Responsive educational proposals to develop skills to meet the demands of Industry 4.0 have become imperative to guarantee inclusive, equitable, and quality education and promote lifelong learning ...opportunities for all, also reducing the negative impact of COVID-19 and the major post-pandemic social issues. This article analyzes which components of Education 4.0 have been considered in 21st century skills frameworks and identifies the teaching and learning methods and key stakeholders impacted. We conducted a systematic literature review (SLR) with research questions to highlight studies that address 21st century frameworks worldwide, identifying which teaching-–earning strategies contain 4.0 components, their learning dimensions, and the targeted stakeholders. The findings allowed us to identify opportunities to create or improve 21st century skills frameworks with the required Education 4.0 components to develop future skills. Our study revealed the absence of these frameworks for teachers and schools. Most are oriented toward students, developing competencies through the dimensions of character, meta-learning, and linking active learning teaching strategies. This work presents studies incorporating innovative educational practices and the core Education 4.0 components. It concludes with a reflection on creating educational models to develop complex-reasoning competencies and auto-systemic thinking to support problem-solving and address social needs.
Open science, as a common good, opens possibilities for the development of nations, through innovations and collaborative constructions, which help to democratize knowledge. Advances in this area are ...still emerging, and the open science, co-creation of knowledge and open innovation triangle, is presented as an opportunity to generate an original contribution from research to open educational theory and practices. The study analyzed the articles that addressed this triangle, in order to identify the contexts and challenges that arise in open innovation and the co-creation of knowledge to promote open science. The method was a systematic literature review (SLR) of 168 articles published in open access format, from January 2014 to May 2017 in the Web of Science and Scopus databases. In the validation process, the York University criteria were used: inclusion and exclusion, relevance of the pertinent studies, evaluation of the quality / validity of included studies and description of data / basic studies. The findings showed that the most-widely publicized contexts were in the United States and Brazil, in the business and academic sectors (closely followed by the social sector), and the challenges were open to innovation, opening and research. The research concludes that the context and practices of collaboration are substantial elements for innovation and open science.
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IZUM, KILJ, NUK, ODKLJ, PILJ, PNG, SAZU, UL, UM, UPUK
Today's complex, dynamic, interconnected world presents the field of education ("Education 4.0") with significant challenges in developing competencies for reasoning for complexity. This article ...analyzes complex thinking as a macro-competency with sub-competencies of critical, systemic, scientific, and innovative thinking in educational environments. We worked with the systematic literature review method, selecting 35 articles in the Scopus and Web of Science databases using keywords words of interest and applying inclusion and exclusion criteria. Seven research questions guided the data analysis. The results highlighted that: (a) there are common characteristics of studies linking complex thinking, critical thinking, and creative thinking; (b) there is predominance of the qualitative method in the studies; (c) the critical thinking competency has been the most addressed in the research; (d) the predominant components of Education 4.0 are teaching methods and techniques; and (e) the three challenges that stand out for educational research are project feasibility, research opportunities, and required skills. This article is intended to be of value to academic and social communities and decision-makers interested in developing reasoning for complexity within the framework of Education 4.0.
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GEOZS, IJS, IMTLJ, KILJ, KISLJ, NLZOH, NUK, OILJ, PNG, SAZU, SBCE, SBJE, UILJ, UL, UM, UPCLJ, UPUK, ZAGLJ, ZRSKP
In recent years, MALDI-TOF Mass Spectrometry (MS) method has emerged as a promising and a reliable tool for bacteria identification. In this study we compared Bruker MALDI-TOF MS and conventional ...phenotypic methods to identify a collection of 333 Gram-positive clinical isolates comprising 22 genera and 60 species. 16S rRNA sequencing was the reference molecular technique, and rpoB gene sequecing was used as a secondary gene target when 16Sr RNA did not allow species identification of Corynebacterium spp. We also investigate if score cut-offs values of ≥ 1,5 and ≥ 1,7 were accurate for genus and species-level identification using the Bruker system. Identification at species level was obtained for 92,49% of Gram-positive rods by MALDI-TOF MS compared to 85,89% by phenotypic method. Our data validates the score ≥ 1,5 for genus level and ≥ 1,7 for species-level identification in a large and diverse collection of Gram-positive rods. The present study has proved the accuracy of MALDI-TOF MS as an identification method in Gram-positive rods compared to currently used methods in routine laboratories.
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DOBA, IZUM, KILJ, NUK, PILJ, PNG, SAZU, SIK, UILJ, UKNU, UL, UM, UPUK
Society 5.0 is a transformative vision for the future driven by integrating digital technologies and human-centered approaches, fusing with cyber-physical spaces to create a smart society that ...addresses megatrends through innovative and collaborative solutions by stakeholders. This article analyzes Maturity Models (MMs) in Higher Education to identify the components of Education 4.0 that aim to achieve Society 5.0, seeking the dimensions and levels associated with the quintuple helix and the mission of the HEIs. We conducted a systematic literature review (SLR) guided by research questions to highlight studies that address Maturity Models worldwide, identify components of Education 4.0 in the MM, research methods and instruments used, internal and external stakeholders, and some characteristics of the university missions. The study method employed was a Systematic Review analyzing 26 articles from 2018 to 2023 found in WoS and Scopus databases using inclusion and exclusion criteria under a Prisma workflow. The findings were that the HEIs must: a) analyze dimensions of various Education 4.0 components in a balanced way, b) incorporate comparative designs and mixed methods of the MM models, c) provide technology transfer services, training, and data centers, d) provide fully open environments to educate all citizens inclusively, and e) use sustainable MMs for a significant difference in impact. This review offers educational leaders and policymakers the methodologies for measuring the Education 4.0 path to Society 5.0.
This article aims to study machine learning models to determine their performance in classifying students by gender based on their perception of complex thinking competency. Data were collected from ...a convenience sample of 605 students from a private university in Mexico with the eComplexity instrument. In this study, we consider the following data analyses: 1) predict students’ gender based on their perception of complex thinking competency and sub-competencies from a 25 items questionnaire, 2) analyze models’ performance during training and testing stages, and 3) study the models’ prediction bias through a confusion matrix analysis. Our results confirm the hypothesis that the four machine learning models (Random Forest, Support Vector Machines, Multi-layer Perception, and One-Dimensional Convolutional Neural Network) can find sufficient differences in the eComplexity data to classify correctly up to 96.94% and 82.14% of the students’ gender in the training and testing stage, respectively. The confusion matrix analysis revealed partiality in gender prediction among all machine learning models, even though we have applied an oversampling method to reduce the imbalance dataset. It showed that the most frequent error was to predict Male students as Female class. This paper provides empirical support for analyzing perception data through machine learning models in survey research. This work proposed a novel educational practice based on developing complex thinking competency and machine learning models to facilitate educational itineraries adapted to the training needs of each group to reduce social gaps existing due to gender.
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EMUNI, FIS, FZAB, GEOZS, GIS, IJS, IMTLJ, KILJ, KISLJ, MFDPS, NLZOH, NUK, OILJ, PNG, SAZU, SBCE, SBJE, SBMB, SBNM, UKNU, UL, UM, UPUK, VKSCE, ZAGLJ
Class 1 integrons are one of the most successful elements in the acquisition, expression and spread of antimicrobial resistance genes (ARG) among clinical isolates. Little is known about the gene ...flow of the components of the genetic platforms of class 1 integrons within and between bacterial communities. Thus it is important to better understand the interactions among "environmental" intI1, its genetic platforms and its distribution with human activities.
An evaluation of two types of genetic determinants, ARG (sul1 and qacE1/qacEΔ1 genes) and lateral genetic elements (LGE) (intI1, ISCR1 and tniC genes) in a model of a culture-based method without antibiotic selection was conducted in a gradient of anthropogenic disturbances in a Patagonian island recognized as being one of the last regions containing wild areas. The intI1, ISCR1 genes and intI1 pseudogenes that were found widespread throughout natural communities were not associated with urbanization (p>0.05). Each ARG that is embedded in the most common genetic platform of clinical class 1 integrons, showed different ecological and molecular behaviours in environmental samples. While the sul1 gene frequency was associated with urbanization, the qacE1/qacEΔ1 gene showed an adaptive role to several habitats.
The high frequency of intI1 pseudogenes suggests that, although intI1 has a deleterious impact within several genomes, it can easily be disseminated among natural bacterial communities. The widespread occurrence of ISCR1 and intI1 throughout Patagonian sites with different degree of urbanization, and within different taxa, could be one of the causes of the increasing frequency of multidrug-resistant isolates that have characterized Argentina for decades. The flow of ARG and LGE between natural and clinical communities cannot be explained with a single general process but is a direct consequence of the interaction of multiple factors operating at molecular, ecological, phylogenetic and historical levels.
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DOBA, IZUM, KILJ, NUK, PILJ, PNG, SAZU, SIK, UILJ, UKNU, UL, UM, UPUK
This article aims to study the performance of machine learning models in forecasting gender based on the students' open education competency perception. Data were collected from a convenience sample ...of 326 students from 26 countries using the eOpen instrument. The analysis comprises 1) a study of the students' perceptions of knowledge, skills, and attitudes or values related to open education and its subcompetencies from a 30-item questionnaire using machine learning models to forecast participants' gender, 2) validation of performance through cross-validation methods, 3) statistical analysis to find significant differences between machine learning models, and 4) an analysis from explainable machine learning models to find relevant features to forecast gender. The results confirm our hypothesis that the performance of machine learning models can effectively forecast gender based on the student's perceptions of knowledge, skills, and attitudes or values related to open education competency.
Educational strategies have evolved over the years, due to research breakthroughs and the application of technology. By using the latest learning innovations, curriculum and instructional design can ...be enhanced and strengthened. The "Handbook of Research on Driving STEM Learning with Educational Technologies" is an authoritative reference source for the latest scholarly research on the implementation and use of different techniques of instruction in modern classroom settings. Featuring exhaustive coverage on a variety of topics including data literacy, student motivation, and computer-aided assessment, this resource is an essential reference publication ideally designed for academicians, researchers, and professionals seeking current research on emerging uses of technology for STEM education. Following the Preface by María-Soledad Ramírez-Montoya, this book contains the following chapters: (1) Training Educational Researchers in Science and Mathematics: A Case Study Through a Binational Workshop Mexico-UK (María-Soledad Ramírez-Montoya); (2) Using Modeling and Simulation to Learn Mathematics (Ruth Rodríguez Gallegos); (3) Teachers and Mathematical Modeling: What Are the Challenges? (Samantha Analuz Quiroz Rivera and Ruth Rodríguez Gallegos); (4) Data Literacy and Citizenship: Understanding "Big Data" to Boost Teaching and Learning in Science and Mathematics (Eddy L. Borges-Rey); (5) Financial Literacy: Gaps Found Between Mexican Public and Private, Middle, and High-School Students (Adriana Berenice Valencia Álvarez and Jaime Ricardo Valenzuela González); (6) A Project-Based Learning Approach: Developing Mathematical Competences in Engineering Students (Ismael Osuna Galan and Alejandro Miguel Rosas-Mendoza); (7) Didactic Sequences Teaching Mathematics for Engineers With Focus on Differential Equations (Luis Ramón Siero González and Avenilde Romo Vázquez); (8) Making Links Between Solutions to an Unstructured Problem: The Role of Pre-Written, Designed Student Responses (Sheila Evans); (9) Assessing Authentic Intellectual Work in Mathematics Tasks (Lesly Yahaira Rodríguez Martínez, María Guadalupe Pérez Martínez, and Adriana Mercado Salas); (10) The Importance of the Disciplinary Perspective in Educational Research (Ross Kerr Galloway and Paul Hernandez-Martinez); (11) Learning Biology With Situated Learning in Mexican Zapoteca Tele-Secondary Schools (Paulina Guerrero-Gutiérrez); (12) Transformations of the Concept of Linear Function in Technological High Schools (Rebeca Flores Garcia); (13) Measurement Instruments to Motivate Scientific Learning by Conceptual Change (Ana Marcela Monjardín Gopar and Gerónimo Mendoza Meraz); (14) Test Design to Assess the Qualities of Science Students' Prior Knowledge (Luis Hernán Arellano Ulloa, Gerónimo Mendoza Meraz, and Ana Cecilia Villarreal Ballesteros); (15) Argumentation Schema to Analyze High School Students' Scientific Reasoning (Ricardo Lorenzo De la Garza, Genaro Zavala, and Alma Adrianna Gómez Galindo); (16) Accurate Items for Inaccurate Conceptions in Undergraduate Physics Students (Eder Hernandez and Genaro Zavala); (17) A Look into Students' Interpretation of Electric Field Lines (Esmeralda Campos and Genaro Zavala); (18) Research-Based Strategies in an Electric Circuits Lab: Tutorials and RealTime Physics Approaches (Monica Quezada-Espinoza and Genaro Zavala); (19) Integration of Digital Technologies: Collaborative Practices in Teaching Mathematics (Andrés Vázquez Faustino); (20) The Effectiveness of Computer-Aided Assessment for the Purposes of a Mathematical Sciences Lecturer (Stephen James Broughton, Paul Hernandez-Martinez, and Carol L. Robinson); (21) Construction of the Definite Integral Concept Using Open Source Software (Lizzeth Aurora Navarro-Ibarra, Omar Cuevas-Salazar, and Alan Daniel Robles-Aguilar); (22) Context as Action in the Teaching of Statistical Concepts: An Activity Theory Perspective (Helen Harth); (23) Statistics in Journalism Practice and Higher Education (Jairo A. Lugo-Ocando); (24) Understanding Quality of Statistics in News Stories: A Theoretical Approach from the Audience's Perspective (Alessandro Martinisi); and (25) The Uses of Science Statistics in the News Media and on Daily Life (Renata Faria Brandao). A compilation of references, a section about the contributors, and an index are included.
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