Artículo
Permanent URI for this collectionhttps://hdl.handle.net/11285/345284
Artículo científico o editorial en una publicación periódica académica sujeto a revisión de pares. Cumple con los índices internacionales o bases de datos de amplia cobertura, como el listado del Current Contents, ISI WEB of Knowledge (http://isiknowledge.com/) e índice de revistas mexicanas de CONACYT (www.conacyt.mx/dac/revistas). Éstos indizan y resumen los artículos de revistas seleccionadas, en todas las áreas del saber.
Browse
Search Results
- Computational thinking in STEM education: current state-of-the-art and future research directions(Frontiers, 2025-01-08) Rasikh, Tariq; Aponte Babines, Bertha María; Ramírez, Jesús; Icaza Longoria, Inés Álvarez; Naseer, Fawad; Todor GanchevThe knowledge society exists mainly due to advancing technology and the exponential development of professionals’ capabilities. Digital transformation and new technologies generate complex environments demanding high-level skills. This work analyzes the current state of pedagogical approaches with a special focus on project-based learning that develops computational thinking in STEM students. A Systematic Literature Review examined the current state of pedagogical approaches along with project-based learning aimed at enhancing computational thinking within the context of higher education. Results allowed us to infer that (a) computational thinking promotes sustainable development through STEM education and novel teaching practices; (b) it is a fundamental skill for the problem-solving processes that evolve with technological progress; (c) its development is a global concern, not limited to a country’s development level; and (d) its introduction at an early stage provides opportunities for the advancement of vulnerable groups. Outlining, this study conducts a Systematic Literature Review (SLR) using PRISMA 2020 guidelines to analyze pedagogical approaches including project-based learning for enhancing computational thinking in STEM higher education, identifying global research trends, common strategies, and areas for improvement, while proposing a framework to align computational thinking skills with emerging technological challenges and promote sustainable educational practices. This study presents relevant results on the construction of state-of-the-art computational thinking and education; it is valuable for curricular design underpinning disciplinary and interdisciplinary approaches.
- Remaigining the future through the co-creation of social entrepreneurship in higher education: a multivariate prediction model approach(Emerald, 2024-12-10) Ramírez Montoya, María Soledad; Casillas Muñoz, Fidel; Tariq, Rashik; Icaza Longoria, Inés Álvarez; Portugués Castro, May; EGADE Bussines SchoolPurpose – This remastered analysis focuses on the impact of entrepreneurial interventions in higher education institutions (HEI), particularly in social entrepreneurship. The study evaluated the effectiveness of such interventions through a pre-and post-test approach, examining various skill sets in students. The primary goal was to analyze the influence of entrepreneurial training programs on students’ competencies in social entrepreneurship by analyzing changes in personal behavior, leadership, innovation, social value and management skills before and after the educational interventions. Design/methodology/approach – The study employed a quasi-experimental design, analyzing pre-and post-test results in three distinct social entrepreneurship training experiences. The sample consisted of 304 participants, providing a comprehensive view of the impact of these interventions. Findings – The main findings were: (1) Educational interventions in social entrepreneurship must emphasize strategies for self-awareness, emotional intelligence and personal development improvement. The analysis revealed significant improvements in these areas, indicating that targeted strategies in these domains are essential for enhancing the effectiveness of social entrepreneurship education. (2) The impact of educational interventions on these capabilities can be effectively evaluated using machine learning methods such as ordinary least squares (OLS) regression. This approach allows for the inclusion of variables such as gender, age or location, providing a comprehensive assessment of the interventions’ impact. (3) The interventions were particularly effective in improving students’ innovation and leadership competencies. The analysis demonstrated substantial enhancements in these areas, underscoring the success of the interventions in developing these critical skills. (4) The study highlighted the need for a more focused approach in future interventions, emphasizing the importance of management, social value and personal skills. Additionally, it pointed out the necessity of developing and utilizing appropriate tools to create and evaluate these interventions effectively. Practical implications – The study provides insights into improving educational interventions in social entrepreneurship to better develop essential skills in students. Originality/value – This research introduces a significant approach to educational interventions for educational communities and decision-makers by demonstrating the effectiveness of entrepreneurial training for competencies in innovation and leadership, which are crucial for societal and economic development.