Purpose: Scholars are increasingly paying attention to the characteristics of effective citizenship education. The systematic use of data to maximise student learning, also called an output-driven approach, is often presented as a powerful predictor of student outcomes. However, its effectiveness has not been studied in citizenship education.…

Background: Data literacy (DL) is vital for teachers, as it enables them to build on data and improve teaching and learning. Therefore, developing DL among pre-service teachers is critical. Objectives: The purpose of this study is threefold: to evaluate whether a feedback visualisation of peer assessment-based teaching approach (FVPA-based…

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…

The purpose of this paper is to detail an exploratory case study which highlights a process to modernize an undergraduate marketing curriculum by incorporating aspects of digital marketing and analytics in all courses. In comparison to most other university models that offer, at best, one course in digital marketing, this paper details a blueprint…

As computational methods are widely used in science disciplines, integrating computational thinking (CT) into classroom materials can create authentic science learning experiences for students. In this study, we classroom-tested a CT-integrated geoscience curriculum module designed for secondary students. The module consisted of three inquiry…

In the era of big data, many business organizations consider data analytics skills as important criteria in the acquisition of qualified applicants. As numerous managerial decisions in the field of marketing are becoming evidence-based, business schools have integrated case studies about different stages of data analytics such as problem…

The paper critiques key international teaching excellence and higher education outcomes frameworks for their lack of attention to epistemic equality. It subsequently argues that adequate 'datafication' of these frameworks, to demonstrate the extent to which universities offer teaching experiences which promote intellectual equivalence of all…

Student engagement is regarded as a critical educational outcome. However, it has proven to be elusive to educators within technical domains, such as marketing research and analytics, which has inspired the exploration of experiential course design elements. Client-sponsored projects (CSPs) have become a popular tactic to meet this objective in…

The purpose of this article is to describe a multidisciplinary approach implemented in teaching public policy analysis at university level. The approach fuses (a) contextual policy analysis with (b) bivariate and multivariate analysis techniques and (c) data analytics skills to improve the learners' competence to conduct "decisional"…

Background: Acquisition and generalization of data analysis skills are perennial challenges for psychology students. Teaching advanced data analysis in a psychology-specific context might improve students' learning. Objective: At a mid-sized public university, we evaluated student outcomes after a new quantitative psychology course taught in the…

The Fluid Earth (FE) is an interactive data visualization initially developed for learning about Earth's atmosphere in informal educational settings. In this study, we tested FE in middle school classes to assess student engagement in a formal educational setting. Using a quasi-experimental design, students were assigned to interact with the data…

Drawing upon his experience, more than 60 years ago, as a psychometric support person to a very special teacher of brain damaged children, the author of this article reflects on the productive use of educational assessments and data from them to educate - assessment in the service of learning. Findings from the Gordon Commission on the Future of…

Statistical thinking is essential to understanding the nature of scientific results as a consumer. Statistical thinking also facilitates thinking like a scientist. Instead of emphasizing a "correct" procedure for data analysis and its outcome, statistical thinking focuses on the process of data analysis. This article reviews frequentist…

The increasing prevalence of learner-centred forms of learning as well as an increase in the number of learners actively participating on a wide range of digital platforms and devices give rise to an ever-increasing stream of learning data. Learning analytics (LA) can enable learners, teachers, and their institutions to better understand and…

In the age of big data and analytics, it is important that students learn about artificial intelligence (AI) and machine learning (ML). Machine learning is a discipline that focuses on building a computer system that can improve itself using experience. ML models can be used to detect patterns from data and recommend strategic marketing actions.…