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One of the main goals for Higher Education is to educate students to work in teams. Such a skill not only improves their social behavior in the community, but also the ability for solving complex problems. Usually, the process of making teams is carried out by professor of the subject, who has to take into account several criteria (e.g. the presence of leader, heterogeneity of the team according the level of knowledge, sex, among others). When the subject has just few students, this task becomes easy. However, in the case of classes with a large number of students, this task becomes complex and there is no warranty about the accomplishment of the considered criteria. In that sense, the present work proposes a computational solution that automatizes the task of student teams building. Specifically, it was approached as a multi-objective combinatorial optimization problem, which was solved using a Pareto Dominance-based algorithm. In order to validate the proposal we performed several computational experiments involving real case studies from the English subject of three careers at the Technical State University of Quevedo. Results show that the proposed approach is able to build balanced teams according to the considered criteria.

In this study, we report on a Systematic Mapping Study (SMS) for the application of technology acceptance models to Moodle under the prism of latent variable modeling. Based on an automatic search including primary studies from journals, conferences, and book chapters during 2001 to 2019, 41 primary were selected. We aim to contribute to a better understanding of how research has been conducted in this field by identifying research trends and gaps. Moreover, we assessed the reported statistical processes and quantitatively summarized the main findings achieved so far. We found that this is a research topic with an increasing interest today, where most of the reported experiences extend the Technology Acceptance Model (TAM), focus on college students from several programs, come from Europe or Asia, and are published as articles of journals with different impact factors. Overall, studies presented important issues regarding how the statistical analysis was conducted, specially regarding pre- and post-analysis stages. Furthermore, a large number of hypotheses has been tested with a predominance of those from original models. Some research opportunities were also identified and discussed.

Being digitally competent is an imperative requirement for the 21st century university teacher, a fact recognized by both the literature and policymakers. Although this topic has been addressed in different reviews and critical studies recently, none of them have systematically and explicitly addressed the factors that explain, or are explained by, the digital competencies of university teachers. Examples of these factors include, among others, demographic, professional and psychological aspects of university teachers, as well as very specific digital competencies. The present study seeks to close this gap through a systematic mapping of the literature published until 2021 in journals indexed by Scopus and Web of Science (WOS). Based on the selection of 53 primary studies, we characterized the literature and summarized the main results reported so far. The analysis allowed us to conclude the following: (1) there is a growing number of contributions aimed at understanding the acquisition of digital competencies, especially from external factors; (2) European, and more specifically Spanish, university teachers from multiple disciplines are the most studied population; (3) most studies adopted quantitative approaches to explain but not prove causality; (4) there is a great heterogeneity of relationships and results that explain the digital competencies of university professors. The implications of these results are discussed with a view to identifying the gaps that provide scope for future research.

Evaluating digital competencies has become a topic of growing interest in recent years. Although several reviews and studies have summarized the main elements of progress and shortcomings in this area, some issues are yet to be explored. Very little information is available about the ways of ensuring the validity and reliability of the instrument used. This study addresses this issue through systematic mapping covering the period from January 2015 to July 2020. Based on 88 primary studies, we conclude that a growing number of studies have emerged over the years; most of them are based on European university students in social science programs; the quality of the journals where they were published is low; and the instruments used are mostly questionnaires and ad-hoc surveys that measure the various dimensions of digital competence based on participants' perceptions. Out of the eight possible types of quality assessment, studies commonly report only four (one in the case of reliability and three in the case of validity). More than 50% of the studies do not provide evidence of having assessed the reliability and validity at the same time. Although participant discipline resulted in a significantly association with the practice of reporting reliability and validity assessments, no specific dimension explained such association. A non-parametric multivariate analysis reveals, among other interesting patterns, that the practice of not reporting quality assessments is more present in studies where participants belong to the fields of Engineering and Technology, Health Sciences, and Humanities.

This paper addresses the problem of insolvency prediction in Spanish SMEs from a binary classification perspective. From a dataset containing more than 325 dependent variables of different natures (including demographic and economic-financial) and 17562 SMEs, a decision tree has been fitted that with a 0.93 accuracy predicts the state of a company and allows it to identify the most relevant variables in such prediction. The results obtained indicate that, in general, insolvency can be predicted from very few financial variables and with an anticipation of more than 10 years before the insolvency event. As a result, it is possible to provide early warnings to SMEs based on the indicators identified. [ABSTRACT FROM AUTHOR]

Learning computer programming is a challenging process. Among the current approaches for overcoming this challenge, visual programming languages (VPLs), such as Scratch, have shown very promising results for beginners. Interestingly, some higher education institutions have started to use VPLs to introduce basic programming concepts, mainly in CS1 courses. However, an important issue regarding Scratchs usage in higher education environments is that students may feel unmotivated being confronted by programming exercises that do not fulfill their individual expectations. To try and overcome this barrier, we propose CARAMBA, a Scratch extension including an exercise recommender system. Based on features, such as taste and complexity, CARAMBA is able to personalize student learning with Scratch by suitably suggesting exercises for students. An in-depth evaluation was conducted about the effects of our proposal on both the learning of basic concepts of CS1 and the overall performance of students. We adopted an equivalent pretest-posttest design with 88 college students at an Ecuadorian university. Results confirm that recommending exercises in Scratch had a positive effect on students programming learning abilities in terms of pass rates. In totality, the pass rate achieved by our proposal was over 52%, which is 8% higher than the rate achieved during a previous experience using only Scratch (without recommendation) and 21% higher than the historical results of traditional teaching (without Scratch). Furthermore, we analyzed the degree of exploitation of CARAMBA by students to portray two facts: students actually used CARAMBA and there was a significant, positive correlation between the utilization of CARAMBA and the scores obtained by the students.

In this study, we report on a Systematic Mapping Study (SMS) for the application of technology acceptance models to Moodle under the prism of latent variable modeling. Based on an automatic search including primary studies from journals, conferences, and book chapters during 2001 to 2019, 41 primary were selected. We aim to contribute to a better understanding of how research has been conducted in this field by identifying research trends and gaps. Moreover, we assessed the reported statistical processes and quantitatively summarized the main findings achieved so far. We found that this is a research topic with an increasing interest today, where most of the reported experiences extend the Technology Acceptance Model (TAM), focus on college students from several programs, come from Europe or Asia, and are published as articles of journals with different impact factors. Overall, studies presented important issues regarding how the statistical analysis was conducted, specially regarding pre- and post-analysis stages. Furthermore, a large number of hypotheses has been tested with a predominance of those from original models. Some research opportunities were also identified and discussed. [ABSTRACT FROM AUTHOR]

Moodle is one of the most widely used learning management systems currently and has traditionally been studied through the Technology Acceptance Model. Existing literature is scattered and does not allow us to clearly conclude what characteristics this technological acceptance has as well as its main progress. The study aimed to provide an overview of the scientific literature on the application of TAM in the study of the acceptance and technological use of Moodle through a Systematic Mapping Study (SMS). Results from 24 selected studies indicate that the topic is of increasing interest and that the literature is characterized by studies that 1) use extended versions of TAM; 2) are based on university students from different programs; 3) take place in Europe or Asia; 4) are published in journals with different impact factors; and 5) have focused on testing mainly the original TAM hypotheses. Although a lot of hypotheses have been studied (271), only 16 have been accepted more times than rejected by 2 or more studies, with Perceived Ease of Use being the most commonly present construct in the hypotheses. Results imply that although TAM remains as a robust model for studying Moodle there are still important gaps to be addressed. [ABSTRACT FROM AUTHOR]

Learning computer programming is a skill hard to achieve in college students. One of the current approaches to dealing with this difficulty is to introduce Visual Programming Languages such as Scratch in the initial courses. The goal is to soften the learning curve and focus the student on acquiring algorithmic and computational thinking. However, there is evidence that the motivation of more prepared students may be affected since they usually expect more professional environments to work with. One recent alternative to solve this dilemma is CARAMBA, a Web platform that involves an exercise recommendation system along with Scratch. In this way, students can build their learning paths according to their interests and level of knowledge. Although the success of CARAMBA is remarkable, some questions related to its impact still remain to be answered. In this sense, the present investigation aims to analyze the correlation existing between two important variables: the level of utilization of CARAMBA and the improvement rate on a computer programming course. The results obtained from an Ecuadorian university show a positive, significant correlation between these two variables, which is an additional evidence of the benefits of CARAMBA. [ABSTRACT FROM AUTHOR]