Estimating and accounting for statistical uncertainty have become essential in today's information age, and crucial for cultivating a sound decision making citizenry. Engaging with statistical uncertainty early on can support the gradual development of uncertainty-related considerations that are often challenging to foster at any age. Statistical…

The Precipitating Change Project was a 5-year development, implementation, and research study of an innovative 4-week middle school curricular unit in computational weather forecasting that integrates students' learning and use of meteorology and computational thinking (CT) concepts and practices. The project produced a list of CT skills and…

Example-based learning often uses a design in which learners first receive basic instructional explanations of new principles and concepts and then examples thereof. In this sequence, it is crucial that learners self-explain by using the content of the basic instructional explanations to elaborate on the examples. Typically, learners are not…

This paper discusses Multi-Feature Hierarchical Sequential Pattern Mining, MFH-SPAM, a novel algorithm that efficiently extracts patterns from students' learning activity sequences. This algorithm extends an existing sequential pattern mining algorithm by dynamically selecting the level of specificity for hierarchically-defined features…