Raven’s Standard Progressive Matrices for Adolescents: A Case for a Shortened Version

Cognitive ability of adolescents is often measured using the Raven’s Standard Progressive Matrices (RSPM). However, the RSPM knows a long administration time which may be suboptimal, as time-on-task effects are known to increase fatigue, to lower motivation, and to worsen performance on cognitive tasks. Therefore, a shortened version for adolescents was developed recently. In the current preregistered study we investigated this shortened version in a sample of adolescents (N = 99) of average educational backgrounds. We tested whether the shortened RSPM is a valid alternative to the original RSPM, which proved to be the case, as we observed a moderate to high correlation between the two versions. Moreover, we tested version effects on fatigue, motivation and performance. Fatigue was lower and motivation was higher after completing the short compared to the original version, and performance was better in the short compared to the original version. However, additional analyses suggested that beneficial version effects on performance were not due to reduced time-on-task, but due to the short version containing less difficult items than the original version. Moreover, version related differences in performance were not related to version related differences in fatigue and motivation. We conclude that the shortened version of the RSPM is a valid alternative to the original version, and that the shortened version is beneficial in terms of fatigue and motivation, but that these beneficial effects on fatigue and motivation do not carry over to performance.</p

How much do you want to learn? High-school students' willingness to invest effort in valenced feedback-learning tasks

High-school students decide in which tasks to invest their cognitive effort on a daily basis. At school, such decisions often relate to feedback-learning situations (e.g., whether or not to do homework exercises). To investigate how willing high-school students are to invest their cognitive effort in such situations, we administered in this preregistered study a feedback-learning task in combination with a cognitive effort-discounting task – a paradigm to quantify willingness to invest effort. We did so to a large sample (N = 195) from average educational backgrounds in an ecologically valid setting (a school class). We specifically tested whether high-school students discounted their effort in feedback-learning tasks, which proved to be the case, and whether this discounting was differentially affected by positive and negative feedback, which proved not to be the case. We also found that learning was unaffected by feedback valence, except that students learned better from positive than from negative feedback when high effort was required. These results imply that in a school setting, where feedback learning is common, high-school students are less willing to invest cognitive effort in more effortful tasks irrespective of feedback valence, and that positive feedback can aid learning when high effort is required. We provide several recommendations as to how our proposed combination of feedback learning and effort discounting could be used to understand and improve students' academic motivation. Educational relevance statement: High school students sometimes struggle with motivation for learning, at least partly because of low willingness to invest their effort. By investigating high-school students' willingness to invest effort for learning within an educational context, we aim to enhance understanding of this decision-making process in high-school students. Our results indicate that in a school setting, where feedback learning is common, high-school students are less willing to invest cognitive effort in more effortful tasks irrespective of whether they receive positive or negative feedback, but that positive feedback can aid learning when learning tasks require high effort. These results imply that positive feedback may reduce the costs of learning or increase its benefits for difficult tasks.</p

Is it worth it? How your brain decides to make an effort

Everything you do requires you to exert effort. For instance, basic things like walking or cycling require physical effort and have to do with using your body. Another type of effort is cognitive effort, which has to do with thinking and using your brain. For instance, think about trying to master a Rubik’s cube. Would you want to put in your effort here? The pleasure of finding a solution might outweigh the effort of thinking hard. Or you may decide that finding a solution is not worth your effort. Why and when would you decide to think hard? In this article, we will explain how you decide to exert cognitive effort and what is happening in your brain while you make this decision.Pathways through Adolescenc

Towards Higgs boson production in gluon fusion to NNLO in the MSSM

We consider the Higgs boson production in the gluon-fusion channel to next-to-next-to-leading order within the Minimal Supersymmetric Standard Model. In particular, we present analytical results for the matching coefficient of the effective theory and study its influence on the total production cross section in the limit where the masses of all MSSM particles coincide. For supersymmetric masses below 500 GeV it is possible to find parameters leading to a significant enhancement of the Standard Model cross section, the $K$-factors, however, change only marginally.Comment: 20 pages; v2: modification of discussion of numerical effect, version to appear in EPJC; v3: eq.(18) corrected, minor correction

On the NLO QCD corrections to the production of the heaviest neutral Higgs scalar in the MSSM

We present a calculation of the two-loop top-stop-gluino contributions to Higgs production via gluon fusion in the MSSM. By means of an asymptotic expansion in the heavy particle masses, we obtain explicit and compact analytic formulae that are valid when the Higgs and the top quark are lighter than stops and gluino, without assuming a specific hierarchy between the Higgs mass and the top mass. Being applicable to the heaviest Higgs scalar in a significant region of the MSSM parameter space, our results complement earlier ones obtained with a Taylor expansion in the Higgs mass, and can be easily implemented in computer codes to provide an efficient and accurate determination of the Higgs production cross section.Comment: 18 pages, 4 figure

Differential Cross Section for Higgs Boson Production Including All-Orders Soft Gluon Resummation

The transverse momentum $Q_T$ distribution is computed for inclusive Higgs boson production at the energy of the CERN Large Hadron Collider. We focus on the dominant gluon-gluon subprocess in perturbative quantum chromodynamics and incorporate contributions from the quark-gluon and quark-antiquark channels. Using an impact-parameter $b$-space formalism, we include all-orders resummation of large logarithms associated with emission of soft gluons. Our resummed results merge smoothly at large $Q_T$ with the fixed-order expectations in perturbative quantum chromodynamics, as they should, with no need for a matching procedure. They show a high degree of stability with respect to variation of parameters associated with the non-perturbative input at low $Q_T$. We provide distributions $d\sigma/dy dQ_T$ for Higgs boson masses from $M_Z$ to 200 GeV. The average transverse momentum at zero rapidity $y$ grows approximately linearly with mass of the Higgs boson over the range $M_Z < m_h \simeq 0.18 m_h + 18$~GeV. We provide analogous results for $Z$ boson production, for which we compute $\simeq 25$ GeV. The harder transverse momentum distribution for the Higgs boson arises because there is more soft gluon radiation in Higgs boson production than in $Z$ production.Comment: 42 pages, latex, 26 figures. All figures replaced. Some changes in wording. Published in Phys. Rev. D67, 034026 (2003