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We investigated whether retrieval-based learning can facilitate the acquisition of cognitive skills, focusing on the control-of-variables strategy. This core scientific experimentation skill is regularly taught in science education classes because understanding it is essential for understanding experimental investigations in science. In the present study, participants initially read a text explaining the control-of-variables strategy. We compared the effects of subsequent retrieval practice and restudy of the text in performing a transfer test requiring the application of the control-of-variables strategy by judging the validity of a number of experimental designs. In addition, recall of the initially studied text was assessed as well. Repeated retrieval practice in combination with restudy opportunities resulted in better performance in both the transfer test and the recall test as compared to mere restudy or a single study opportunity. These findings demonstrate that retrieval practice is a useful tool for promoting deep conceptual learning.
cpm.4.CSE/IRT (compact process model for Competence Science Education based on IRT models) is a process model for competence measurement based on IRT models. It allows the efficient development of measuring instruments for computer science education. Cpm.4.CSE/IRT consists of four sub processes: B1 determine items, B2 test items, B3 analyze items according to Rasch model, and B4 interpret items by criteria. Cpm.4.CSE/IRT is modeled in IDEF0, a process modeling language that is standardized and widely used. It is implemented in R, an open-source software optimized for statistical calculations and graphics that allows users to interact using the web application framework Shiny. Through coordinated processes, cpm.4.CSE/IRT ensures the quality and comparability of test instruments in competence measurement. Cpm.4.CSE/IRT is demonstrated using an example from the competence area of Modeling.