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…

This article explores how making data playable, i.e. developing exploratory co-creation techniques that use elements of play and games to interpret small to mid-sized datasets beyond the current focus on visual evidence, can help a) promote creative data literacy in higher education, and b) expand existing definitions of data literacy. The article…

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…

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…

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,"…

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…

Statistical literacy refers to two interrelated components: people's ability to interpret and critically evaluate statistical information, and their ability to discuss or communicate their reactions to statistical information. The ability to read and interpret graphical displays is part of statistical literacy because much of the statistical…

This manuscript focuses on the role of data analytics in mediating how teachers make sense of racial and gender inequity in patterns of student participation in their classrooms. Five middle school mathematics teachers participated in a year-long professional development program, centered on data analytics generated by the EQUIP observation tool.…

The aim of this study was to conduct a systematic literature review on the use of serious games in science education between 2016 and 2020 years. A total of 39 articles were included from Science Citation Index-Expanded (SCI-Expanded), Social Science Citation Index (SSCI), Arts & Humanities Citation Index (A&HCI) and Emerging Sources…

In the higher education context, an increasing concern on the technical or instrumental approach permeates attention to academics' data literacies and faculty development. The need for data literacy to deal specifically with the rise of learning analytics in higher education has been raised by some authors, though in spite of some focus on the…

An online peer-assessment system typically allows students to give textual feedback to their peers, with the goal of helping the peers improve their work. The amount of help that students receive is highly dependent on the quality of the reviews. Previous studies have investigated using machine learning to detect characteristics of reviews (e.g.,…

This paper presents a financial statements analysis (FSA) project that integrates Bloomberg and Thomson Reuters in an introductory MBA accounting course. The project introduces students to leading financial databases that are used in practice and helps them to understand how such databases can be effectively leveraged to analyze both the financial…

Data science surrounds us in contexts as diverse as climate change, air pollution, route-finding, genomics, market manipulation, and movie recommendations. To open the "data-science-black-box" for lower secondary school students, we developed a data science teaching unit focusing on the analysis of environmental data, which we embedded…

In this study, we held a 12-hour workshop focused on training the Data-Driven Learning (DDL) approach for in-service Chinese teachers aiming to implement this pedagogy in Mandarin Chinese classrooms in the future. We analyzed data from a postworkshop questionnaire to understand how the individual-level traits of Chinese teachers (such as their…

In Applied AI, or 'machine learning', methods such as neural networks are used to train computers to perform tasks without human intervention. In this article, we question the applicability of these methods to education. In particular, we consider a case of recent attempts from data scientists to add AI elements to a handful of online learning…