Performance and mathematical self-concept in university students using Khan Academy.

Information and Communication Technologies (ICT) have fueled innovative support techniques in the educational field that enhance students' educational training processes. The goal of this study was to measure the relationships between progress in that training, mathematical self-concept, and the new students' academic performance when they were supported by an online training, through the Khan Academy platform. A sample of 906 students distributed over four cohorts was analyzed through correlational and inferential quantitative methodology. The results show that students' academic performance was directly related to their mathematical self-concept, their progress in the online training, and other socioeconomic factors, such as being in receipt of grants, their parents' educational attainment, and access to technological devices at home, highlighting a technological gap in academic performance in favor of students with access to such devices. Further research is needed about the role of teachers and the methodology that accompanies learning through this technological tool.

Differences About Reasons and Sources of Information for Choosing Degree Courses.

BACKGROUND: Only a few months before starting university, more than 50% of Spanish high-school students do not know what course to choose. Data from the Ministry of Education show that dropout rates reach 40% in some Spanish communities. This study aims to analyse the most important reasons behind students' choices of degree course and the sources of information they use to help them choose depending on the type of the school and the field of study chosen. METHOD: A sample of 2,254 students from all over Spain completed two previously validated questionnaires. RESULTS: The results showed that in general terms, intrinsic motives were more highly valued. The sources of information that students used most and rated more highly were university websites and family advice. Students from private schools rated guidance activities organized by universities more highly than students from state schools. Mann-Whitney U and Kruskal-Wallis statistics showed that the intrinsic component was more highly valued by students who wanted to study degrees in the fields of Arts and Humanities or Services. CONCLUSIONS: These findings provide quality information that may be used to improve the effectiveness of guidance counselling activities.

RegulonDB 11.0: Comprehensive high-throughput datasets on transcriptional regulation in Escherichia coli K-12.

Genomics has set the basis for a variety of methodologies that produce high-throughput datasets identifying the different players that define gene regulation, particularly regulation of transcription initiation and operon organization. These datasets are available in public repositories, such as the Gene Expression Omnibus, or ArrayExpress. However, accessing and navigating such a wealth of data is not straightforward. No resource currently exists that offers all available high and low-throughput data on transcriptional regulation in Escherichia coli K-12 to easily use both as whole datasets, or as individual interactions and regulatory elements. RegulonDB (https://regulondb.ccg.unam.mx) began gathering high-throughput dataset collections in 2009, starting with transcription start sites, then adding ChIP-seq and gSELEX in 2012, with up to 99 different experimental high-throughput datasets available in 2019. In this paper we present a radical upgrade to more than 2000 high-throughput datasets, processed to facilitate their comparison, introducing up-to-date collections of transcription termination sites, transcription units, as well as transcription factor binding interactions derived from ChIP-seq, ChIP-exo, gSELEX and DAP-seq experiments, besides expression profiles derived from RNA-seq experiments. For ChIP-seq experiments we offer both the data as presented by the authors, as well as data uniformly processed in-house, enhancing their comparability, as well as the traceability of the methods and reproducibility of the results. Furthermore, we have expanded the tools available for browsing and visualization across and within datasets. We include comparisons against previously existing knowledge in RegulonDB from classic experiments, a nucleotide-resolution genome viewer, and an interface that enables users to browse datasets by querying their metadata. A particular effort was made to automatically extract detailed experimental growth conditions by implementing an assisted curation strategy applying Natural language processing and machine learning. We provide summaries with the total number of interactions found in each experiment, as well as tools to identify common results among different experiments. This is a long-awaited resource to make use of such wealth of knowledge and advance our understanding of the biology of the model bacterium E. coli K-12.

Lab experience with seafood control at the undergraduate level: Cephalopods as a case study.

The correct labeling of seafood is important to protect nature and the rights of consumers. Given the certainty that the resources of the sea are not inexhaustible, only strict regulations and the implementation of sustainable fishing systems and reliable and traceable marketing systems can help ensure the long-term sustainability of fishery resources. Detecting mislabeling and seafood fraud is a useful resource for improving students' motivation and developing active learning methodologies in higher education. In the present study, we have proposed to the students a lab exercise consisting of exploring 25 different commercial cephalopod products from three major European supermarkets by using DNA barcoding and analyzing the results under the framework of EU and Spanish regulations. The problem is connected with the last theme (traceability) of the Conservation Genetics and Breeding course with the aim of providing students with a practical research lab experience about a real problem before going deeper into more theoretical contents. In this way, they can use the knowledge and the skills they acquired previously to better comprehend and think critically about the problem. Findings from students' answers to a survey revealed that the use of this approach generates useful information for communities, increases curiosity and feelings of benefit, and leads to high levels of satisfaction with lab practices compared with those in other courses. In conclusion, lab exercises focused on seafood control, in addition to being viable, can be used as a tool in classes to improve students' commitment to higher education.

Dropout and transfer paths: What are the risky profiles when analyzing university persistence with machine learning techniques?

University dropout is a growing problem with considerable academic, social and economic consequences. Conclusions and limitations of previous studies highlight the difficulty of analyzing the phenomenon from a broad perspective and with bigger data sets. This paper proposes a new, machine-learning based method, able to examine the problem using a holistic approach. Advantages of this method include the lack of strong distribution hypothesis, the capacity for handling bigger data sets and the interpretability of the results. Results are consistent with previous research, showing the influence of personal and contextual variables and the importance of academic performance in the first year, but other factors are also highlighted with this model, such as the importance of dedication (part or full time), and the vulnerability of the students with respect to their age. Additionally, a comprehensive graphic output is included to make it easier to interpret the discovered rules.

Information sources used by high school students in the college degree choice.

INTRODUCTION: Searching for information is a necessary step for young people to decide what to study and prevent school drop-out. The aim of this study is to identify the main sources of information used by students in choosing a university career and to assess the degree of usefulness of these sources. METHOD: A new measuring instrument to assess the use and usefulness of the information sources used in choosing university studies was developed. 2,005 high school students aged 17 to 24 (M = 17.56, SD = .77) participated in the study, representing 44.95 % of the total of school centers of the Principality of Asturias (Spain). RESULTS: The new instrument has adequate psychometric properties and shows that the information from parents and web pages by universities are the most used and most useful information sources for pre-university students. CONCLUSIONS: Obtaining this type of information is very important, as it encourages investing in those activities or resources that are important for pre-university students.

Washback Effect of University Entrance exams in Applied Mathematics to Social Sciences.

Curricular issues of subject Applied Mathematics to Social Sciences are studied in relation to university entrance exams performed in several Spanish regions between 2009-2014. By using quantitative and qualitative analyses, it has been studied how these exams align with curriculum and how they produce a washback on curriculum and teachers' work. Additionally, one questionnaire about teachers' practices has been performed, in order to find out how the exams are influencing teaching methodology development. Main results obtained show that evaluation is producing a bias on the official curriculum, substantially simplifying the specific orientation that should guide applied mathematics. Furthermore, teachers' practices are influenced by the exams, and they usually approach their teaching methodology to the frequent types of exams. Also, slight differences among the teachers lead to distinguish two behavioral subgroups. Results can also be useful in an international context, because of the importance of standardized exit exams in OECD countries.