In this paper, we describe a course project in which teams of undergraduate students propose and execute an end-to-end analytics project to solve a real-world problem. The project challenges students to implement machine learning, optimization, simulation, or a combination of these three techniques on real-world data that they collect. A…

The statistical problem-solving process is key to the statistics curriculum at the school level, post-secondary, and in statistical practice. The process has four main components: formulate questions, collect data, analyze data, and interpret results. The Pre-K-12 Guidelines for Assessment and Instruction in Statistics Education (GAISE) emphasizes…

Data collection and analysis (DCA) skills apply mathematical knowledge, such as counting, sorting, and classifying, to investigations of real-world questions. This pursuit lays the foundation for learners to develop flexible problem-solving skills with data. This pilot study tested a preschool intervention intended to support teachers in promoting…

We examined the outcomes of elementary school-based problem-solving teams (PSTs) who participated in a multi-component consultation focused on enhancing systematic problem solving. Consultation provided to each PST included training in the use of a problem-solving protocol (i.e., "Outcomes: Planning Monitoring, and Evaluating"…

Feedback on how students progress through completing subgoals can improve students' learning and motivation in programming. Detecting subgoal completion is a challenging task, and most learning environments do so either with "expert-authored" models or with "data-driven" models. Both models have advantages that are…

At the stage of designing an educational environment, one of the most significant problems is the creation of effective visualization tools for collecting, organizing and analysing educational information. Existing approaches to visual information analysis have a number of disadvantages, which include a significant resource intensity and high…

Experiential learning opportunities have been proven effective in teaching applied and complex subjects such as business analytics. Current business analytics pedagogy tends to focus heavily on the modeling phase with students often lacking a comprehensive understanding of the entire analytics process including dealing with real-life data that are…

The preschool years, spanning from birth to age six, are crucial periods for acquiring social-emotional learning (SEL) skills. An effective way to address social-emotional learning deficits is to implement evidence-based intervention programs. The purpose of this article is to review specific evidencebased social-emotional learning intervention…

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…

The increasing use of massive data requires effective teaching strategies for business analytics. The discipline combines analytical skills, information technology, and business-domain knowledge, and is challenging to teach to business students. This research demonstrates that business undergraduate students can benefit from an experiential…

This paper describes the evolution of "recognition of need for data" and "strategical thinking", two types of thinking identified by Wild and Pfannkuch in their Framework for Statistical Thinking in Empirical Enquiry, as well as its relevance for math teacher professional development. The research was carried out with ten…

Fisheries scientists make sure that fish populations ("fisheries") are managed properly, neither over- or under-utilized, to maintain long-term economic and ecological stability. Scientists collect data and conduct surveys to determine fish populations, and then make recommendations about how many fish may be caught by commercial and…

Peter Dunn and Margaret Marshman present the second of their data files articles in which they discuss the statistical investigation cycle which describes the whole process of conducting a statistical research study. [For "The Data Files: A Series of Articles to Support Mathematics Teachers to Teach Statistics," see EJ1259108.]

The African Data Initiative started as a crowd-sourced campaign to improve the teaching of statistics in African universities. The analysis of climate data provides one suitable context to illustrate ideas that lead to a radical new form of teaching. The problem within the context comes first, the technicalities are largely reduced -- mathematics…

Effective collaboration between student peers is not spontaneous. A system that can measure collaboration in real-time may be useful, as it could alert an instructor to pairs that need help in collaborating effectively. We tested whether superficial measures of speech and user interface actions would suffice for measuring collaboration. Pairs of…