Contribution: This research illuminates information entropy's efficacy as a pivotal educational tool in programming, enabling the precise quantification of algorithmic complexity and student abstraction levels for solving problems. This approach can provide students quantitative, comparative insights into the differences between optimal and…

In recent years, computing education researchers have investigated the impact of problem context on students' learning and programming performance. This work continues the investigation motivated, in part, by cognitive load theory and educational research in computer science and other disciplines. The results of this study could help inform…

Exams constitute the predominant form of summative assessment in undergraduate biology education, with the assumption that exam performance should reflect student conceptual understanding. Previous work highlights multiple examples in which students can answer exam problems correctly without the corresponding conceptual understanding. This…

Presents the text of a message sent to Susan Gerofsky by Robert Thomas after reading her article on a linguistic and narrative view of word problems in mathematics education. Gerofsky's response is also included. (DDR)

Incident identification graphs can be used to diagnose areas of difficulty in a subject's problem-solving schema at the episodic level. In this study, 22 subjects (2 experts and 20 novices) categorized into five problem-solving groups (expert, high algorithmic/high conceptual, low algorithmic/high conceptual, high algorithmic/low conceptual, and…

This article gives a comprehensive description of a theory for efficient assessment of knowledge. The essential concept is that the knowledge state of a subject, with regard to a specified field of information, can be represented by a particular subset of problems that the subject is capable of solving. (SLD)