351 research outputs found

    Carelessness and Affect in an Intelligent Tutoring System for Mathematics

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    We investigate the relationship between students’ affect and their frequency of careless errors while using an Intelligent Tutoring System for middle school mathematics. A student is said to have committed a careless error when the student’s answer is wrong despite knowing the skill required to provide the correct answer. We operationalize the probability that an error is careless through the use of an automated detector, developed using educational data mining, which infers the probability that an error involves carelessness rather than not knowing the relevant skill. This detector is then applied to log data produced by high-school students in the Philippines using a Cognitive Tutor for scatterplots. We study the relationship between carelessness and affect, triangulating between the detector of carelessness and field observations of affect. Surprisingly, we find that carelessness is common among students who frequently experience engaged concentration. This finding implies that a highly engaged student may paradoxically become overconfident or impulsive, leading to more careless errors. In contrast, students displaying confusion or boredom make fewer careless errors. Further analysis over time suggests that confused and bored students have lower learning overall. Thus, their mistakes appear to stem from a genuine lack of knowledge rather than carelessness

    Generalization of the K-SVD algorithm for minimization of ß-divergence

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    [EN] In this paper, we propose, describe, and test a modification of the K-SVD algorithm. Given a set of training data, the proposed algorithm computes an overcomplete dictionary by minimizing the ß-divergence () between the data and its representation as linear combinations of atoms of the dictionary, under strict sparsity restrictions. For the special case , the proposed algorithm minimizes the Frobenius norm and, therefore, for the proposed algorithm is equivalent to the original K-SVD algorithm. We describe the modifications needed and discuss the possible shortcomings of the new algorithm. The algorithm is tested with random matrices and with an example based on speech separation.This work has been partially supported by the EU together with the Spanish Government through TEC2015-67387-C4-1-R (MINECO/FEDER) and by Programa de FPU del Ministerio de Educacion, Cultura y Deporte FPU13/03828 (Spain).García Mollá, VM.; San Juan-Sebastian, P.; Virtanen, T.; Vidal Maciá, AM.; Alonso-Jordá, P. (2019). Generalization of the K-SVD algorithm for minimization of ß-divergence. Digital Signal Processing. 92:47-53. https://doi.org/10.1016/j.dsp.2019.05.001S47539

    Improving small area estimation by combining surveys : new perspectives in regional statistics

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    A national survey designed for estimating a specific population quantity is sometimes used for estimation of this quantity also for a small area, such as a province. Budget constraints do not allow a greater sample size for the small area, and so other means of improving estimation have to be devised. We investigate such methods and assess them by a Monte Carlo study. We explore how a complementary survey can be exploited in small area estimation. We use the context of the Spanish Labour Force Survey (EPA) and the Barometer in Spain for our study

    Discovering duplicate tasks in transition systems for the simplification of process models

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    This work presents a set of methods to improve the understandability of process models. Traditionally, simplification methods trade off quality metrics, such as fitness or precision. Conversely, the methods proposed in this paper produce simplified models while preserving or even increasing fidelity metrics. The first problem addressed in the paper is the discovery of duplicate tasks. A new method is proposed that avoids overfitting by working on the transition system generated by the log. The method is able to discover duplicate tasks even in the presence of concurrency and choice. The second problem is the structural simplification of the model by identifying optional and repetitive tasks. The tasks are substituted by annotated events that allow the removal of silent tasks and reduce the complexity of the model. An important feature of the methods proposed in this paper is that they are independent from the actual miner used for process discovery.Peer ReviewedPostprint (author's final draft

    Carelessness and Affect in an Intelligent Tutoring System for Mathematics

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    We investigate the relationship between students' affect and their frequency of careless errors while using an Intelligent Tutoring System for middle school mathematics. A student is said to have committed a careless error when the student's answer is wrong despite knowing the skill required to provide the correct answer. We operationalize the probability that an error is careless through the use of an automated detector, developed using educational data mining, which infers the probability that an error involves carelessness rather than not knowing the relevant skill. This detector is then applied to log data produced by high-school students in the Philippines using a Cognitive Tutor for scatterplots. We study the relationship between carelessness and affect, triangulating between the detector of carelessness and field observations of affect. Surprisingly, we find that carelessness is common among students who frequently experience engaged concentration. This finding implies that a highly engaged student may paradoxically become overconfident or impulsive, leading to more careless errors. In contrast, students displaying confusion or boredom make fewer careless errors. Further analysis over time suggests that confused and bored students have lower learning overall. Thus, their mistakes appear to stem from a genuine lack of knowledge rather than carelessness

    How teachers' practices and students' attitudes towards technology affect mathematics achievement: results and insights from PISA 2012

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    The present work seeks to deepen the impact of factors linked to the characteristics of teaching practices and students' attitudes towards the use of technology on their performance in mathematics in the process of teaching-learning in the Spanish context. In this sense, this study is a secondary analysis of the PISA 2012 data. Therefore, it is an ex post facto design. Regarding the attitudes and the contextual variables, the results do coincide with the accumulated evidence. However, once these contextual effects have been controlled for, the negative relationship found between the pedagogic strategies used by the teachers and the mathematics score cannot but convey perplexity, since the results relative to student-oriented, formative assessment and teacher-directed instruction are clearly contradictory to the solid previous evidence. The data do not allow us to explain this paradoxical result. We dare to point to a conjecture that we find plausible. All these complex variables are informed through questionnaires responded to by students and require a great degree of inference in the answers. Future studies must consider the complexity of the measured variables as well as the students' perception and understanding of them

    Improvement of regeneration in pepper: a recalcitrant species

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    [EN] Organogenesis is influenced by factors like genotype, type of explant, culture medium components, and incubation conditions. The influence of ethylene, which can be produced in the culture process, can also be a limiting factor in recalcitrant species like pepper. In this work, bud induction was achieved from cotyledons and hypocotyls-from eight pepper cultivars-on Murashige and Skoog (MS) medium supplemented with 22.2 mu M 6-benzyladenine (6BA) and 5.71 mu M indole-3-acetic acid (IAA), in media with or without silver nitrate (SN) (58.86 mu M), a suppressor of ethylene action. In the SN-supplemented medium, the frequencies of explants with buds and with callus formation were lower in both kinds of explant, but higher numbers of developed shoots were isolated from explants cultured on SN. Bud elongation was better in medium with gibberellic acid (GA(3)) (2.88 mu M) than in medium free of growth regulators or supplemented with 1-aminocyclopropane-1-carboxylic acid (ACC) at 34.5 mu M. However, isolation of shoots was difficult and few plants were recovered. The effect of adding SN following bud induction (at 7 d) and that of dark incubation (the first 7 d of culture) was also assessed in order to improve the previous results. When SN was added after bud induction, similar percentages of bud induction were found for cotyledons (average frequency 89.37% without SN and 94.37% with SN) whereas they doubled in hypocotyls (50% without SN and 87.7% with SN). In addition, in both kinds of explant, the number of developed plants able to be transferred to soil (developed and rooted) was greatly increased by SN. Dark incubation does not seem to improve organogenesis in pepper, and hypocotyl explants clearly represent a better explant choice-with respect to cotyledonary explants-for the pepper cultivars assayed.We thank the COMAV germplasm bank at Universitat Politecnica de Valencia and the Arid Lands Institute for pepper seeds and the Tunisian Ministry of Higher Education and Scientific Research who fund N. Gammoudi's stay.Gammoudi, N.; San Pedro-Galan, T.; Ferchichi, A.; Gisbert Domenech, MC. (2018). Improvement of regeneration in pepper: a recalcitrant species. In Vitro Cellular & Developmental Biology - Plant. 54(2):145-153. https://doi.org/10.1007/s11627-017-9838-1S145153542Ashrafuzzaman M, Hossain MM, Razi Ismail M, Shahidul Haque M, Shahidullah SM, Uz Zaman S (2009) Regeneration potential of seedling explants of chilli (Capsicum annuum). Afr J Biotechnol 8:591–596Bortesi L, Fischer R (2015) The CRISPR/Cas9 system for plant genome editing and beyond. 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    Essential versus accessory aspects of cell death: recommendations of the NCCD 2015

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    Cells exposed to extreme physicochemical or mechanical stimuli die in an uncontrollable manner, as a result of their immediate structural breakdown. Such an unavoidable variant of cellular demise is generally referred to as ‘accidental cell death’ (ACD). In most settings, however, cell death is initiated by a genetically encoded apparatus, correlating with the fact that its course can be altered by pharmacologic or genetic interventions. ‘Regulated cell death’ (RCD) can occur as part of physiologic programs or can be activated once adaptive responses to perturbations of the extracellular or intracellular microenvironment fail. The biochemical phenomena that accompany RCD may be harnessed to classify it into a few subtypes, which often (but not always) exhibit stereotyped morphologic features. Nonetheless, efficiently inhibiting the processes that are commonly thought to cause RCD, such as the activation of executioner caspases in the course of apoptosis, does not exert true cytoprotective effects in the mammalian system, but simply alters the kinetics of cellular demise as it shifts its morphologic and biochemical correlates. Conversely, bona fide cytoprotection can be achieved by inhibiting the transduction of lethal signals in the early phases of the process, when adaptive responses are still operational. Thus, the mechanisms that truly execute RCD may be less understood, less inhibitable and perhaps more homogeneous than previously thought. Here, the Nomenclature Committee on Cell Death formulates a set of recommendations to help scientists and researchers to discriminate between essential and accessory aspects of cell death
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