This paper explores an emerging methodological approach called doppelganger as method. This method uses the idea of a doppelganger or double to explore the social world. It is specifically used to examine datafication, or the increase in the production and use of data and its impact on education. Doppelganger as method begins by locating doubles,…

With the development of the information age, the quality of physical education teaching in universities has become an important goal of teaching reform. Improving the quality of physical education and significantly improving students' physical fitness is one of the development goals of higher education. Therefore, this article proposes an…

This study examined the predictive power of students' demographic characteristics, reading attitudes, school characteristics, and teacher-informed reading activities on three metacognitive reading skills: understanding and remembering, summarizing, and assessing credibility and their influence on 15-year-old students' reading scores. The dataset…

The purpose of this study is to review journal papers on educational big data research published from 2010 to 2018. A total of 143 papers were selected. The papers were characterized based on three dimensions: (a) educational goals; (b) educational problems addressed; and (c) big data analytical techniques used. A qualitative content analysis…

Despite a growing focus on access to and use of emergent literacy assessment in early childhood, little is known about early childhood teachers' data practices and their associations with children's emergent literacy skills. A questionnaire was used to confirm and elaborate findings from prior qualitative work (Schachter & Piasta, 2022)…

The COVID-19 pandemic uniquely affected nearly all the subject matter in a typical principles of macroeconomics class. Fluctuations in the basic macroeconomic data in the COVID era were staggering and offer new teaching opportunities. In addition, because the recession was primarily driven by supply side shocks, the entire episode offers a unique…

Educational curricula in data analysis are increasingly fundamental to statistics, data science, and a wide range of disciplines. The educational literature comparing coding syntaxes for instruction in data analysis recommends utilizing a simple syntax for introductory coursework. However, there is limited prior work to assess the pedagogical…

We present an interactive spreadsheet that supports teaching essential concepts in classification using the logistic regression (LoR) model for binary classification. The interactive spreadsheet demonstrates the capabilities of LoR by integrating computation with visualization. Students will reinforce concepts like probabilities, maximum…

Even under ideal conditions, teaching is tough work. Facing unrelenting pressure from administrators and parents and caught in a race against time to improve student outcomes, educators can easily become discouraged (or worse, burn out completely) without a robust coaching system in place to support them. For more than 20 years, perfecting such a…

This study aimed at understanding and investigating the lived experiences of early childhood teachers' observation practices as a professional tool. Interpretative phenomenological approach was utilized to investigate participants' experiences deeply from their lived experiences. The current study's participants consisted of five early childhood…

In 2010, Nolan and Temple Lang proposed "integration of computing concepts into statistics curricula at all levels." The unprecedented growth in data and emphasis on data science has provided an impetus to finally realizing full implementations of this in new statistics and data science programs and courses. We discuss a proposal for the…

The emerging field of data science has brought attention to how we teach statistics and data science (Bargagliotti et al., 2020; Franklin et al., 2007) and prepare the next generation of statistics and data science teachers (Franklin et al., 2013). To realize the full potential of statistics and data science, researchers have also called for using…

This article describes the motivation and design for introductory coursework in computation aimed at midcareer professionals who desire to work in data science and analytics but who have little or no background in programming. In particular, we describe how we use modern interactive computing platforms to accelerate the learning of our students…

Generating personalized learning pathways for e-learners is a critical issue in the field of e-learning as it plays a pivotal role in guiding learners towards the successful achievement of their learning objectives. The existing literature has proposed various methods from different perspectives to address this issue, including learner-based,…

This study explores the use of generative AI, specifically ChatGPT, in statistical data analysis and its implications for statistics education at universities of applied sciences. This paper begins with first discussing the future division of labor between humans and machines in the context of statistical data analyses following the widespread…