In this digital ITEMS module, Dr. Jeffrey Harring and Ms. Tessa Johnson introduce the linear mixed effects (LME) model as a flexible general framework for simultaneously modeling continuous repeated measures data with a scientifically defensible function that adequately summarizes both individual change as well as the average response. The module…

Purpose: The purpose of this paper is to set forth a less-costly, more flexible approach to teaching the analysis of international business development opportunities. Design/methodology/approach: The approach capitalizes upon the high-quality business condition metrics, which are necessary to inform the development decision, that have recently…

The purpose of this study was to identify the underlying cognitive attributes used during the design and development of science-based serious educational games. Study methods rely on a modification of cognitive diagnostics, item response theory, and Bayesian estimation with traditional statistical techniques such as factor analysis and model fit…

Computational Thinking (CT) has recently been addressed as one of the key skills for the twenty-first century. Integrating CT into different subject areas of K-12 education is also now widely accepted to improve the quality of instruction. In that sense, it is important to enable educators and researchers to recognize how to integrate…

Statistical investigations, a thread within the statistics strand of the mathematics and statistics learning area (Ministry of Education, 2007), are underpinned by the statistical enquiry cycle. As teachers introduce their students to the statistical enquiry cycle, they are supporting their students to become data detectives, posing and answering…

Primarily methodological in its orientation, this paper offers a presentation of 'research outcomes' in ways that challenge and disrupt commonplace notions of data and analysis. In an attempt to write against the grain of conventional qualitative research practice and to experiment with alternative encounters with data and analysis, I present…

When completing a needs assessment, Extension professionals should include both objective county data and stakeholder input data. Specifically, Extension professionals should identify potential areas of need, source available objective data, source data from relevant county stakeholders, and analyze similarities and differences in objective and…

The theory of practice architectures is a useful theoretical, methodological and analytical tool for educational research. The use of the theory is emerging as germane in early childhood education research. This article explores concepts from the theory as applied in an early childhood education research project. The article focuses on the concept…

To succeed, undergraduate science students need to both acquire knowledge, and learn to apply it effectively. Here a novel 1st year undergraduate module (incorporating blended learning, applied bioinformatic skills and scientific posters) is described and its effectiveness evaluated (quantitatively and qualitatively). The aims were to engage…

In Australia, under the National Assessment Plan, educational accountability testing in literacy and numeracy (NAPLAN) is undertaken with all students in Years 3, 5, 7 and 9 to monitor student achievement and inform policy. However, the extent to which these data have been analysed to report student progress is limited. This article reports a…

By exposing students to the concept of digital agriculture earlier in their lives, they will be able to develop the proper mindset to advance the field further when they enter the professional world. Engaging students in activities such as the one described here, which center on the Grand Engineering Challenges and socially relevant contexts, may…

Understanding and analyzing data is a crucial aspect of quantitative literacy in the 21st century, leading scholars and policy makers to push for more rigorous instruction in this area rooted in statistical investigation. In this study, we examine 144 upper-elementary mathematics lessons on data and statistics topics to assess the extent to which…

To be successful in online education, learners should be able to self-regulate their learning due to the autonomy offered to them. Accurate measurement of learners' self-regulated learning (SRL) in online education is necessary to determine which learners are in need of support and how to best offer support. Trace data is gathered automatically…

The emergence of personalised data technologies such as learning analytics is framed as a solution to manage the needs of higher education student populations that are growing ever more diverse and larger in size. However, the current approach to learning analytics presents tensions between increasing student agency in making learning-related…

We do not learn through experiences alone; we learn by thinking about our experiences. But after disappointing exam results, students can reflect on their performance in unproductive ways, circulating scripted beliefs about why they did poorly: "The professor talks too fast," "The test didn't cover the lectures in class,"…