In the context of higher education's growing significance and the persistence of inequalities in it, the article aims to further develop the understanding of higher education as a public good and to explore its association with social cohesion in a European comparative perspective. It shifts the focus from the content of higher education as a…

Schools are frequently seen as the hubs of the community, providing resources and a gathering place for members of the community. The process of surveying the community in order to identify unique needs within the community, and then intentionally forging partnerships capable of ameliorating the specific needs, are strategies used by community…

The goal of biological sciences is to understand the biomolecular mechanics of living organisms. Proteins serve as the foundation for organisms functional analysis and sequence analysis has shown to be invaluable in answering questions about individual organisms. The first step in any sequence analysis is alignment and it is common that even…

We present an analysis of log data from a semester's use of the OpenDSA eTextbook system with the goal of determining the most difficult course topics in a data structures course. While experienced instructors can identify which topics students most struggle with, this often comes only after much time and effort, and does not provide real-time…

The authors generated data visualizations to compare sections of the library book collection, expenditures in those areas, student enrollment in majors and minors, and number of courses. The visualizations resulting from the entered data provide an excellent starting point for conversations about possible imbalances in the collection and point to…

Data science is a broad, interdisciplinary field concerned with the extraction of knowledge or insights from data, with the classification of data as a core, fundamental task. One of the most persistent challenges faced when performing classification is the class imbalance problem. Class imbalance refers to when the frequency with which each class…

Observers have expressed concern about growing inequality in resources across universities. But are universities really becoming more unequal? We argue that the typical approach of examining endowment growth alone is not sensible. In line with the literature on household inequality, we focus instead on a comprehensive income measure. We find that…

In this paper, we show how data mining algorithms (e.g. Apriori Algorithm (AP) and Collaborative Filtering (CF)) is useful in New Social Network (NSN-AP-CF). "NSN-AP-CF" processes the clusters based on different learning styles. Next, it analyzes the habits and the interests of the users through mining the frequent episodes by the…

In this study, we used a paper-pencil questionnaire to investigate whether teachers, administrators, and parents differed in their preferences and accuracy when interpreting visual data displays for decision making. For the data analysis, we used nonparametric tests due to violations of distributional assumptions for using parametric tests. We…

TIMSS and PIRLS assess representative samples of students at regular intervals, measuring trends in student achievement and student contexts for learning. Because individual students are not tracked over time, analysis of international large-scale assessment data is usually conducted cross-sectionally. Gustafsson (2007) proposed examining the data…

This study investigates the issue of the goodness of fit of different skills assessment models using both synthetic and real data. Synthetic data is generated from the different skills assessment models. The results show wide differences of performances between the skills assessment models over synthetic data sets. The set of relative performances…

This dissertation examines the role of conceptions of data's value in data practices. Based on a study of three small teams of scientists carrying out ecological research at a biological station, my study addresses the following main question: How do scientists conceive of the value of their data, and how do scientists enact conceptions of value…

This article raises important questions about whether the increasing control of early years education through performance data is genuinely a means for school improvement. This composite article, examines the pervasiveness of attainment data in early years education professional activity, its impact on early years teachers' consciousness and…

The present study sought to investigate the family, individual, and dyad-specific contributions to observed cognitive sensitivity during family interactions. Moreover, the influence of cumulative risk on sensitivity at the aforementioned levels of the family was examined. Mothers and 2 children per family were observed interacting in a round robin…

Learning a more distributed representation of the input feature space is a powerful method to boost the performance of a given predictor. Often this is accomplished by partitioning the data into homogeneous groups by clustering so that separate models could be trained on each cluster. Intuitively each such predictor is a better representative of…