Yoxas/statistical_literacy huggingface dataset:
High-throughput biology presents unique opportunities and challenges for dermatological research. Drawing on a small handful of exemplary studies, we review some of the major lessons of these new technologies. We caution against several common errors and introduce helpful statistical concepts that may be unfamiliar to researchers without experience in bioinformatics. We recommend specific software tools that can aid dermatologists at varying levels of computational literacy, including platforms with command line and graphical user interfaces. The future of dermatology lies in integrative research, in which clinicians, laboratory scientists, and data analysts come together to plan, execute, and publish their work in open forums that promote critical discussion and reproducibility. In this article, we offer guidelines that we hope will steer researchers toward best practices for this new and dynamic era of data intensive dermatology.
High-throughput phenotyping brings new opportunities for detailed genebank accessions characterization based on image-processing techniques and data analysis using machine learning algorithms. Our work proposes to improve the characterization processes of bean and peanut accessions in the CIAT genebank through the identification of phenomic descriptors comparable to classical descriptors including methodology integration into the genebank workflow. To cope with these goals morphometrics and colorimetry traits of 14 bean and 16 forage peanut accessions were determined and compared to the classical International Board for Plant Genetic Resources (IBPGR) descriptors. Descriptors discriminating most accessions were identified using a random forest algorithm. The most-valuable classification descriptors for peanuts were 100-seed weight and days to flowering, and for beans, days to flowering and primary seed color. The combination of phenomic and classical descriptors increased the accuracy of the classification of Phaseolus and Arachis accessions. Functional diversity indices are recommended to genebank curators to evaluate phenotypic variability to identify accessions with unique traits or identify accessions that represent the greatest phenotypic variation of the species (functional agrobiodiversity collections). The artificial intelligence algorithms are capable of characterizing accessions which reduces costs generated by additional phenotyping. Even though deep analysis of data requires new skills, associating genetic, morphological and ecogeographic diversity is giving us an opportunity to establish unique functional agrobiodiversity collections with new potential traits.
High-value care is providing high quality care at low cost; we sought to define hospital value and identify the characteristics of hospitals which provide high-value care. Retrospective observational study. Acute care hospitals in the USA. All Medicare beneficiaries with claims included in Center for Medicare & Medicaid Services Overall Star Ratings or in publicly available Medicare spending per beneficiary data. Our primary outcome was value defined as the difference between Star Ratings quality score and Medicare spending; the secondary outcome was classification as a 4 or 5 star hospital with lowest quintile Medicare spending ('high value') or 1 or 2 star hospital with highest quintile spending ('low value'). Two thousand nine hundred and fourteen hospitals had both quality and spending data, and were included. The value score had a mean (SD) of 0.58 (1.79). A total of 286 hospitals were classified as high value; these represented 28.6% of 999 4 and 5 star hospitals and 46.8% of 611 low cost hospitals. A total of 258 hospitals were classified as low value; these represented 26.6% of 970 1 and 2 star hospitals and 49.3% of 523 high cost hospitals. In regression models ownership, non-teaching status, beds, urbanity, nurse to bed ratio, percentage of dual eligible Medicare patients and percentage of disproportionate share hospital payments were associated with the primary value score. There are high quality hospitals that are not high value, and a number of factors are strongly associated with being low or high value. These findings can inform efforts of policymakers and hospitals to increase the value of care.
Higher education has always been the top priority of the country and society. With the gradual completion of the Chinese curriculum system, in addition to some subject knowledge, the education on ideology, morality, and quality has also become more and more perfect. Moral education in colleges and universities is an example of this. However, current moral education instruction in colleges and universities is still based on examination-oriented education, and students have not been exposed to the culture deeply. As a result, the goal of this study is to strengthen traditional culture's function in moral education instruction in colleges and universities, as well as conduct research on its application value. In response to this, this paper designs an embedded moral education network teaching platform, which focuses on increasing the importance of the role of administrators, and is responsible for collecting statistics of traditional culture resources and applying them to teaching. The education for traditional culture also traces its origins and provides suggestions for the new era with reference to historical moral education research. The results of this paper believe that, for the response time of the system, in the campus network environment, the response time is about 3 s, the minimum value is 2.8 s, and the maximum value is also 3.2 s. In an ordinary network environment, the response time is also within 3.8 s. This demonstrates that the approach proposed in this research is efficient and capable of meeting the needs of moral education instruction in colleges and universities.
Higher education institutions (HEIs) are adopting sustainable development (SD) in their strategies for the future. The roadmap by UNESCO is the path to follow to reach success. The approach is different for every HEI, thus the objective of this paper is to analyze the current state of education for sustainable development activities provided by HEIs through the eyes of the academic community (responders category: professors, researchers, associate professors). The method to conduct the study was an interview that had 40 enclosed questions and a free part at the end where the responders could bring additional information to the study if they considered it necessary. All the interviews were transcribed and given a code (e.g., RHEI1, RHEI 29) in order to perform the analysis using descriptive statistics with the help of the program MS Office EXCEL. The results showed some areas where the activities provided by HEIs need improvement and also revealed promising aspects through partnerships. Making the values of SD known to the academic and local community will help fulfill the true potential for change and future development. Moreover, the analysis showed the need to educate educators and improve their digital skills and teaching methods/techniques in order to achieve sustainable development. Another result revealed the need for improvements in HEI curricula that will contribute to gaining those skills/abilities that emerging jobs should have.
Higher education institutions are adapting and innovating like never before to provide highly individualized learning environments for both traditional and non-traditional students. This seismic upheaval in the higher education landscape is being observed across the world. The present study aimed to evaluate the effectiveness of a blended learning approach on nursing students' self-directed learning readiness. This study is a quasi-experimental approach in which a non-equivalent control group was used in a post-test design. A comparison was carried out with two separate semester cohort students representing the control and intervention groups which had 24 and 30 students, respectively. This study included first-year nursing students that enrolled in a course called "Anatomy and Physiology" course of nursing education at a private university. The control group received all their teaching face-to-face, and the intervention group used information technology and prescribed activities in their online e-book. The self-directed learning readiness (SDLR) tool measures the learners' readiness in self-directed learning in both groups. This scale comprises three subscales which are "self-management," "desire for learning," and "self-control." An independent-samples t-test was conducted to compare self-directed learning readiness in the control and intervention groups. Data were analyzed using IBM SPSS Statistics 25 software to measure the independent t-test. The self-directed readiness scores were significantly higher in the intervention group with P = 0.019. The intervention group showed a higher mean value on the subscales of self-management and self-control, which demonstrated a significant difference with P values of 0.018 and 0.028, respectively. The subscale desire for learning was insignificant with a P value of 0.166. This study concluded that the overall results demonstrate that incorporating blended learning using e-books for anatomy and physiology courses in nursing education can contribute to students' readiness for self-directed learning. Specifically, the blended learning teaching and learning strategy had a positive impact on nursing students' capacity for self-management and self-control.
Higher education institutions are promoting the adoption of innovative methodologies and instructional approaches to engage and promote personalized learning paths to their students. Several strategies based on gamification, artificial intelligence, and data mining are adopted to create an interactive educational setting centred around students. Within this personalized learning environment, there is a notable boost in student engagement and enhanced educational outcomes. The MathE platform, an online educational system introduced in 2019, is specifically crafted to support students tackling difficulties in comprehending higher-education-level mathematics or those aspiring to deepen their understanding of diverse mathematical topics - all at their own pace. The MathE platform provides multiple-choice questions, categorized under topics and subtopics, aligning with the content taught in higher education courses. Accessible to students worldwide, the platform enables them to train their mathematical skills through these resources. When the students log in to the training area of the platform, they choose a topic to study and specify whether they prefer basic or advanced questions. The platform then selects a set of seven multiple-choice questions from the available ones under the chosen topic and generates a test for the student. After completing and submitting the test, the answers are recorded and stored on the platform. This paper describes the data stored in the MathE platform, focusing on the 9546 answers to 833 questions, provided by 372 students from 8 countries who use the platform to practice their skills using the questions (and other resources) available on the platform. The information in this paper will help research about active learning tools to support the improvement of future education, especially at higher educational level. Furthermore, these data are valuable for understanding student learning patterns, assessing platform efficacy, gaining a global perspective on mathematics education, and contributing to the advancement of active learning tools for higher education.
Higher education institutions are under increasing pressure to respond to societal needs which has in turn led to changes in the type of knowledge, competencies, and skills required from learners. Assessment of student learning outcomes is the most powerful educational tool for guiding effective learning. In Ethiopia, studies are scarce on assessment practices of learning outcomes of postgraduate students in biomedical and pharmaceutical sciences. This study investigated the assessment practices of learning outcomes of postgraduate students pursuing studies in biomedical and pharmaceutical sciences at the College of Health Sciences of Addis Ababa University. A quantitative cross-sectional study was conducted using structured questionnaires administered to postgraduate students and teaching faculty members in 13 MSc programs in biomedical and pharmaceutical sciences at the College of Health Sciences of Addis Ababa University. About 300 postgraduate and teaching faculty members were recruited with purposive sampling. The data collected included assessment methods, types of test items, and student preferences on assessment formats. Data were analyzed using quantitative approaches, descriptive statistics, and parametric tests. The study indicated that several assessment strategies and test items were practiced without a significant difference across fields of study. Regular attendance, oral questioning, quiz, group and individual assignments, seminar presentations, mid-term tests, and final written examination were commonly practiced assessment formats, while short question and long question essays were the most commonly used test items. However, students were not commonly assessed for skills and attitude. The students indicated they mostly preferred short essay questions, followed by practical-based examinations, long essay questions, and oral examination. The study identified several challenges to continuous assessment. Practice of assessing students' learning outcomes involves multiple methods focusing on assessing mainly knowledge; however, the assessment of skills appears inadequate, and several challenges appear to be hindering implementation of continuous assessment.
Higher education is one of the types of education most influenced by digital technologies. This situation, in educational contexts of quality and equity, presents different advantages but, at the same time, also many challenges. One of them is the use of ICT to support students with disabilities. In this line, the main objective of this study is to evaluate an instrument to measure the level of training and knowledge of university teachers in Spain concerning the application of ICT as support for students with disabilities. For the validation of content, the technique of "expert judgement" was used, applying a process of expert selection called "Expert Competence Coefficient" or "K Coefficient". The instrument's reliability index was obtained through two statistics, Cronbach's alpha and McDonald's Omega. From the results obtained, it is confirmed that the questionnaire under study is an instrument with evidence of validity and reliability that allows us to diagnose, among university teaching staff, sub-dimensions of special relevance to find out the level of training and knowledge they have about ICT and students with disabilities.
Higher education students are frequently required to assess lecturers with a convenient, fast, and anonymous learning management system. Following the coronavirus disease 2019 (COVID-19) pandemic outbreak, Universiti Teknologi MARA Malaysia (UiTM) adopted a remote teaching and learning approach. This study examined how lecturers' professionalism, course impression, and facilitating conditions at UiTM affected undergraduate and graduate students' remote learning pre- and mid-pandemic. The higher prediction accuracy of the model demonstrated that students' remote learning activities were highly related to lecturers' professionalism, course impression, and facilitating conditions. The structural model demonstrated that the t-statistics of all measurement variables were significant at 1%. The strongest predictor of students' enjoyment of remote learning pre- and mid-pandemic was lecturers' professionalism. In the importance-performance matrix, lecturers' professionalism was in the quadrant for 'keep up the good work'. Facilitating conditions and course impression did not require further improvement even during the pandemic. The influence of remote learning was demonstrated in the students' graduation rates and grades. The results also presented theoretical and practical implications for the UiTM hybrid learning plan post-pandemic.
Higher plants, as autotrophic organisms, are effective sources of molecules. They hold great promise for metabolic engineering, but the behavior of plant metabolism at the network level is still incompletely described. Although structural models (stoichiometry matrices) and pathway databases are extremely useful, they cannot describe the complexity of the metabolic context, and new tools are required to visually represent integrated biocurated knowledge for use by both humans and computers. Here, we describe ChloroKB, a Web application (http://chlorokb.fr/) for visual exploration and analysis of the Arabidopsis (Arabidopsis thaliana) metabolic network in the chloroplast and related cellular pathways. The network was manually reconstructed through extensive biocuration to provide transparent traceability of experimental data. Proteins and metabolites were placed in their biological context (spatial distribution within cells, connectivity in the network, participation in supramolecular complexes, and regulatory interactions) using CellDesigner software. The network contains 1,147 reviewed proteins (559 localized exclusively in plastids, 68 in at least one additional compartment, and 520 outside the plastid), 122 proteins awaiting biochemical/genetic characterization, and 228 proteins for which genes have not yet been identified. The visual presentation is intuitive and browsing is fluid, providing instant access to the graphical representation of integrated processes and to a wealth of refined qualitative and quantitative data. ChloroKB will be a significant support for structural and quantitative kinetic modeling, for biological reasoning, when comparing novel data with established knowledge, for computer analyses, and for educational purposes. ChloroKB will be enhanced by continuous updates following contributions from plant researchers.
Higher rates of Smoking among university students have been reported in various studies. On the other hand, health literacy (HL) can improve health behaviors. In fact, identifying factors affecting the adoption of smoking preventive behaviors such as HL can help prevent and reduce the prevalence of smoking among people. The aim of this study was to identify the relationship between different levels of HL and adoption of smoking preventive behaviors among university student in 2016. This was a cross-sectional descriptive study. Three hundred and forty-seven dormitory students of Shahid Beheshti University of Medical Sciences in Iran were selected through single-stage cluster sampling for the study. Data were collected using a measure of HL (the HL inventory for adults-HELIA) and a designed questionnaire to assess the adoption of smoking preventive behaviors. The data were analyzed using SPSS software version. 16 and descriptive statistical and Logistic regression test. The mean (SD) of the score for adoption of smoking preventive behaviors and HL were 45.91 (12.99) and 70.52 (14.12) out of 100, respectively. The results showed that the adoption of smoking preventive behaviors had significant relationship with variables such as HL, gender, father's education and not smoking (P < 0.05). Less adoption of smoking preventive behaviors was seen in students with lower levels of HL, female students, students with illiterate fathers and smokers. Therefore, it seems essential to take these factors into consideration in designing preventive programs for smoking in target groups.
Higher-order thinking (HOT) is widely recognized as an essential objective of health profession education (HPE). Based on Lipman's three-dimensional model of thinking, we investigated strategies for the development of HOT including critical thinking (CT), creative thinking, and caring thinking in HPE in three consecutive studies. Fostering students' CT is regarded as an outcome of HPE. However, there is the limited level of consensus on educational interventions for CT development. In view of some of the controversies surrounding the development of CT skills and dispositions in HPE, the aim of this study was to determine educational interventions affecting CT development in HPE. This study employed the best-fit framework synthesis design. The frameworks recommended by Abrami et al. were used as a basis for the synthesis. The priori themes were extracted from the selected best-fit frameworks. Then, Google Scholar, PubMed, SID, and ProQuest databases were searched for the literature related to the development of CT skills and dispositions in HPE students. Derived data from the HPE literature were coded against the priori themes, extracted from the best-fit frameworks. Interpretation and restructuring of the new themes derived from HPE literature, and the preexisting priori themes resulted in the final framework of the interventions affecting CT development in HPE students. The themes extracted from the HPE studies (including reflection, discussion, simulation, role-playing, questioning, and explicit expression of CT goals in curriculum) were similar to the a priori themes derived from the studies by Abrami et al. The new themes of experiential learning, art-based learning, argument mapping, concept mapping, and creating appropriate educational atmosphere were obtained by constant comparison of the data among the studies. The comprehensive framework of CT development methods provides a toolkit for medical educators. According to the results of the current study, the mixed approach, where CT is taught as an independent track, along with the discipline-specific CT development, seems to be more effective, compared to the immersion approach. Creating learning moments in the context of practice through experiential learning is noteworthy in the development of CT skills and dispositions. Further research is needed to evaluate the efficacy of the newly developed strategies, such as art-based learning and concept mapping.