The proliferation of digital services has led to an increasing demand for secure and reliable digital identity verification, resulting in the development of national digital identity (NDI) systems. These systems provide individuals with a trusted method of verifying their online identity, a necessary prerequisite for accessing a wide range of services, such as banking, healthcare and government services. This review paper takes an in-depth look at the evolution of NDI systems and the advanced technologies that have improved their security and reliability. It looks at the notable NDI systems and digital identity programmes that have been introduced in different countries and analyses both their successes and limitations. In addition, the paper examines emerging technologies such as blockchain and their potential impact on NDI systems. Based on the assessment of these systems and technologies, practical recommendations and best practises are provided for the future development and implementation of NDI systems in other countries.
Evaluation of the questions’ level of complexity for the statistical course was proposed using the revised version of Bloom’s taxonomy. The use of Bloom's taxonomy in statistical examination papers allows the degree of difficulty to be pseudo-objectively assessed. Well-constructed questions in the final examination will help in measuring students' abilities based on comprehensive cognitive skills. Therefore, this study used Rasch Model to evaluate the quality and reliability of final exam questions for probability and statistics course. According to research findings, five out of 30 questions are considered as misfit items. It is therefore recommended that these items be removed or rephrased to better suit the students’ ability level in a course. Whereas, nine questions have significant differences between taxonomy level and Rasch level that require further analysis. Overall, students view the set of exam questions as simple due to the unavailability of difficult items. Based on this result, it is suggested that the exam questions should undergo verification process from the expert and students should be exposed early to various types of questions with different level of difficulty.
Articles you may be interested inA fast and accurate model for forecasting wind speed and solar radiation time series based on extreme learning machines and principal components analysis J. Renewable Sustainable Energy 6, 013114 (2014); 10.1063/1.4862488How bootstrap can help in forecasting time series with more than one seasonal pattern AIP Conf.Abstract. The Employment Injury Scheme (EIS) provides protection to employees who are injured due to accidents whilst working, commuting from home to the work place or during employee takes a break during an authorized recess time or while travelling that is related with his work. The main purpose of this study is to forecast value on claims amount of EIS for the year 2011 until 2015 by using appropriate models. These models were tested on the actual EIS data from year 1972 until year 2010. Three different forecasting models are chosen for comparisons. These are the Naïve with Trend Model, Average Percent Change Model and Double Exponential Smoothing Model. The best model is selected based on the smallest value of error measures using the Mean Squared Error (MSE) and Mean Absolute Percentage Error (MAPE). From the result, the best model that best fit the forecast for the EIS is the Average Percent Change Model. Furthermore, the result also shows the claims amount of EIS for the year 2011 to year 2015 continue to trend upwards from year 2010.
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