal, Juan Andrés; Ceballos Cancino, Héctor Gibrán; Tecnologico de MonterreyEarly dropout of students is one of the bigger problems that universities face currently. Several machine learning techniques have been used for detecting students at risk of dropout. By using sociodemographic data and qualifications of the previous level, the accuracy of these predictive models is good enough for implementing retention programs. In addition, by using grades of the first semesters, the accuracy of these models increases. Nevertheless, the classification errors produced by these models cause undetected students to be discarded from the retention programs, whereas students with no actual risk consume additional resources. In order to provide more accurate models, we propose the use of a stacking ensemble technique to obtain an improved combined dropout model, while using relatively few variables. The model results show values on the expected ranges for an early dropout model, but with considerably fewer features and historical information, and we show that deploying the models would be cost-efficient for the institution if applied towards an intervention program.