Ten years after the announcement of the "rise of the super experiment" at Educational Data Mining 2012, challenges to implementing "internet scale" educational experiments often persist for educational technology providers, especially when they seek to test substantive instructional interventions. Studies that deploy and test…

This article examines the social utility of the concept, 'data literacy'. Recent developments in the processes of datafication challenge long-held assumptions about privacy and the role of both state and commerce in individual lives. Typically, these have been addressed through: "regulatory" legal constraints underwritten by the nation…

This study examines the use of data analytics to evaluate students' behaviours during their participation in an online collaborative learning environment called SkyApp. To visualise the learning traits of engagement, emotion and motivation, students' inputs and activity data were captured and quantified for analysis. Experiments were first carried…

The purpose of study was gain insight into pre-service teachers' experiences in using classroom data to make learning and teaching decisions. The qualitative study is based on the reflections and recommendations of three pre-service teachers' that participated in a data-driven decision-making intervention whilst on an immersive 10-week…

The article shares collaborating educators (authors') experiences in supporting a group of student-teachers' interventions to improve learning practices as part of an action research course in a teacher education setting. The authors engaged in a series of reflective discussions in making sense of and improving the course process. Facilitation and…

With the advent of Precision Teaching more than 50 years ago, researchers and practitioners began to examine how to use K-12 students' academic data to guide instructional decisions. Although the field has advanced with the use of curriculum-based measurement and data-driven decision rules for reading and math, the same is not true in the area of…

Student success efficacy studies are aimed at assessing instructional practices and learning environments by evaluating the success of and characterizing student subgroups that may benefit from such modalities. We propose an ensemble learning approach to perform these analytics tasks with specific focus on estimating individualized treatment…

Higher education faces the challenge of high student attrition, which is especially disconcerting if associated with low participation rates, as is the case in South Africa. Recently, the use of learning analytics has increased, enabling institutions to make data-informed decisions to improve teaching, learning, and student success. Most of the…

Tools for automatic grading programming assignments, also known as Online Judges, have been widely used to support computer science (CS) courses. Nevertheless, few studies have used these tools to acquire and analyse interaction data to better understand the students' performance and behaviours, often due to data availability or inadequate…

Basil Bernstein wrote extensively about official educational knowledge, pedagogic recontextualisation and pedagogic identities. However, his theoretical oeuvre tended to focus on the textual rather than the affective aspects of policy recontextualisation. In addition, his work on the realisation of official pedagogic identity positions at the…

Data-based decision-making has the potential to increase student achievement results. Data-based decision-making can be defined as teachers' systematic analysis of data sources in order to study and adapt their educational practices for the purpose of maximizing learning results. Teachers must apply the findings from their data use to their…

Background: This work is based on the idea that young children benefit from early introduction of scientific concepts. Few researches describe didactical strategies focusing on physics understanding for young children and analyse their effectiveness in standard classroom environments. Purpose: The aim is to identify whether didactical strategies…

Data analysis inherently requires problem solving, yet it is the most understudied mathematical skill for individuals with extensive support needs. The current study taught elementary students with extensive support needs (i.e., autism and intellectual disability) to solve math word problems requiring analysis of scaled pictographs through…

Current preservice teacher education practice related to data use has been deemed inadequate, in that it is unevenly distributed and often superficial. In response, this article describes a course-based classroom assessment data-literacy experience for preservice elementary teachers. Grounded in extant theory and research concerning data literacy…

Collaborative problem solving in computer-supported environments is of critical importance to the modern workforce. Coworkers or collaborators must be able to co-create and navigate a shared problem space using discourse and non-verbal cues. Analyzing this discourse can give insights into how consensus is reached and can estimate the depth of…