This paper presents an analysis of learning analytics practices which aimed to achieve personalised learning. It addresses the need for a systematic analysis of the increasing amount of practices of learning analytics which are targeted at personalised learning. The paper summarises and highlights the characteristics and trends in relevant…

This book explores how stories can be used as 'data' that prefigure and make possible the numerous permutations of life that comprise existence, and examines how stories can be reconfigured to transform that existence into something 'other'. It uses varied theoretical and critical frameworks such as autoethnography and posthumanism with which to…

Many students persistently misinterpret histograms. Literature suggests that having students solve dotplot items may prepare for interpreting histograms, as interpreting dotplots can help students realize that the statistical variable is presented on the horizontal axis. In this study, we explore a special case of this suggestion, namely, how…

In this study, technology-enhanced statistical problem-solving tasks designed by pre-service teachers (PTs) were examined. The PTs designed 28 tasks. The designed tasks were analyzed within the context of the Considerations for Design and Implementation of Statistics Tasks (C-DIST) components. It was revealed that the tasks were mostly designed…

As data becomes an integral part of our lives, the general public faces the increasing need to actively engage with data to participate in daily activities, support personal goals, and understand social issues. Formal data science training, however, remains out of reach for most people and does not cater to their diverse needs related to data.…

The efficiency of universities, which have a network structure of production process, is an essential component of performance measurement in education. However, most previous studies use traditional Data Envelopment Analysis (DEA), which disregards the network structure of the production process in universities. This study adopts a two-stage…

Principals at Hunter School District, a pseudonym, lacked capacity for using data, a reflection of the district's lack of a culture of data-driven decision-making. HSD was located in New York City, with 23 schools serving 11,600 students; students were 90% Black or Latino with 90% coming from low-income families and 20% living in temporary…

This study aimed to discover the perspectives and experiences of elementary school teachers in rural southeast Tennessee regarding their collaborative efforts to effectively implement data-driven instruction for individual student success. The research problem is that the current collaboration efforts for teachers to implement data-driven…

The Civil Rights Data Collection (CRDC) is a mandatory survey of all public schools and school districts in the 50 states, Washington, D.C., and the Commonwealth of Puerto Rico. Since the 2009-10 CRDC, schools and school districts have reported the number of students who were referred to law enforcement and arrested at the nation's public schools.…

The purpose of this study was to investigate the effectiveness of four different models (bifactor, CTC(M-1), CTCU and unidimensional) as to optimal model selection when the wording effect associated with negatively worded items was present. A Monte Carlo simulation study was conducted to compare model-data fit and accuracy in parameter estimates…

Over recent years, the sharing of personal data among students is uncontrolled, especially on the social media networks, resulting in widespread data intrusions that compromise their privacy and confidentiality. Against this backdrop, this study was conducted to identify the level of knowledge of personal data protection among students. This…

In this study, it was aimed to examine the effect of missing data in different patterns and sizes on test equating methods under the NEAT design for different factors. For this purpose, as part of this study, factors such as sample size, average difficulty level difference between the test forms, difference between the ability distribution,…

In order to produce the most reliable syntheses of the effectiveness of educational interventions, systematic reviews need to adhere to rigorous methodological standards. This meta-review investigated risk of bias occurring while conducting a systematic review and the presence of open science practices like data sharing and reproducibility of the…

Data mining (DM) is an in-depth approach to data analysis by mining useful information from large amounts of data, and this technique is now being used in an increasing number of fields. In this paper, the authors present the design of a real-time data analysis system for sports training based on DM technology and use the corresponding mining…

Background: Science education should encompass enculturation in science which implies performing scientific practices such as use of data and modelling, in authentic contexts like the field. Purpose: This work aims to determine how preservice elementary teachers (PETs) use data obtained in the field, and how these data contribute to the process of…