The aim of this study was to investigate the ways in which textile materials and techniques are expressed in contemporary art in Finland. The first phase of data collection was to identify a population of Finnish artists who use textile craft-based forms in their art and who produce their works themselves. After that, six discretionary selected…

The assessment and understanding of students' ideas in discourse have often been a difficult problem for teachers to tackle. Recent innovations and technologies such as text mining can provide a partial solution by generating an estimated count of important keywords which are representative of ideas within discourse. However, investigating idea…

Prompted by discovering a paper written in 1980 which described a process of 'ethnography by proxy', I revisit this concept in the light of two research projects: a workplace study of an electronics company conducted in the early 1990s and a later home-based study of young children's encounters with toys and technology. The paper defines…

There is an increasing body of research which examines the reliability and validity of different modes of network measurement with most studies focusing on the classical paper or digital network questionnaires. Visual methods of data collection, in which interviewees draw their ego-centered network in a pictorial representation, still live a kind…

Several high-profile incidents of violence at U.S. schools have, understandably, raised concerns about the safety of students while at school. Just one incident of violence causes significant harm. In light of this, it is important to examine commonly held beliefs about school safety and violence because they sometimes reflect a misperception or…

Outcome-driven data literacy is a relatively new discipline in the field of K-12 education. With the exception of a few researchers, a handful of teacher training organizations, and practices observed in some public schools, there is little guidance for how teacher training organizations interested in developing outcome-driven, data-literate…

Between 2012 and 2022, the literacy proficiency of the working-age population in the countries that took part in the Survey of Adult Skills is set to improve, mainly driven by the relatively low proficiency of the cohorts who will reach 65 between now and 2022 and the much higher literacy skills among the incoming age group. The participating…

"The Realities of Research Data Management" is a series of four reports looking at the context, influences and choices research universities face in building or acquiring research data management (RDM) capacity. The findings are derived from detailed case studies of four research universities, hailing from four distinct national…

As the field of education continues to grow, new methods and approaches to teaching are being developed with the goal of improving students' understanding of concepts. While research exists showing positive effects for particular teaching methods in small case studies, generalizations to larger populations of students, which are needed to…

Data is flexible in that it is molded by not only the features and variables available to a researcher for analysis and interpretation, but also by how those features and variables are recorded and processed prior to evaluation. "Big Data" from online learning platforms and intelligent tutoring systems is no different. The work presented…

Existing personalized learning systems (PLSs) have primarily focused on providing learning analytics using data from learners. In this paper, we extend the capability of current PLSs by incorporating data from instructors. We propose a latent factor model that analyzes instructors' preferences in explicitly "excluding" particular…

BKT and other classical student models are designed for binary environments where actions are either correct or incorrect. These models face limitations in open-ended and data-driven environments where actions may be correct but non-ideal or where there may even be degrees of error. In this paper we present BKT-SR and RKT-SR: extensions of the…

The last 20 years has seen an uptick in research on missing data problems, and most software applications now implement one or more sophisticated missing data handling routines (e.g., multiple imputation or maximum likelihood estimation). Despite their superior statistical properties (e.g., less stringent assumptions, greater accuracy and power),…

Recent federal policy changes have placed new requirements on states to demonstrate and document their efforts to improve access to high-quality early care and education (ECE), and have made clear the urgent need for a shared understanding of this concept. This guidebook was developed to address the need for developing a common understanding and…

Purpose: Novice researchers experience difficulties in analysing qualitative data. To develop the skills necessary for qualitative data analysis, theoretical manuals are often insufficient. Supervisors supporting students in analysing qualitative data stress the need for practical guidance, including exercises and feedback. The purpose of this…