Complex Problems and generative learning: for AI, presentation of the 15–20 min video stories, was followed

by a rather open problem statement in form of a real-life goal. Students were supposed to find (“generate”) themselves the intermediate, science (or other discipline) related questions to be solved for this goal, and the entire instructional INCB024360 nmr setting (long story, embedded data, multistep problems, generative learning) leads to a rather high complexity. While this indeed is close to many real-life problem settings, it entails considerable, at a given learning level maybe hardly surmountable difficulties. In terms of instructional psychology, there is a dilemma of complexity vs. cognitive load, which cannot be decided a priori, but requires empirical investigation. For this purpose, complexity must be variable, necessitating a flexible, easy-to-change learning anchor (such as NSP). In the present study, problems were less

complex than in AI (but still encompassing transfer and discussion, see the section on problem levels in “Materials and Methods”). This is close to current teaching practice, but the entire approach is also appropriate for studying variable degrees of complexity ( Kuhn, 2007, Kuhn, 2008, Kuhn and Müller, 2006 and Kuhn and Müller, 2007). Summing up, the approach presented here is Smoothened a form of CBSE based on work on narrative contexts and, regarding its design principles, more specifically inspired by Anchored Instruction. While most of the design features mentioned PD-166866 datasheet above are maintained, the video-based “anchors” of the original AI approach were of course deliberately

replaced by newspaper story problems. In line with existing research described in the preceding section, the following research questions were examined, beginning with two questions on general effects: first, whether science learning with newspaper story problems is more motivating than learning with content-identical, conventional counterparts. Second, whether it is also more effective for learning, and to which degree. Furthermore, whether these general beneficial effects also cover more specific aspects, closely connected to the theoretical background of the approach: third, whether perceived self-concept (as motivation sub-dimension) can be improved (because this is a feature of particular importance to CBSE in general, and NSP in particular). Fourth, whether the same is true for transfer ability (as learning sub-dimension, again essential for CBSE and, more generally, for scientific literacy). Finally, there are two questions which are important for practical implementation (a main objective of the present study), viz.