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.,…

In the small town of Sitka, Alaska, frequent and often catastrophic landslides threaten residents. One challenge associated with disaster preparedness is access to timely and reliable risk information. As with many small but diverse towns, who or what is a trustworthy source of information is often contested. To help improve landslide…

The purpose of this study is to reveal the status of scientific publications on learning analytics from the past to the present in terms of bibliometric indicators. A total of 659 publications on the subject between the years 2011-2021 were found in the search using keywords after various screening processes. Publications were revealed through…

The importance of learning design in education is widely acknowledged in the literature. Should learners make effective use of opportunities provided in a learning design, especially in online environments, previous studies have shown that they need to have strong skills for self-regulated learning (SRL). The literature, which reports the use of…

Gaining insight into course choices holds significant value for universities, especially those who aim for flexibility in their programs and wish to adapt quickly to changing demands of the job market. However, little emphasis has been put on utilizing the large amount of educational data to understand these course choices. Here, we use network…

The study of teacher development and teaching interaction in physical classrooms has presented research problems, but with the development of classroom observation and video analysis, quantitative and visual analysis of the teaching process has been realized. In order to better understand the teaching models of teachers, this study is devoted to…

This AERA Open special topic concerns the large emerging research area of education data science (EDS). In a narrow sense, EDS applies statistics and computational techniques to educational phenomena and questions. In a broader sense, it is an umbrella for a fleet of new computational techniques being used to identify new forms of data, measures,…

Social Network Analysis (SNA) is a promising yet underutilized tool in the international development field. SNA entails collecting and analyzing data to characterize and visualize social networks, where nodes represent network members and edges connecting nodes represent relationships or exchanges among them. SNA can help both researchers and…

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…

Large-group (n > 8) co-located collaboration has not been adequately studied because it demands different conceptual framings than those used to study small-group collaboration, while also posing pragmatic constraints on data collection. Working within these pragmatic constraints, we use video data to devise an indicator of the current…

Data science has maintained its popularity for about 20 years. This study adopts a bottom-up approach to understand what data science is by analyzing the descriptions of courses offered by the data science programs in the United States. Through topic modeling, 14 topics are identified from the current curricula of 56 data science programs. These…