Kognitive Basisfunktionen

Die Relevanz der kognitiven Basisfunktionen Arbeitsgedächtnis und der Fähigkeit zum Shifting sowie der fluiden Intelligenz für viele kognitive Leistungen wurde wiederholt gezeigt. Insbesondere das Arbeitsgedächtnis ist wichtig für das Lernen und sollte bei Entscheidungen hinsichtlich instruktionaler Unterstützungsmaßnahmen berücksichtigt werden. In der ersten Studie der vorliegenden Arbeit wurde untersucht, ob der Effekt einer Lernumgebung mit hohem Grad an instruktionaler Unterstützung durch Lösungsbeispiele verglichen mit einer Lernumgebung mit niedrigem Grad an instruktionaler Unterstützung (Problemlösen) auf den Wissenserwerb von der Arbeitsgedächtniskapazität, der Shifting-Fähigkeit sowie der fluiden Intelligenz moderiert wird. In den beiden Lernumgebungen lernten 76 Studierende aus den Fachrichtungen Pädagogik, Psychologie und Schulpsychologie mit Problemen aus der Domäne Statistik. Die Ergebnisse zeigten, dass die Fähigkeit zum Shifting und die fluide Intelligenz, nicht aber die Arbeitsgedächtniskapazität einen moderierenden Einfluss auf den Erwerb anwendungsorientierten Wissens haben. Die kognitive Belastung war nicht mit der Arbeitsgedächtniskapazität, aber der fluiden Intelligenz, konzeptuellem und anwendungsorientiertem Vorwissen sowie Skalen eines Fragebogens zur Erfassung aktueller Motivation korreliert. Den Ergebnissen der ersten Studie zu Folge könnten die Fähigkeit zum Shifting und die fluide Intelligenz für die Bestimmung des optimalen Grads an instruktionaler Unterstützung wichtig sein. Vor dem Hintergrund der Bedeutung kognitiver Basisfunktionen und einer Vielzahl neuerer Studien zu Arbeitsgedächtnistrainings wurde in der zweiten Studie dieser Arbeit eine Metaanalyse zu Arbeitsgedächtnistrainings durchgeführt. In dieser Metaanalyse wurden mehrere, bisher nicht beachtete Trainingsbedingungen als potentielle Moderatoren berücksichtigt. Es wurden 47 Studien mit 65 Gruppenvergleichen analysiert. Die Ergebnisse zeigten, dass Arbeitsgedächtnistrainings nahe Transfereffekte auf Kurzzeit- und Arbeitsgedächtniskomponenten erzielen, die zum Follow-up erhalten bleiben. Weite Transfereffekte auf andere kognitive Fähigkeiten und Fertigkeiten (nonverbale und verbale Fähigkeit, Fertigkeit zur Wortdekodierung, mathematische Fähigkeiten und Fertigkeiten) waren klein, auf die nonverbale und verbale Fähigkeit beschränkt und blieben nicht zum Follow-up erhalten. Unter den Moderatoren hatten der Interventionstyp, die Trainingsdosis, die Sessiondauer, die Supervision während des Trainings und der Trainingsort einen Einfluss auf nahe und weite Transfereffekte. Den Ergebnissen der zweiten Studie zufolge können Arbeitsgedächtnistrainings robuste, nahe Transfereffekte auf andere Aufgaben erzielen, die Kurzzeit- und Arbeitsgedächtniskomponenten erfassen. Die Bedingungen für Transfereffekte, insbesondere weite Transfereffekte, sind noch schlecht verstanden. Arbeitsgedächtnistrainings mit optimierten Trainingsbedingungen könnten jedoch zu praktisch relevanten Transfereffekten führen

Executive functions in the context of complex learning: Malleable moderators?

Executive functions are crucial for complex learning in addition to prior knowledge. In this article, we argue that executive functions can moderate the effectiveness of instructional approaches that vary with respect to the demand on these functions. In addition, we suggest that engagement in complex activity contexts rather than specific cognitive training paradigms may enhance executive functions and yield practically relevant transfer effects to other cognitive abilities. We develop several hypotheses and principles for how to improve executive functions in these contexts. For future research, we suggest to systematically investigate the moderating role of executive functions in learning environments with varying degrees of instructional support and varying context characteristics. We identify potential factors influencing the improvement of executive functions to be considered in a systematic research program

Validation of plasma biomarker candidates for the prediction of eGFR decline in patients with type 2 diabetes

Objective: The decline of estimated glomerular filtration rate (eGFR) in patients with type 2 diabetes is variable and early interventions would likely be cost effective. We elucidated the contribution of 17 plasma biomarkers to the prediction of eGFR loss on top of clinical risk factors. Research Design and Methods: We studied participants in PROVALID, a prospective multinational cohort study of patients with type 2 diabetes and a follow up of more than 24 months (n = 2560; baseline median eGFR 84 mL/min/1.73m2, UACR 8.1 mg/g). The 17 biomarkers were measured at baseline in 481 samples using Luminex technology and ELISA. The prediction of eGFR decline was evaluated by linear mixed modeling. Results: In univariable analyses nine of the 17 markers showed significant differences in median concentration between the two groups. A linear mixed model for eGFR obtained by variable selection exhibited an adjusted R2 of 62%. A panel of twelve biomarkers was selected by the procedure and accounted for 34% of the total explained variability, of which 32% were due to five markers. Each biomarker’s individual contribution to the prediction of eGFR decline on top of clinical predictors was generally low. When included into the model, baseline eGFR exhibited the largest explained variability of eGFR decline (R2 of 79%) and the contribution of each biomarker dropped below 1%. Conclusions: In this longitudinal study of patients with type 2 diabetes and maintained eGFR at baseline, 12 of the 17 candidate biomarkers were associated with eGFR decline, but their predictive power was low

How to combine collaboration scripts and heuristic worked examples to foster mathematical argumentation – when working memory matters

Mathematical argumentation skills (MAS) are considered an important outcome of mathematics learning, particularly in secondary and tertiary education. As MAS are complex, an effective way of supporting their acquisition may require combining different scaffolds. However, how to combine different scaffolds is a delicate issue, as providing learners with more than one scaffold may be overwhelming, especially when these scaffolds are presented at the same time in the learning process and when learners’ individual learning prerequisites are suboptimal. The present study therefore investigated the effects of the presentation sequence of introducing two scaffolds (collaboration script first vs. heuristic worked examples first) and the fading of the primarily presented scaffold (fading vs. no fading) on the acquisition of dialogic and dialectic MAS of participants of a preparatory mathematics course at university. In addition, we explored how prior knowledge and working memory capacity moderated the effects. Overall, 108 university freshmen worked in dyads on mathematical proof tasks in four treatment sessions. Results showed no effects of the presentation sequence of the collaboration script and heuristic worked examples on dialogic and dialectic MAS. Yet, fading of the initially introduced scaffold had a positive main effect on dialogic MAS. Concerning dialectic MAS, fading the collaboration script when it was presented first was most effective for learners with low working memory capacity. The collaboration script might be appropriate to initially support dialectic MAS, but might be overwhelming for learners with lower working memory capacity when combined with heuristic worked examples later on

New Polynomial-Based Molecular Descriptors with Low Degeneracy

In this paper, we introduce a novel graph polynomial called the ‘information polynomial’ of a graph. This graph polynomial can be derived by using a probability distribution of the vertex set. By using the zeros of the obtained polynomial, we additionally define some novel spectral descriptors. Compared with those based on computing the ordinary characteristic polynomial of a graph, we perform a numerical study using real chemical databases. We obtain that the novel descriptors do have a high discrimination power

Integrative analysis of prognostic biomarkers derived from multiomics panels for the discrimination of chronic kidney disease trajectories in people with type 2 diabetes

Clinical risk factors explain only a fraction of the variability of estimated glomerular filtration rate (eGFR) decline in people with type 2 diabetes. Cross-omics technologies by virtue of; a wide spectrum screening of plasma samples have the potential to identify biomarkers for the refinement of prognosis in addition to clinical variables. Here we utilized proteomics, metabolomics and lipidomics panel assay measurements in baseline plasma samples from the multinational PROVALID study (PROspective cohort study in patients with type 2 diabetes mellitus for VALIDation of biomarkers) of patients with incident or early chronic kidney disease (median follow-up 35 months, median baseline eGFR 84 mL/min/1.73m2, urine albumin-to-creatinine ratio 8.1 mg/g). In an accelerated case-control study, 258 individuals with a stable eGFR course (median eGFR change 0.1 mL/min/year) were compared to 223 individuals with a rapid eGFR decline (median eGFR decline -6.75 mL/min/year) using Bayesian multivariable logistic regression models to assess the discrimination of eGFR trajectories. The analysis included 402 candidate predictors and showed two protein markers (KIM-1, NTproBNP) to be relevant predictors of the eGFR trajectory with baseline eGFR being an important clinical covariate. The inclusion of metabolomic and lipidomic platforms did not improve discrimination substantially. Predictions using all available variables were statistically indistinguishable from predictions using only KIM-1 and baseline eGFR (area under the receiver operating characteristic curve 0.63). Thus, the discrimination of eGFR trajectories in patients with incident or early diabetic kidney disease and maintained baseline eGFR was modest and the protein marker KIM-1 was the most important predictor

Multitasking behavior and its related constructs: Executive functions, working memory capacity, relational integration, and divided attention

Although prior investigations have revealed cognitive abilities to be important predictors of multitasking behavior, few investigations have been conducted on the relation between executive functions (EFs) and multitasking behavior. The current study examines the underlying cognitive constructs associated with the concept of multitasking behavior. A sample of 202 young adults completed a battery of EFs (shifting, updating, and inhibition), three working memory capacity (WMC) tests, three relational integration tests, two divided attention tests, and a multitasking scenario (Simultaneous Capacity). First, in direct replication attempts, the results replicated the multitasking behavior model (Biihner, Konig, Pick, & Krumm, 2006) and partially replicated the three-factor and nested factors EFs models (Friedman et al., 2016). Second, hierarchical multiple regression analyses and relative weight analyses revealed that updating, inhibition, relational integration, and divided attention had strong contributions in explaining multitasking behavior variance, whereas shifting and WMC did not show any explanatory power beyond these constructs. Finally, using structural equation modeling, we found that the general EF ability (common EF) representing variance common to shifting, updating, and inhibition highly overlapped with multitasking behavior. Our results are of value not only to shed light on the relevant cognitive correlates of multitasking behavior but also to position multitasking behavior in an established framework of cognitive abilities

Polarimetric Balanced Detection: Background-Free Mid-IR Evanescent Field Laser Spectroscopy for Low-Noise, Long-term Stable Chemical Sensing

In this work, we introduce polarimetric balanced detection as a new attenuated total reflection (ATR) infrared (IR) sensing scheme, leveraging unequal effective thicknesses achieved with laser light of different polarizations. We combined a monolithic widely tunable Vernier quantum cascade laser (QCL-XT) and a multibounce ATR IR spectroscopy setup for analysis of liquids in a process analytical setting. Polarimetric balanced detection enables simultaneous recording of background and sample spectra, significantly reducing long-term drifts. The root-mean-square noise could be improved by a factor of 10 in a long-term experiment, compared to conventional absorbance measurements obtained via the single-ended optical channel. The sensing performance of the device was further evaluated by on-site measurements of ethanol in water, leading to an improved limit of detection (LOD) achieved with polarimetric balanced detection. Sequential injection analysis was employed for automated injection of samples into a custom-built ATR flow cell mounted above a zinc sulfide multibounce ATR element. The QCL-XT posed to be suitable for mid-IR-based sensing in liquids due to its wide tunability. Polarimetric balanced detection proved to enhance the robustness and long-term stability of the sensing device, along with improving the LOD by a factor of 5. This demonstrates the potential for new polarimetric QCL-based ATR mid-IR sensing schemes for in-field measurements or process monitoring usually prone to a multitude of interferences.European CommissionEuropean Commission3542