Despite the efforts of instructional design (ID) to solve real-life problems, it remains challenging to adapt and be flexible in such situations. In particular, problems that require simultaneous knowledge of multiple domains and contexts are more challenging to solve because real-life problems do not reconstruct the learned experience. This is…

In research practice, it is common to measure cognitive load after learning using self-report scales. This approach can be considered risky because it is unclear on what basis learners assess cognitive load, particularly when the learning material contains varying levels of complexity. This raises questions that have yet to be answered by…

Complex sequences are ubiquitous in human mental life, structuring representations within many different cognitive domains--natural language, music, mathematics, and logic, to name a few. However, the representational and computational machinery used to learn abstract grammars and process complex sequences is unknown. Here, we used an artificial…

Through research-backed strategies and practical applications, author Julia A. Simms explores self-regulated learning, instructional sequences, and brain-based learning. She examines the development of cognitive and metacognitive skills, working memory, and effective explicit instruction, offering step-by-step guidance for teachers to facilitate…