Cognitive load in algebra: element interactivity in solving equations

Central to equation solving is the maintenance of equivalence on both sides of the equation. However, when the process involves an interaction of multiple elements, solving an equation can impose a high cognitive load. The balance method requires operations on both sides of the equation, whereas the inverse method involves operations on one side only. In an experiment, middle school students (N?=?71) were randomly assigned to the balance and inverse methods to complete a pre-test, an acquisition phase and a post-test. Pre-test and post-test comparisons found that the inverse group outperformed the balance group for those equations that involved high element interactivity. Instructional efficiency measures further confirmed that the balance method imposed higher cognitive load. The inverse method was capable of reducing cognitive load due to the interacting elements.     

Creatine kinase activity weakly correlates to volume completed following upper body resistance exercise

In the current study, we examined the relationship between serum creatine kinase (CK) activity following upper body resistance exercise with a 1- or 3-min rest between sets. Twenty men performed two sessions, each consisting of four sets with a 10-repetition maximum load. The results demonstrated significantly greater volume for the 3-min condition (M = 4156 kg, SD = 867, for 3 min; vs. M = 3503 kg SD = 759, for 1 min; p < .001), with no significant differences in delta CK activity between conditions (p = .574). Nevertheless, there was a weak correlation between the delta CK activity and total volume of exercise completed (r = .55 with a 1-min rest, and r = .45 with a 3-min rest). Therefore, the volume following upper body resistance exercise correlates weakly with serum CK levels, irrespective of rest interval length between sets.     

Going Deep into Mechanisms for Moral Reasoning Growth: How Deep Learning Approaches Affect Moral Reasoning Development for First-year Students

The purpose of this paper was to determine the effects of deep approaches to learning on the moral reasoning development of 1,457 first-year students across 19 institutions. Results showed a modest positive relationship between our measures of deep approaches to learning and moral reasoning at the end of the first year of college even after controlling for precollege moral reasoning. After accounting for a host of demographic and relevant student characteristics and for the natural clustering of students, we found that the integrative learning subscale, which captures students’ participation in activities designed to integrate information from varied sources and diverse perspectives, positively affected moral reasoning among first-year students. Implications for researchers and practitioners are discussed.     

Relations between intelligence and the development of metaconceptual knowledge

Across two studies, we developed and tested a declarative metacognitive interview to investigate the effects of developmental level and verbal intelligence on children's metaconceptual understanding of processes related to concept use and object categorization. Metaconceptual knowledge developed throughout elementary school, with near ceiling scores for adults. IQ scores correlated positively with metaconceptual interview scores for all groups of children. Study 2 confirmed a relationship between scores on the metaconceptual interview and performance on a Twenty Questions task for which strategic performance was presumed to depend on such knowledge, though metaconceptual knowledge was most important when IQ was lower. Implications for theory development and hypotheses about how metaconceptual knowledge develops are discussed.     

Example-Based Learning in Heuristic Domains: A Cognitive Load Theory Account

One classical instructional effect of cognitive load theory (CLT) is the worked-example effect. Although the vast majority of studies have focused on well-structured and algorithmic sub-domains of mathematics or physics, more recent studies have also analyzed learning with examples from complex domains in which only heuristic solution strategies can be taught (e.g., troubleshooting, mathematical proving). Is learning by such examples also effective, and do the same instructional design principles apply? We discuss the main findings of an own research program and of related studies that addressed such questions. We found that CLT’s basic design principles also hold true for heuristic domains: Reduce extraneous load by employing examples, maximize germane load by fostering self-explanations, prevent cognitive overload by pretraining in the case of difficult learning materials, and by focusing attention on the most relevant aspects. Other typical CLT assumptions (e.g., better provide information for novice learners) were not confirmed in its generality. The present findings extend the applicability of CLT but also identify some potentially too simplistic assumptions.     

Robust block second order sliding mode control for a quadrotor

This paper presents the design of a controller based on the block control technique combined with the super twisting control algorithm for trajectory tracking of a quadrotor helicopter. A first order exact differentiator is used in order to estimate the virtual control inputs, which simplifies the control law design. In addition, the wind parameter resulting from the aerodynamic forces is also estimated in order to ensure robustness against these unmatched perturbations. The stability and finite time convergence of the exact differentiator have been recently proved by means of Lyapunov functions, and therefore the stability analysis of the proposed controller has been carried out along the same lines. The performance and effectiveness of the proposed controller are tested in a simulation study taking into account external disturbances.     

Good practices for student learning: Mixed‐method evidence from the Wabash National Study

Kathleen M. Goodman, Marcia Baxter Magolda, Tricia A. Seifert, and Patricia M. King review both quantitative and qualitative data to understand students' college experiences and provide powerful information to guide educators.