There are currently numerous style manuals that contain rules and recommendations for the preparation and presentation of scientific documents. Among the most widespread standards we can quote: the Council of Science Editors (CSE) style and the Harvard System of Referencing, widely used in biology, physics and chemistry; The Chicago Manual Style, widely used in history and law; the IEEE Standards Style Manual, used in engineering, computer science and technology; the MLA Handbook for Writers of Research Papers, common in literature, arts and humanities publications; the Publication Manual of the American Psychological Association (APA), frequently used in the social and behavioral sciences; and the Uniform Requirements for Manuscripts Submited to Biomedical Journals (URM) or Vancouver format, applied by the main biomedical journal publishers. Each of these manuals offer specific guidelines that logically conform to the conventions of the different scientific fields. Among other issues, they tend to address aspects such as the structure and organization of the manuscript, indications for presenting tables and figures, the format of citations and bibliographic references, and even offer ethical, legal and deontological recommendations. Among scientific journals of educational research, the adoption of the APA publication manual is widespread. Proof of this is that the 10 Spanish educational journals with an international impact factor in the 2021 edition of the Journal Citation Reports (categories of Education & Educational Research, Education, Scientific Disciplines, Education, Special and Psychology, Educational) refer in their guidelines for the submission of manuscripts to the indications contained in this manual. In the specific case of Education XXI, it is expressly indicated that, in the preparation of the manuscript, authors should follow the APA publication guidelines in its 7th edition.

(1) The present study aims to explore the impact of job demands and resources (JDR), personal resources, and the organizational culture on workers’ wellbeing and health. (2) A cross-sectional survey of Spanish workers in small and medium-sized enterprises (SMEs) was conducted with a sample of 1599 workers from 154 SMEs. A multivariate multilevel analysis was performed to analyze the different relationships. (3) In light of the results obtained, we observed that job demands were negatively associated with workers’ health, while job resources were positively correlated to workers’ health and wellbeing. Secondly, the different types of identification at work are positively related to job satisfaction and organizational citizenship behaviors (OCBs), but the intensity of this association differs with the form of identification. Finally, at the organization level, the dimensions of organizational culture are related differently to employees’ job satisfaction, OCBs, and health; (4) these results confirm the role of organizational culture and its association with desirable outcomes, allowing us to expand the JDR model.

This paper analyzes the evolution of technology trends in education from 2010 to 2015, using as input the predictions made in the Horizon Reports on Higher Education, published yearly since 2004. Each edition attempts to forecast the most promising technologies likely to impact on education along three horizons: the short term (the year of the report), the midterm (the following two years), and the long term (the following four years). This paper applies social analysis, based on Google Trends, and bibliometric analysis, with data from Google Scholar and Web of Science, to these predictions in order to discover which technologies were successful and really impacted mainstream education, and which ones failed to have the predicted impact and why. This paper offers guidelines that may be helpful to those seeking to invest in new research areas.

This article analyzes a survey delivered in 2019 to 259 experts in engineering education that asked them to forecast information and communication technologies, which were most likely to impact the practice of engineering education based on the expert's discipline (electrical, electronics, mechanical, telecommunications engineering, computer science, etc.) and region. The analysis was performed from different perspectives. First, a descriptive approach was used to analyze technologies that are considered as the most important for the experts and a nonparametric perspective approach was adopted to evaluate variation in the responses according to discipline, region, and years of experience. Second, a decision tree technique was used to establish technology profiles based on when the experts expected that the technologies will impact mass engineering education and the challenges or requirements needed to get widespread use. Third, the Spearman correlation coefficient was used to determine the value of social interest, measured through Google Trends, as a predictor of expert ratings of different technologies. Results indicate adaptive and personalized learning technologies, learning analytics, and open educational resources are the three most promising technologies that will impact engineering education in the short term. Results also show a relation between the predictions made by the experts in 2019 and the social interest in the Google Trends education category.