A matrix method for solving high-order linear difference equations with mixed argument using hybrid legendre and taylor polynomials

A numerical method for solving the higher order linear difference equations with variable coefficients and mixed argument under the mixed conditions is presented. The method is based on the hybrid Legendre and Taylor polynomials. The solution is obtained in terms of Legendre polynomials. IIIustrative examples are included to demonstrate the validity and applicability of the technique.     

Pedagogical approaches for e-assessment with authentication and authorship verification in Higher Education

Checking the identity of students and authorship of their online submissions is a major concern in Higher Education due to the increasing amount of plagiarism and cheating using the Internet. The literature on the effects of e-authentication systems for teaching staff is very limited because it is a novel procedure for them. A considerable gap is to understand teaching staff' views regarding the use of e-authentication instruments and how they impact trust in e-assessment. This mixed-method study examines the concerns and practices of 108 teaching staff who used the TeSLA—Adaptive Trust-based e-Assessment System in six countries: the UK, Spain, the Netherlands, Bulgaria, Finland and Turkey. The findings revealed some technological, organisational and pedagogical issues related to accessibility, security, privacy and e-assessment design and feedback. Recommendations are to provide a FAQ and an audit report with results, to raise awareness about data security and privacy, to develop policies and guidelines about fraud detection and prevention, e-assessment best practices and course team support.     

Utilization of biological variation data in the interpretation of laboratory test results – survey about clinicians’ opinion and knowledge

IntroductionTo interpret test results correctly, understanding of the variations that affect test results is essential. The aim of this study is: 1) to evaluate the clinicians’ knowledge and opinion concerning biological variation (BV), and 2) to investigate if clinicians use BV in the interpretation of test results.Materials and methodsThis study uses a questionnaire comprising open-ended and close-ended questions. Questions were selected from the real-life numerical examples of interpretation of test results, the knowledge about main sources of variations in laboratories and the opinion of clinicians on BV. A total of 399 clinicians were interviewed, and the answers were evaluated using a scoring system ranked from A (clinician has the highest level of knowledge and the ability of using BV data) to D (clinician has no knowledge about variations in laboratory). The results were presented as number (N) and percentage (%).ResultsAltogether, 60.4% of clinicians have knowledge of pre-analytical and analytical variations; but only 3.5% of them have knowledge related to BV. The number of clinicians using BV data or reference change value (RCV) to interpret measurements results was zero, while 79.4% of clinicians accepted that the difference between two measurements results located within the reference interval may be significant.ConclusionsClinicians do not use BV data or tools derived from BV such as RCV to interpret test results. It is recommended that BV should be included in the medical school curriculum, and clinicians should be encouraged to use BV data for safe and valid interpretation of test results.