Egocentric networks represent a popular research design for network research. However, to what extent and under what conditions egocentric network centrality can serve as reasonable substitutes for their sociocentric counterparts are important questions to study. The answers to these questions are uncertain simply because of the large variety of…

We propose a new method for analyzing and visualizing information on a large collection of personal networks to uncover the socio-centric structure of relationships among aggregated actors that we clustered into categories. The network of categories identifies the links between groups of sampled ego actors sharing a given attribute (e.g.,…

The interest in Data Envelopment Analysis (DEA) has grown since its first put forward in 1978. In response to the overwhelming interest, systematic literature reviews, as well as bibliometric studies, have been performed in describing the state-of-the-art and offering quantitative outlines with regard to the high-impact papers on global…

Education has been considered a cornerstone for human and economic development. Although there is a national educational strategy in most countries, various implementations are at the state level. This paper studies academic efficiency at the primary and secondary levels and the human development dimensions -- long and healthy life, being…

In this paper, a key node mining algorithm of entropy-CRITIC combined weighted GRA-TOPSIS method is proposed, which is based on the network structure features. First, the method obtained multi-dimensional data of students' identities, seating relationships, social relationships, and so on to build a database. Then, the seating similarity among…

Despite the positive claims on the pedagogical use of social annotation and online collaborative writing tools discussed in the literature, most of the findings are derived from interviews or self-reported survey data. Very few studies probed deep into the learning processes and examined students' digital traces and the artefacts they…

The thriving developer community has a significant impact on the widespread use of R software. To better understand this community, we conducted a study analyzing all R packages available on CRAN. We identified the most popular topics of R packages by text mining the package descriptions. Additionally, using network centrality measures, we…

Social Network Analysis (SNA) is a statistical method used to analyze the social structure and interactions among individuals within a network. SNA is used extensively in a number of disciplines such as sociology, geography, and communications research. However, the use of SNA by practitioners and researchers in assessment and evaluation is much…

Text mining techniques have become popular in many disciplines in the era of big data. Author profiling analysis, a method of text mining, is useful for identifying the intellectual structures of research fields and the latest research topics that did not appear from author co-citation analysis. This study analyzed the changing intellectual…

Background: Data visualizations transform data into visual representations such as graphs, diagrams, charts and so forth, and enable inquiries and decision-making in many professional fields, as well as in public and economic areas. How students' data visualization literacy (DVL), including constructing, comprehending, and utilizing adequate data…

Humans have always been lured by the idea that they can use data to understand a phenomenon and make predictions about it. Learning analytics, in this sense, promise to understand and optimize learning and the environments in which it occurs by collecting data from learners and learning contexts. In this regard, this study systematically examines…

The development of digital technologies has created a market need for specialists working with the big data that is necessary for making management decisions. This study aims to identify the skills structure of the data analyst profession (DAP) in Russia. The authors used a program code written in Python to examine relevant vacancies extracted…

Students across disciplines struggle with sensemaking when they are faced with the need to understand and analyze massive amounts of information. This is particularly salient in the disciplines of both history and data science. Our approach to helping students build expertise with complex information leverages activity theory to think about the…

Social network analysis (SNA) consists of a broad set of frameworks and methods to assess how direct and indirect relationships influence individual functioning. Although interest in SNA has steadily increased in the psychological sciences, school psychology has not kept pace. This article provides a general overview of core SNA concepts,…

There has been extensive research using centrality measures in educational settings. One of the most common lines of such research has tested network centrality measures as indicators of success. The increasing interest in centrality measures has been kindled by the proliferation of learning analytics. Previous works have been dominated by…