Marina Dobrota

A new perspective on the ICT Development Index

Information and Communication Technology (ICT) represents an important structural part of modern society; this is why countries strive for constant progress in ICT and why it draws such significant attention. Bearing this in mind, the main goal of this paper is to present an I-distance methodology that holds a new perspective on the measurement of information development, to compare it to the ICT development index (IDI), and to point out improvements that such methodology provides. IDI combines 11 indicators related to three ICT categories: Access, Use and Skills (by weighting the first two by 40 percent and the third by 20 percent). The approach presented in this study uses the same indicators, synthesizing them into one value. Subsequently, which variables are the most relevant for measuring ICT development level of countries are able to be determined. Consequently, the I-distance method provides useful insight into developing countries and ways that enhance their ranking. The results show that the correlation between the I-distance values and IDI values is very strong, r = 0.961, p < 0.01, which makes I-distance an acceptable measurement method for evaluating countries’ ICT development levels.

A new approach to the QS university ranking using the composite I-distance indicator: Uncertainty and sensitivity analyses

Some major concerns of universities are to provide quality in higher education and enhance global competitiveness, thus ensuring a high global rank and an excellent performance evaluation. This article examines the Quacquarelli Symonds (QS) World University Ranking methodology, pointing to a drawback of using subjective, possibly biased, weightings to build a composite indicator (QS scores). We propose an alternative approach to creating QS scores, which is referred to as the composite I‐distance indicator (CIDI) methodology. The main contribution is the proposal of a composite indicator weights correction based on the CIDI methodology. It leads to the improved stability and reduced uncertainty of the QS ranking system. The CIDI methodology is also applicable to other university rankings by proposing a specific statistical approach to creating a composite indicator.

Student Perception of Moodle Learning Management System: A Satisfaction and Significance Analysis.

This research study addresses differences in student perception of the significance of Moodle learning management system (LMS) quality characteristics and differences in student satisfaction in regard to such characteristics. Therein, it has been proven in this study that male and female students are equally satisfied with Moodle LMS quality characteristics and that there is a difference in the significance that students give to these characteristics. When students were observed in regard to their age and year of study, it was found that these groups assigned different significance levels to quality characteristics and were not equally satisfied with them. It was also found that there is a substantial statistical difference in the significance students gave to quality characteristics and in student satisfaction itself, according to how much time they spent using the Moodle application, which is also noted as one of the most important aspects of the research conducted. A further analysis of the variables demonstrated that the following components of quality characteristics were more important to female students: average waiting time for a response, feedback quality, material thoroughness, material clarity, website user-friendliness, cooperation diversity, and material quantity.

ARWU ranking uncertainty and sensitivity: What if the award factor was Excluded?

The Academic Ranking of World Universities (ARWU) uses six university performance indicators, including “Alumni” and “Awards”—the number of alumni and staff winning Nobel Prizes and Fields Medals. These two indicators raised doubts about the reliability of this ranking method because they are difficult to cope with. Recently, a newsletter was published featuring a reduced ARWU ranking list, leaving out Nobel Prize and Fields Medal indicators: the Alternative Ranking (Excluding Award Factor). We used uncertainty and sensitivity analyses to examine and compare the stability and confidence of the official ARWU ranking and the Alternative Ranking. The results indicate that if the ARWU ranking is reduced to the 4‐indicator Alternative Ranking, it shows greater certainty and stability in ranking universities.

A New Approach to the Evaluation of Countries’ Educational Structure and Development: The European Study

The ranking of higher education institutions, as well as the ranking of countries based on their scientific achievements, draws a significant amount of attention. Nevertheless, the ranking of countries according to their educational structure provides a completely different view. This article introduces a new approach to ranking, proposes certain changes in defining the parameters that should be included in the ranking process, and compares the results to the available Education index. This provides a new perspective on the evaluation of a country’s educational structure, which can speak volumes about its overall educational development.

Shedding the Light on the Stability of University Rankings in the ICT Field

ABSTRACT A global trend nowadays is shifting the attention from the overall university ranking towards the ranking in a particular scientific field: “Ranking by Subject” and/or “Field Ranking”. The objective of the research presented in this paper is the review of the Information and Communication Technologies (ICT) aspect of the universities performance. The major concern of the study is the uncertainty and sensitivity of ICT field ranking, regarding the weighting scheme of a particular ranking methodology. The paper thus examines the ICT field-based section of the Quacquarelli Symonds (QS) and URAP rankings and gives a detailed comparison of the stability of these ranking methods. According to the results, URAP ICT ranking is shown to be more stable than QS ICT ranking, with a lower level of uncertainty and sensitivity to different model assumptions. Moreover, we gave an overview of particular standings of Indian universities in both QS and URAP ICT rankings, tackling the issue of the uncertainty and sensitivity of their positions.

Data Mining Models for Prediction of Customers’ Satisfaction: The CART Analysis

Data mining is a powerful technology with great potential to help companies focus on the most important information in their data warehouses (Fayyad et al., 1996; Xu and Zhang, 2005). Data mining tools can predict future trends and behaviors, allowing businesses to make proactive, knowledge-driven decisions (Sharma et al., 2008). They scan databases for hidden patterns, finding predictive information that experts may miss because it lies outside their expectations. Technologies that have been developed in the area of data mining and knowledge discovery in databases became necessary because the traditional analysis of data has been insufficient for a very long time (Frawley et al., 1991).