Interspersing easy math problems among challenging problems: detection of interspersal effects in whole-class applications

Interspersing easy problems among challenging problems has been shown to both increase students’ preference for completing math worksheets and the fluency with which they complete challenging problems. Although early research examining the interspersal procedure in mathematics was conducted with college-age students, there are a growing number of studies utilizing the interspersal procedure in elementary and secondary school settings. A particular concern with existing research however is whether the beneficial effects are maintained across multiple sessions and whether effects generalize when implemented with large groups of students. The current study addressed this concern by administering both control and interspersal math worksheets consisting of instructionally relevant problems to 75 fourth grade students across four sessions. Because students’ instructional levels differed, analyses were conducted separately for students identified as fluent and less fluent based upon student performance on the control worksheet administered during session 1. Dependent measures included digits correct and problems correct as well as students’ responses to four preference questions following each session. Although results differ from previous research in that students completed significantly more digits correct on control worksheets, explanations of these differences are examined and implications are discussed.     

Against digital ontology

The paper argues that digital ontology (the ultimate nature of reality is digital, and the universe is a computational system equivalent to a Turing Machine) should be carefully distinguished from informational ontology (the ultimate nature of reality is structural), in order to abandon the former and retain only the latter as a promising line of research. Digital vs. analogue is a Boolean dichotomy typical of our computational paradigm, but digital and analogue are only “modes of presentation” of Being (to paraphrase Kant), that is, ways in which reality is experienced or conceptualised by an epistemic agent at a given level of abstraction. A preferable alternative is provided by an informational approach to structural realism, according to which knowledge of the world is knowledge of its structures. The most reasonable ontological commitment turns out to be in favour of an interpretation of reality as the totality of structures dynamically interacting with each other. The paper is the first part (the pars destruens) of a two-part piece of research. The pars construens, entitled “A Defence of Informational Structural Realism”, is developed in a separate article, also published in this journal.     

The effects on classifier performance of 2D discrete wavelet transform analysis and whale optimization algorithm for recognition of power quality disturbances

Power Quality (PQ) is becoming more and more important day by day in the electric network. Signal processing, pattern recognition and machine learning are increasingly being studied for the automatic recognition of any disturbances that may occur during the generation, transmission, and distribution of electricity. There are three main steps to identify the PQ disturbances. These include the use of signal processing methods to calculate the features representing the disturbances, the selection of those that are more useful than these feature sets to prevent the creation of a complex classification model, the creating a classification model that recognizes multiple classes using the selected feature subsets. In this study, one-dimensional (1D) PQ disturbances signals are transformed into two-dimensional (2D) signals, 2D discrete wavelet transforms (2D-DWT) are used to extract the features. The features are extracted by using the wavelet families such as Daubechies, Biorthogonal, Symlets, Coiflets and Fejer-Korovkin in 2D-DWT to analyze PQ disturbances. Whale Optimization Algorithm (WOA) and k-nearest neighbor (KNN) classifier determine the feature subsets. Then, WOA and k nearest neighbor (KNN) classifier are used to determine the feature group. By using KNN and Support Vector Machines (SVM) classification methods, Classifier models that distinguish PQ disturbances are formed. The main aim of the study is to determine the features derived from 2D wavelet coefficients for different wavelet families and to determine which of them has a better classification performance to distinguish PQ disturbances signals. At the same time, different classification methods are simulated and a model which can classify PQ disturbances signals with high performance is created. Also, the generated models are analysed for their performance in terms of different noise levels (40 dB, 30 dB, 20 dB). The result of this simulation study shows that the model developed to classify PQ disturbances is superior to conventional models and other 2D signal processing methods in the literature. In addition, it was concluded that the proposed method can cope better with noisy signals by low computational complexity and higher classification rate.     

Construction of CCZ transform for quadratic APN functions

Almost perfect nonlinear (APN) function is an important type of function in cryptography, especially quadratic APN function. Since the notion of CCZ-equivalence developed, the construction of CCZ transform for APN functions to obtain new APN functions became a critical issue in cryptography. Inspired by the result of Budaghyan who used Gold functions, this article gives the construction of CCZ transform for all quadratic vectorial Boolean functions and proves that for quadratic APN functions, the functions transformed have algebraic degree 3, thus EA-inequivalent to all quadratic functions, and have minimum algebraic degree 2, thus EA-inequivalent to all power functions.     

利用时频分析研究非相位锁定脑电活动

时频分析技术自20世纪80年代被引入到心理学脑电数据分析领域以来, 克服了传统的时域ERP方法只能分析相位锁定成分的缺陷, 可以帮助研究者挖掘到脑电信号中非相位锁定的成分。在心理学领域, 应用最多的时频分析方法是小波变换和Hilbert变换, 而能量、相位一致性和耦合是三个最常用的分析指标。研究者利用不同的分析指标来揭示不同的心智过程。不同频段的能量被认为体现了不同的认知过程, 如α能量被发现与注意选择性有关, 而γ能量则与特征整合相关。相位一致性常被用于讨论ERP产生的机制。耦合则通常说明了长距离脑区之间的信息交流以及高级脑区对低级脑区的认知控制, 在完成各种复杂认知任务的时候会表现出不同的耦合模式。     

The perceptions of social context (PoSC): Introducing the PoSC scale

IntroductionThe Perception of Social Context refers to the perceptions that workers have of (1) the immediate supervisor, (2) the colleagues, and (3) top management of their organization.ObjectiveThe purpose of the present paper is to introduce the Perceptions of Social Context (PoSC) scale, an instrument for assessing workers’ perception of their social context.MethodWe used three studies (N total = 960) to test the internal, external, convergent, and predictive validity of the PoSC, as well as its reliability.ResultsIn Study 1, the hypothesized three-factor structure was empirically tested and supported by means of exploratory structural equation modeling. Study 2 provided further support for the factorial structure of the scale and evidence for its convergent and external validity in relation to important organizational variables. Study 3 provided evidence for the predictive validity with respect to job satisfaction and performance.ConclusionEstablished validity allows the PoSC scale to be used to specifically detect behaviors enacted by key social constituents and thus to plan specific and therefore more effective interventions.     

Testing the conditional independence and monotonicity assumptions of item response theory

When item characteristic curves are nondecreasing functions of a latent variable, the conditional or local independence of item responses given the latent variable implies nonnegative conditional covariances between all monotone increasing functions of a set of item responses given any function of the remaining item responses. This general result provides a basis for testing the conditional independence assumption without first specifying a parametric form for the nondecreasing item characteristic curves. The proposed tests are simple, have known asymptotic null distributions, and possess certain optimal properties. In an example, the conditional independence hypothesis is rejected for all possible forms of monotone item characteristic curves.The author acknowledges Paul W. Holland for valuable conversations on the subject of this paper; Henry Braun and Fred Lord for comments at a presentation on this subject which led to improvements in the paper; Carl H. Haag for permission to use the data in §4; Bruce Kaplan for assistance with computing; and two referees for helpful suggestions. Requests for reprints should be sent to Paul R. Rosenbaum     

The determinants of Portuguese preference for vehicle automation: A descriptive and explanatory study

During the last century, innovation of automated vehicles (AVs) technologies are successively maturing while progressively excluding the human intervention in vehicle driving. The objective of this paper was to analyze the determinants of Portuguese drivers’ decision to adopt AVs technologies, in an under explored context, where the driver of contemporary vehicles does all or part of the dynamic driving task (DDT) in comparison to vehicles equipped with Automated Driving systems (ADS) where the driver can become a passenger temporarily or permanently. In addition, willingness-to-pay for ADS estimates were also investigated. This study data was collected through a survey designed and deployed in Portugal. A mixed logit model was estimated, and the results obtained are in line with the literature of AVs in a number of determinants, but also highlights differences that can be explained by the Portuguese cultural, social and economic context. Overall, 83.7% of the Portuguese drivers favor contemporary vehicles, today, and among those who prefer vehicles with ADS, highly educated drivers’ are willing to pay, on average, 65,671 € for Conditional AVs, 31,185 € for Highly AVs, and about 28,622 € for Full AVs.     

Transforming continuous utility into additive utility using kolmogorov's theorem

For a multidimensional criteria space to have an additive utility function, the strong condition of independence among the co-ordinates (also known as separability) must be satisfied. However, if we are allowed to transform the criteria space into another, then a theorem due to Kolmogorov implies that we can, even in the absence of independence, transform the space into one that has a continuous additive utility function. Since this transformation is complex, it has only theoretical significance. However, certain related results from neurocomputing theory are quite practical and signify that there exists some scope for neurocomputing in multi-criteria decision analysis.