Metacognitive monitoring and control in elementary school children: Their interrelations and their role for test performance

Contemporary models of self-regulated learning emphasize the role of distal motivational factors for student's achievement, on the one side, and the proximal role of metacognitive monitoring and control for learning and test outcomes, on the other side. In the present study, two larger samples of elementary school children (9- and 11-year-olds) were included and their mastery-oriented motivation, metacognitive monitoring and control skills were integrated into structural equation models testing and comparing the relative impact of these different constituents for self-regulated learning. For one, results indicate that the factorial structure of monitoring, control and mastery motivation was invariant across the two age groups. Of specific interest was the finding that there were age-dependent structural links between monitoring, control, and test performance (closer links in the older compared to the younger children), with high confidence yielding a direct and positive effect on test performance and a direct and negative effect on adequate control behavior in the achievement test. Mastery-oriented motivation was not found to be substantially associated with monitoring (confidence), control (detection and correction of errors), or test performance underlining the importance of proximal, metacognitive factors for test performance in elementary school children.

Children's deliberate memory development: The contribution of strategies and metacognitive processes

This chapter focus is laid on the development of memory skills when children are confronted with a task or a situation in which learning or remembering certain target information is crucial. It presents important milestones toward self-regulated learning skills. The chapter discusses precursors of later strategic behaviors and metacognitive skills, the distinct research methods suitable to assessing early indicators of deliberate memory skills, as well as their importance for the emerging memory skills. It outlines the challenges arising from the application of deliberate memory skills in naturalistic, complex task contexts. The chapter adopted an explicit developmental perspective of memory strategies and metacognition in deliberate memory situations.

Self-assessment insufficiently predicts performance in emergency skills

Background: Residents demonstrate a broad range of performance levels for clinical skills, with some at an inadequate level. Adequate self-assessment is important for life long learning. However, its accuracy is questioned extensively. The aim of this study was to evaluate how far the residents’ self-assessment predicts their performance in an expert assessment of emergency skills. Summary of work: Twelve skills were identified as being relevant for the emergency duties of residents in smaller hospitals. Fifteen first-year residents from the departments of internal medicine and general surgery at a district hospital rated their performance on a questionnaire (self-assessment). This was followed by a structured, practical in vivo assessment by an anaesthesiologist (expert assessment). For both, a visual analogue scale from 0 to 10 was used, on which 0 stands for novice and 10 for expert. Predictive validity was described by Spearman’s correlation, which was significant in 3 out of 12 skills only. Median correlation (r) was 0.50 (range 0.16 to 0.93). Conclusion: At the beginning of postgraduate training, self-assessment alone is not sufficient to guide self-directed learning. Take-home message: At the beginning of their residency, physicians need structured feedback in emergency skills which can be offered by anaesthesiologists.

Lernfreude, engagierte Mitarbeit im Unterricht und erfolgreiches Leisten bei instrumentellen Formen der Lernmotivation - ein Widerspruch in sich?

In der Selbstbestimmungstheorie werden neben der intrinsischen Motivation verschiedene Formen extrinsischer Motivation unterschieden. Dabei wird die Freude am Lernen als positive, aktivierende Emotion, die mit positiven Lernhandlungen und hoher Leistung verknüpft ist, für die intrinsische Motivation als konstitutiv betrachtet. Der Zusammenhang zu den anderen Motivationsformen hingegen ist bisher empirisch weitgehend ungeklärt. An diesem Punkt setzt die vorliegende Studie an. Es wurden 356 Schüler und Schülerinnen aus österreichischen Hauptschulen zu zwei Messzeitpunkten (6. und 7. Schulstufe) mittels Fragebögen zu ihrer Motivation, ihrer Lernfreude, der Mitarbeit und der Leistung in der Schule befragt. Die Ergebnisse aus Pfadanalysen bestätigen die positive Beziehung zwischen der identifizierten Motivation und die negative Beziehung zwischen der externalen Motivation und der Lernfreude. Die introjizierte Regulation korreliert in der 7. Schulstufe schwach positiv, in der 6. Schulstufe nicht mit der Lernfreude. Die Mitarbeit weist sowohl positive Bezüge zur Lernfreude als auch zur identifizierten und introjizierten Motivation, jedoch negative Bezüge zur externalen Motivation auf. Eine hohe Mitarbeit ist förderlich für die Leistung.

Towards Self-Learning Radio-Based Localization Systems

Location-awareness indoors will be an inseparable feature of mobile services/applications in future wireless networks. Its current ubiquitous availability is still obstructed by technological challenges and privacy issues. We propose an innovative approach towards the concept of indoor positioning with main goal to develop a system that is self-learning and able to adapt to various radio propagation environments. The approach combines estimation of propagation conditions, subsequent appropriate channel modelling and optimisation feedback to the used positioning algorithm. Main advantages of the proposal are decreased system set-up effort, automatic re-calibration and increased precision.

Learning to drive: learners' self-reported cognitive failure level predicts driving instructor's observation rating of driving performance

OBJECTIVES Evidence increases that cognitive failure may be used to screen for drivers at risk. Until now, most studies have relied on driving learners. This exploratory pilot study examines self-report of cognitive failure in driving beginners and error during real driving as observed by driving instructors. METHODS Forty-two driving learners of 14 driving instructors filled out a work-related cognitive failure questionnaire. Driving instructors observed driving errors during the next driving lesson. In multiple linear regression analysis, driving errors were regressed on cognitive failure with the number of driving lessons as an estimator of driving experience controlled. RESULTS Higher cognitive failure predicted more driving errors (p < .01) when age, gender and driving experience were controlled in analysis. CONCLUSIONS Cognitive failure was significantly associated with observed driving errors. Systematic research on cognitive failure in driving beginners is recommended.

Dopamine-related deficit in reward learning after catecholamine depletion in unmedicated, remitted subjects with bulimia nervosa

Disturbances in reward processing have been implicated in bulimia nervosa (BN). Abnormalities in processing reward-related stimuli might be linked to dysfunctions of the catecholaminergic neurotransmitter system, but findings have been inconclusive. A powerful way to investigate the relationship between catecholaminergic function and behavior is to examine behavioral changes in response to experimental catecholamine depletion (CD). The purpose of this study was to uncover putative catecholaminergic dysfunction in remitted subjects with BN who performed a reinforcement-learning task after CD. CD was achieved by oral alpha-methyl-para-tyrosine (AMPT) in 19 unmedicated female subjects with remitted BN (rBN) and 28 demographically matched healthy female controls (HC). Sham depletion administered identical capsules containing diphenhydramine. The study design consisted of a randomized, double-blind, placebo-controlled crossover, single-site experimental trial. The main outcome measures were reward learning in a probabilistic reward task analyzed using signal-detection theory. Secondary outcome measures included self-report assessments, including the Eating Disorder Examination-Questionnaire. Relative to healthy controls, rBN subjects were characterized by blunted reward learning in the AMPT-but not in placebo-condition. Highlighting the specificity of these findings, groups did not differ in their ability to perceptually distinguish between stimuli. Increased CD-induced anhedonic (but not eating disorder) symptoms were associated with a reduced response bias toward a more frequently rewarded stimulus. In conclusion, under CD, rBN subjects showed reduced reward learning compared with healthy control subjects. These deficits uncover disturbance of the central reward processing systems in rBN related to altered brain catecholamine levels, which might reflect a trait-like deficit increasing vulnerability to BN.

Connectionism as metaphor: Towards an integrated, unified conception of self-system and individual difference

Comments on an article by Kashima et al. (see record 2007-10111-001). In their target article Kashima and colleagues try to show how a connectionist model conceptualization of the self is best suited to capture the self's temporal and socio-culturally contextualized nature. They propose a new model and to support this model, the authors conduct computer simulations of psychological phenomena whose importance for the self has long been clear, even if not formally modeled, such as imitation, and learning of sequence and narrative. As explicated when we advocated connectionist models as a metaphor for self in Mischel and Morf (2003), we fully endorse the utility of such a metaphor, as these models have some of the processing characteristics necessary for capturing key aspects and functions of a dynamic cognitive-affective self-system. As elaborated in that chapter, we see as their principal strength that connectionist models can take account of multiple simultaneous processes without invoking a single central control. All outputs reflect a distributed pattern of activation across a large number of simple processing units, the nature of which depends on (and changes with) the connection weights between the links and the satisfaction of mutual constraints across these links (Rummelhart & McClelland, 1986). This allows a simple account for why certain input features will at times predominate, while others take over on other occasions. (PsycINFO Database Record (c) 2008 APA, all rights reserved)

Radiation metabolomics. 3. Biomarker discovery in the urine of gamma-irradiated rats using a simplified metabolomics protocol of gas chromatography-mass spectrometry combined with random forests machine learning algorithm

Abstract Radiation metabolomics employing mass spectral technologies represents a plausible means of high-throughput minimally invasive radiation biodosimetry. A simplified metabolomics protocol is described that employs ubiquitous gas chromatography-mass spectrometry and open source software including random forests machine learning algorithm to uncover latent biomarkers of 3 Gy gamma radiation in rats. Urine was collected from six male Wistar rats and six sham-irradiated controls for 7 days, 4 prior to irradiation and 3 after irradiation. Water and food consumption, urine volume, body weight, and sodium, potassium, calcium, chloride, phosphate and urea excretion showed major effects from exposure to gamma radiation. The metabolomics protocol uncovered several urinary metabolites that were significantly up-regulated (glyoxylate, threonate, thymine, uracil, p-cresol) and down-regulated (citrate, 2-oxoglutarate, adipate, pimelate, suberate, azelaate) as a result of radiation exposure. Thymine and uracil were shown to derive largely from thymidine and 2'-deoxyuridine, which are known radiation biomarkers in the mouse. The radiation metabolomic phenotype in rats appeared to derive from oxidative stress and effects on kidney function. Gas chromatography-mass spectrometry is a promising platform on which to develop the field of radiation metabolomics further and to assist in the design of instrumentation for use in detecting biological consequences of environmental radiation release.

Evaluating retraining rules for semi-supervised learning in neural network based cursive word recognition

Training a system to recognize handwritten words is a task that requires a large amount of data with their correct transcription. However, the creation of such a training set, including the generation of the ground truth, is tedious and costly. One way of reducing the high cost of labeled training data acquisition is to exploit unlabeled data, which can be gathered easily. Making use of both labeled and unlabeled data is known as semi-supervised learning. One of the most general versions of semi-supervised learning is self-training, where a recognizer iteratively retrains itself on its own output on new, unlabeled data. In this paper we propose to apply semi-supervised learning, and in particular self-training, to the problem of cursive, handwritten word recognition. The special focus of the paper is on retraining rules that define what data are actually being used in the retraining phase. In a series of experiments it is shown that the performance of a neural network based recognizer can be significantly improved through the use of unlabeled data and self-training if appropriate retraining rules are applied.

Governing individual learning in the transition phase of software maintenance offshoring: a dynamic perspective

Prior studies suggest that clients need to actively govern knowledge transfer to vendor staff in offshore outsourcing. In this paper, we analyze longitudinal data from four software maintenance offshore out-sourcing projects to explore why governance may be needed for knowledge transfer and how governance and the individual learning of vendor engineers inter-act over time. Our results suggest that self-control is central to learning, but may be hampered by low levels of trust and expertise at the outset of projects. For these foundations to develop, clients initially need to exert high amounts of formal and clan controls to enforce learning activities against barriers to knowledge sharing. Once learning activities occur, trust and expertise increase and control portfolios may show greater emphases on self-control.