Data-driven marketing analytics courses are integral to modern business management degrees in universities, yet many graduates focus solely on single, separated data analysis techniques during their learning process, hindering effective integration and practical performance. This study proposes that employing the Fishbowl method, which divides…

This is the first of four columns by Tim Erikson which introduces us to the Common Online Data Analysis Platform (CODAP). CODAP is a free, web-based software tool that your students can use for many types of tasks. This first column shows how CODAP can be used for mathematical modelling and where it might fit with the "Australian Curriculum:…

The need for data-driven decision-making primarily motivates interest in analysing Big Data in higher education. Although there has been considerable research on the value of Big Data in higher education, its application to address critical issues within the sector is still limited. This systematic review, conducted in December 2021 and…

Holistic data science education places data science in the context of real world applications, emphasizing the purpose for which data were collected, the pedigree of the data, the meaning inherent in the data, the deploying of sustainable solutions, and the communication of key findings for addressing the original problem. As such it spends less…

Experimental activity in the physics teaching can be considered as a space in which teachers create contexts for students to approach the way scientific knowledge is constructed. In this sense, the strategies for the integration of Information and Communication Technologies (ICT) in the context of science education, has a wide potential to guide…

Problem decomposition into sub-problems or subgoals and recomposition of the solutions to the subgoals into one complete solution is a common strategy to reduce difficulties in structured problem solving. In this study, we use a datadriven graph-mining-based method to decompose historical student solutions of logic-proof problems into Chunks. We…

In Singapore, where primary and secondary students routinely top standardized worldwide mathematics examinations, a paradox emerges: when reaching university, many struggle to apply their skills critically in real-world contexts. This commentary examines the challenges and strategies involved in teaching quantitative reasoning (QR) to…

Modernizing mathematics refers to the idea that teachers should rethink how mathematics has traditionally been taught in schools by making rich tasks and collaboration the focus of instruction and promoting opportunities for active learning. "Modern Math Tasks to Provoke Transformational Thinking" presents carefully crafted tasks that…

This syndicate offers four recommendations to help educators adjust curricula to accommodate the rapid integration of data into journalism. First, instruction in numeracy and basic descriptive statistics must be required as either modules in existing courses or as separate offerings. Second, students should be taught to avoid mistakes in…

Teaching students statistical programming languages while simultaneously teaching them how to debug erroneous code is challenging. The traditional programming course focuses on error-free learning in class while students' experiences outside of class typically involve error-full learning. While error-free teaching consists of focused lectures…

This study aims to investigate problem-solving with dataset (PSWD) as a computational thinking learning implementation as reflected in academic publications. Specifically, the purpose is to specify the scope of PSWD, which overlaps with the data literacy, thinking with data, big data literacy, and data-based thinking concepts in the literature.…

Industrial drug discovery teams encompass scientists from multiple specialties and require participants to communicate effectively across disciplinary boundaries. In this paper, we present an undergraduate or graduate classroom simulation of this environment. Over a series of five workshops, student teams of mixed scientific backgrounds perform…

The poor level of engagement in learning mathematics is primarily caused by ineffective methods of instruction. Therefore, the purpose of this study was to investigate how context-based problem-posing and solving instructional approaches influence students' engagement in learning data handling using a concurrent embedded quasi-experimental…

One of the challenges that science teachers face is the lack of strategy/method to train students in data collection and developing analytical skills, which are pre-requisites to resolve socio-scientific problems and an important element in scientific literacy. In this activity, the SWOT analysis proposed by the Stanford Research Institute in the…

In this article, the authors introduce the "Pre-K-12 Guidelines for Assessment and Instruction in Statistics Education II (GAISE II): A Framework for Statistics and Data Science Education" report. This report, which was published by the American Statistical Association (ASA) and endorsed by the National Council of Teachers of Mathematics…