Spelling suggestions: "subject:"causal inference"" "subject:"kausal inference""
1 |
The application of language-game theory to the analysis of science learning: developing an interpretive classroom-level learning frameworkAhmadibasir, Mohammad 01 July 2011 (has links)
In this study an interpretive learning framework that aims to measure learning on the classroom level is introduced. In order to develop and evaluate the value of the framework, a theoretical/empirical study is designed. The researcher attempted to illustrate how the proposed framework provides insights on the problem of classroom-level learning. The framework is developed by construction of connections between the current literature on science learning and Wittgenstein's language-game theory. In this framework learning is defined as change of classroom language-game or discourse. In the proposed framework, learning is measured by analysis of classroom discourse. The empirical explanation power of the framework is evaluated by applying the framework in the analysis of learning in a fifth-grade science classroom. The researcher attempted to analyze how students' colloquial discourse changed to a discourse that bears more resemblance to science discourse. The results of the empirical part of the investigation are presented in three parts: first, the gap between what students did and what they were supposed to do was reported. The gap showed that students during the classroom inquiry wanted to do simple comparisons by direct observation, while they were supposed to do tool-assisted observation and procedural manipulation for a complete comparison. Second, it was illustrated that the first attempt to connect the colloquial to science discourse was done by what was immediately intelligible for students and then the teacher negotiated with students in order to help them to connect the old to the new language-game more purposefully. The researcher suggested that these two events in the science classroom are critical in discourse change. Third, it was illustrated that through the academic year, the way that students did the act of comparison was improved and by the end of the year more accurate causal inferences were observable in classroom communication. At the end of the study, the researcher illustrates that the application of the proposed framework resulted in an improved version of the framework. The improved version of the proposed framework is more connected to the topic of science learning, and is able to measure the change of discourse in higher resolution.
|
2 |
Efficient Algorithms for Learning Combinatorial Structures from Limited DataAsish Ghoshal (5929691) 15 May 2019 (has links)
<div>Recovering combinatorial structures from noisy observations is a recurrent problem in many application domains, including, but not limited to, natural language processing, computer vision, genetics, health care, and automation. For instance, dependency parsing in natural language processing entails recovering parse trees from sentences which are inherently ambiguous. From a computational standpoint, such problems are typically intractable and call for designing efficient approximation or randomized algorithms with provable guarantees. From a statistical standpoint, algorithms that recover the desired structure using an optimal number of samples are of paramount importance.</div><div><br></div><div>We tackle several such problems in this thesis and obtain computationally and statistically efficient procedures. We demonstrate optimality of our methods by proving fundamental lower bounds on the number of samples needed by any method for recovering the desired structures. Specifically, the thesis makes the following contributions:</div><div><br></div><div>(i) We develop polynomial-time algorithms for learning linear structural equation models --- which are a widely used class of models for performing causal inference --- that recover the correct directed acyclic graph structure under identifiability conditions that are weaker than existing conditions. We also show that the sample complexity of our method is information-theoretically optimal.</div><div><br></div><div>(ii) We develop polynomial-time algorithms for learning the underlying graphical game from observations of the behavior of self-interested agents. The key combinatorial problem here is to recover the Nash equilibria set of the true game from behavioral data. We obtain fundamental lower bounds on the number of samples required for learning games and show that our method is statistically optimal.</div><div><br></div><div>(iii) Lastly, departing from the generative model framework, we consider the problem of structured prediction where the goal is to learn predictors from data that predict complex structured objects directly from a given input. We develop efficient learning algorithms that learn structured predictors by approximating the partition function and obtain generalization guarantees for our method. We demonstrate that randomization can not only improve efficiency but also generalization to unseen data.</div><div><br></div>
|
3 |
Adult Education and Full-time Professionals' Problem Solving Skills: Insights From the Survey of Adult SkillsYi, Shiya January 2020 (has links)
Thesis advisor: Henry I. Braun / Sponsored by OECD, PIAAC represents the first attempt to assess adult problem solving in technology-rich environments (PS-TRE) on an international scale that is comparable cross-culturally and cross-nationally. The objectives of this study are to study (1) the distributions of PS-TRE proficiency scores across 14 selected countries and (2) within each country, the associations between PS-TRE proficiency scores and the different formats of adult education and training (AET) participation. Using data on full-time professionals (at least 25 years old) from these countries, propensity score weighting was applied to estimate the associations between the different formats of AET participation and their PS-TRE proficiency scores. To place these estimates in context, parallel analyses were conducted – one with the sample of full-time associates in the 14 selected countries and the other with full-time professionals’ Literacy and Numeracy proficiency scores as measured by PIAAC. The results showed that after controlling for socio-demographic background, occupational categories, use of key information-processing skills (both at home and at work), as well as use of generic workplace skills, no consistent pattern was found across the 14 selected countries. At the individual country level, scattered significant relationships were identified. For example, in Denmark, both formats of AET participation (vs. None) are significantly and positively associated with full-time professionals’ PS-TRE proficiency scores and their probability of scoring in the top quartile of the PS-TRE distribution (p < .01). While in the United States, Formal AET (vs. None) is significantly and positively associated with full-time associates’ PS-TRE proficiency scores and their probability of scoring in the top quartile of the PS-TRE distribution (p < .01). The variations in relationships between the different formats of AET participation and working adults’ skills proficiency across domains and samples indicate the necessity of conducting qualitative research on AET programs in individual countries. Furthermore, to provide recommendations tailored to the specific needs of each country, a fine-grained classification of AET programs based on the OECD guideline was suggested. / Thesis (PhD) — Boston College, 2020. / Submitted to: Boston College. Lynch School of Education. / Discipline: Educational Research, Measurement and Evaluation.
|
4 |
A infer?ncia causal na filosofia moral de Hume.Jota, Renato de Medeiros 26 November 2007 (has links)
Made available in DSpace on 2014-12-17T15:12:08Z (GMT). No. of bitstreams: 1
RenatoMJ.pdf: 302842 bytes, checksum: 740d121ea6f32e914bba6e0a61a27825 (MD5)
Previous issue date: 2007-11-26 / Starting from the idea that the result of the Humean analysis of causal inferences must be applied coherently to the remaining part of his work, including its moral theory, the present master thesis aims at investigating whether Hume?s moral philosophy is essentially based on feeling, or whether this would not be rather essentially a consequence of our causal inferences in human actions and deliberations. The main idea consists in showing that our moral inferences, to the extent that they are for Hume empirical , depend on our belief in a connexion between something which has been previously observed and something which is not being observed ( but that it is expected to occur or to be observed in the future). Thus, this very belief must base our moral inferences concerning the actions and deliberations of the individuals. Therefore, must e o ipso induce us to associate actions and behaviors, as well as character and moral claims of men to certain moral feelings. Accordingly, the thesis is unfolded in three chapters. In the first chapter Hume?s theory of the perception is reported as essential part of the explanation or the principles that bind ideas in our mind and constitute our inferences. In the second chapter, the Humean analysis of causal inferences is presented and the way they contribute in the formation of our moral inferences is explained. In the third and last chapter, the formation of our moral inferences and the real contribution of the doctrine of freedom and necessity for the examination or our actions are analysed and discussed. / Partindo da id?ia de que o resultado da an?lise humeana das infer?ncias causais deve aplicar-se coerentemente ao restante de sua obra, incluindo sua teoria moral, a presente disserta??o objetiva investigar se a filosofia moral de Hume se fundamenta no sentimento, ou se isto n?o seria antes essencialmente uma
conseq??ncia de nossas infer?ncias causais. A id?ia central consiste em mostrar que nossas infer?ncias morais, na medida em que para Hume s?o emp?ricas, dependem da nossa cren?a em uma conex?o entre o que foi anteriormente observado e algo que n?o ? observado ( mas espera-se ocorrer ou observar-se no
futuro ). Assim, essa mesma cren?a fundamentaria nossas infer?ncias morais sobre as a??es dos indiv?duos, e conseq?entemente, nos levaria a associar determinados comportamentos, bem como o car?ter e as convic??es morais dos homens a certos sentimentos morais . A disserta??o desdobra-se em tr?s cap?tulos. No primeiro cap?tulo relata-se a teoria da percep??o e mostra-se que ela constitui parte essencial da explica??o das nossas infer?ncias . No segundo
cap?tulo, trata-se da an?lise das infer?ncias causais e como contribuem na forma??o das nossas infer?ncias morais. No terceiro, a partir da an?lise anterior, investiga-se a forma??o de nossas infer?ncias morais e a real contribui??o da doutrina da necessidade e da liberdade para o exame de nossas a??es.
|
5 |
Statistical inferences for missing data/causal inferences based on modified empirical likelihoodSharghi, Sima 01 September 2021 (has links)
No description available.
|
Page generated in 0.0407 seconds