Insufficient Effort Responding in Surveys Assessing Self-Regulated Learning: Nuisance or Fatal Flaw?

Despite concerns about their validity, self-report surveys remain the primary data collection method in the research of self-regulated learning (SRL). To address some of these concerns, we took a data set comprised of college students’ self-reported beliefs and behaviours related to SRL, assessed across three surveys, and examined it for instance of a specific threat to validity, insufficient effort responding (IER; Huang, Curran, Keeny, Poposki, & DeShon, 2012). Using four validated indicators of IER, we found the rate of IER to vary between 12-16%. Critically, while we found that students characterised as inattentive and attentive differed in some basic descriptive statistics, the inclusion of inattentive students within the data set did not alter more substantial inferences or conclusions drawn from the data. This study provides the first direct examination of the impact of respondents’ attention on the validity of SRL data generated from self-report surveys

Activity monitoring in patients with depression : A systematic review

Copyright © 2012 Elsevier B.V. All rights reserved.Peer reviewedPreprin

Self-regulation of Time: the Importance of Time Estimation Accuracy

Time management is one central aspect of students’ self-regulated learning. In addition, biased time estimation seems to be central to students’ self-regulation of their time. In this study, we explored college students’ time estimation bias. In addition, we were interested in whether the activation of task beliefs influenced students’ time estimation bias and how specific beliefs about task difficulty influence time estimation bias. Findings suggested that students tended to demonstrate bias in their estimations of the time their academic tasks would take. Additionally, the activation of task beliefs did not influence students’ time estimation accuracy. Finally, both prior task difficulty and anticipated difficulty influenced students’ time estimation bias. These findings highlight the complexity of students’ time estimation bias and point to the opportunities for future directions

Biologically Plausible Learning on Neuromorphic Hardware Architectures

With an ever-growing number of parameters defining increasingly complex networks, Deep Learning has led to several breakthroughs surpassing human performance. As a result, data movement for these millions of model parameters causes a growing imbalance known as the memory wall. Neuromorphic computing is an emerging paradigm that confronts this imbalance by performing computations directly in analog memories. On the software side, the sequential Backpropagation algorithm prevents efficient parallelization and thus fast convergence. A novel method, Direct Feedback Alignment, resolves inherent layer dependencies by directly passing the error from the output to each layer. At the intersection of hardware/software co-design, there is a demand for developing algorithms that are tolerable to hardware nonidealities. Therefore, this work explores the interrelationship of implementing bio-plausible learning in-situ on neuromorphic hardware, emphasizing energy, area, and latency constraints. Using the benchmarking framework DNN+NeuroSim, we investigate the impact of hardware nonidealities and quantization on algorithm performance, as well as how network topologies and algorithm-level design choices can scale latency, energy and area consumption of a chip. To the best of our knowledge, this work is the first to compare the impact of different learning algorithms on Compute-In-Memory-based hardware and vice versa. The best results achieved for accuracy remain Backpropagation-based, notably when facing hardware imperfections. Direct Feedback Alignment, on the other hand, allows for significant speedup due to parallelization, reducing training time by a factor approaching N for N-layered networks

Contextual differences in student motivation and self-regulated learning in mathematics, English, and social studies classrooms

Recent research on self-regulated learning has stressed the importance of both motivational and cognitive components of classroom learning. Much of this research has examined these components without consideration of potential contextual differences. Using a within-subject correlational design, the present study assessed mean level differences in students' task value, self-efficacy, test anxiety, cognitive strategy use, regulatory strategy use, and classroom academic performance by gender and across the subject areas of mathematics, social studies, and English. In addition, the relations among the motivational, strategy use, and performance measures were assessed using multivariate regressions. The participants were 545 seventh and eighth grade students (51% females) who responded to a self-report questionnaire. Results revealed mean level differences by subject area and gender in the motivation and cognitive strategy use variables, but not in regulatory strategy use or academic performance. In contrast, results indicated that the relations among these constructs was very similar across the three subject areas examined. Findings are discussed in terms of their importance for understanding the contextual nature of students' self-regulated learning.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/43860/1/11251_2004_Article_136746.pd

Emission from quantum-dot high-β microcavities : transition from spontaneous emission to lasing and the effects of superradiant emitter coupling

The research is funded in part by the European Research Council under the Seventh Framework ERC Grant Agreement No. 615613 of the European Union, the German Research Foundation via the projects RE2974/5-1, Ka2318 7-1 and JA 619/10-3, and the U.S. Department of Energy under Contract No. DE-AC04-94AL85000. CG and FJ gratefully acknowledge financial support from the German Science Foundation (DFG). FJ further acknowledges support from the German Federal Ministry of Education and Research (BMBF).Measured and calculated results are presented for the emission properties of a new class of emitters operating in the cavity quantum electrodynamics regime. The structures are based on high-finesse GaAs/AlAs micropillar cavities, each with an active medium consisting of a layer of InGaAs quantum dots and the distinguishing feature of having a substantial fraction of spontaneous emission channeled into one cavity mode (high β-factor). This paper demonstrates that the usual criterion for lasing with a conventional (low β-factor) cavity, that is, a sharp non-linearity in the input-output curve accompanied by noticeable linewidth narrowing, has to be reinforced by the equal-time second-order photon autocorrelation function to confirm lasing. The paper also shows that the equal-time second-order photon autocorrelation function is useful for recognizing superradiance, a manifestation of the correlations possible in high-β microcavities operating with quantum dots. In terms of consolidating the collected data and identifying the physics underlying laser action, both theory and experiment suggest a sole dependence on intracavity photon number. Evidence for this assertion comes from all our measured and calculated data on emission coherence and fluctuation, for devices ranging from light emitting diodes (LEDs) and cavity-enhanced LEDs to lasers, lying on the same two curves: one for linewidth narrowing versus intracavity photon number and the other for g(2)(0) versus intracavity photon number.Publisher PDFPeer reviewe

Measurement requirements for a near-Earth asteroid impact mitigation demonstration mission

A concept for an Impact Mitigation Preparation Mission, called Don Quijote, is to send two spacecraft to a Near-Earth Asteroid (NEA): an Orbiter and an Impactor. The Impactor collides with the asteroid while the Orbiter measures the resulting change in the asteroid's orbit, by means of a Radio Science Experiment (RSE) carried out before and after impact. Three parallel Phase A studies on Don Quijote were carried out for the European Space Agency: the research presented here reflects outcomes of the study by QinetiQ. We discuss the mission objectives with regards to the prioritisation of payload instruments, with emphasis on the interpretation of the impact. The Radio Science Experiment is described and it is examined how solar radiation pressure may increase the uncertainty in measuring the orbit of the target asteroid. It is determined that to measure the change in orbit accurately a thermal IR spectrometer is mandatory, to measure the Yarkovsky effect. The advantages of having a laser altimeter are discussed. The advantages of a dedicated wide-angle impact camera are discussed and the field-of-view is initially sized through a simple model of the impact.Comment: 28 page