COVID-19 forced higher education institutions to reinvent themselves. The (usually) face-to-face education has swapped to distance contingency education. This change brought about numerous challenges that impose adjustments in several dimensions, such as pedagogical strategies and the dependence on teaching platforms and computer systems—and, above all, the new relationship between the various actors (students, teachers, and management staff). All the sudden changes, combined with uncertainty concerning what was happening, created several strategies and options. This paper has the main purpose of analyzing the scientific production on higher education of EU27 academic institutions during the 2020 COVID-19 pandemic in journals indexed in Clarivate Analytics’ Web of Science and Elsevier’s Scopus. The sample is composed of 22 articles in total. The results show that the articles were published in 19 journals; their main focuses are Higher Education, COVID-19, and distance learning. In our database, we find several types of concerns, which shows that HEIs have a wide range of dimensions. We intend this article to be an instrument, not only to identify what was done in 2020, but to point out clues for the future.
The epidemiological situation caused by the COVID-19 pandemic led to efforts to mitigate the transmission of the infection, forcing workers and students to stay at home. Universities closed, as did many businesses, forcing education and work to adapt to the new situation. While for some people it was a positive experience, for others it was not. This article analyzes the responses of 89 respondents, over 18 years old, in teleworking or enrolled in university online education, in a survey at the beginning of 2021, when Portugal was in a new state of emergency. Variables such as gender, age and parenthood were used, as well as ownership of equipment, own workspace, and quality of internet, comparing distance learning/work with traditional methods and measuring levels of satisfaction and willingness to adopt this model in the future. These results suggest an association of gender and parenting in the valuation of telework/distance education; women were more positive than men and participants with children were more positive than participants without children. The same was the case for respondents with their own workspace and better-quality internet. There is a strong relation between paternity and the preference for the distance model, in the sense of valuing the distance model, as well as a relation between those who have their own work space and the appreciation of the distance model. In general, respondents to our survey showed that they are not fond of adopting telework/distance learning in the future.
Retention and dropout of higher education students is a subject that must be analysed carefully. Learning analytics can be used to help prevent failure cases. The purpose of this paper is to analyse the scientific production in this area in higher education in journals indexed in Clarivate Analytics’ Web of Science and Elsevier’s Scopus. We use a bibliometric and systematic study to obtain deep knowledge of the referred scientific production. The information gathered allows us to perceive where, how, and in what ways learning analytics has been used in the latest years. By analysing studies performed all over the world, we identify what kinds of data and techniques are used to approach the subject. We propose a feature classification into several categories and subcategories, regarding student and external features. Student features can be seen as personal or academic data, while external factors include information about the university, environment, and support offered to the students. To approach the problems, authors successfully use data mining applied to the identified educational data. We also identify some other concerns, such as privacy issues, that need to be considered in the studies.
Teaching and learning how to program are not easy tasks. Disapproval and dropout rates are a concern for everyone concerned with the topic. Therefore, it is necessary to look for strategies that improve the motivation of students who start a programming course, also improving success rates and decreasing dropout rates. The inverted class model, or flipped classroom, has been used in several experiments, showing very good results. The objectives of this teaching-learning technique is to change the traditional order: students have contact with new subjects before the classroom, using videos, texts or other material, as well as small online tests to check their knowledge. In this way, the face-to-face classes are reserved for discussion, doubts and application of previously acquired knowledge. The purpose of this paper is to analyze the scientific production on Flipped classrooms in introductory programming courses indexed in Elsevier’s Scopus. The sample is composed by 45 articles in total. The results obtained by bibliometric analysis showed when and where those documents are published, who are the authors and what is the focus of said articles. We also analyzed the most cited documents. We made a summary of the articles, namely in what refers to the sample size of the experiences, which programming language is used, in which universities the articles are made, which technology is used, as well as which methods are used in order to create inverted classes and which are the objectives and results of these experiences reported on the articles.. We managed to get a global view of the theme, getting a strong analysis for those who want to use flipped classrooms for teaching programming.
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