Search results for " learning"

Caracterización del curriculum evaluado en matemática en sexto año básico. Un estudio descriptivo en Valparaíso, Chile

2014

Este artículo pretende dar cuenta de los principales resultados de la investigación denominada Caracterización del curriculum evaluado en sexto año básico en matemática: orientaciones para la formación inicial y continua de profesores y profesoras, cuyo objetivo principal fue describir y analizar lo que se evalúa y cómo se evalúa en matemática en dicho nivel en la región de Valparaíso, Chile. Se analizaron 103 pruebas escritas de matemática conducentes a calificación, pertenecientes a 27 establecimientos educacionales. A dichas pruebas, y a sus respectivas 2516 preguntas, se les aplicó un conjunto de códigos referido tanto a aspectos formales como de contenidos y habilidades matemáticas. S…

3D Matrix-Based Visualization System of Association Rules

2017

With the growing number of mining datasets, it becomes increasingly difficult to explore interesting rules because of the large number of resultant and its nature complexity. Studies on human perception and intuition show that graphical representation could be a better illustration of how to seek information from the data using the capabilities of human visual system. In this work, we present and implement a 3D matrix-based approach visualization system of association rules. The main visual representation applies the extended matrix-based approach with rule-to-items mapping to general transaction data set. A novel method merging rules and assigning weight is proposed in order to reduce the …

Discovering representative models in large time series databases

2004

The discovery of frequently occurring patterns in a time series could be important in several application contexts. As an example, the analysis of frequent patterns in biomedical observations could allow to perform diagnosis and/or prognosis. Moreover, the efficient discovery of frequent patterns may play an important role in several data mining tasks such as association rule discovery, clustering and classification. However, in order to identify interesting repetitions, it is necessary to allow errors in the matching patterns; in this context, it is difficult to select one pattern particularly suited to represent the set of similar ones, whereas modelling this set with a single model could…

Predicting hospital associated disability from imbalanced data using supervised learning.

2019

Hospitalization of elderly patients can lead to serious adverse effects on their functional capability. Identifying the underlying factors leading to such adverse effects is an active area of medical research. The purpose of the current paper is to show the potential of artificial intelligence in the form of machine learning to complement the existing medical research. This is accomplished by studying the outcome of hospitalization of elderly patients as a supervised learning task. A rich set of features characterizing the medical and social situation of elderly patients is leveraged and using confusion matrices, association rule mining, and two different classes of supervised learning algo…

Analyzing the Correlation of Classical and Community-aware Centrality Measures in Complex Networks

2021

International audience; Identifying influential nodes in social networks is a fundamental issue. Indeed, it has many applications, such as inhibiting epidemic spreading, accelerating information diffusion, preventing terrorist attacks, and much more. Classically, centrality measures quantify the node's importance based on various topological properties of the network, such as Degree and Betweenness. Nonetheless, these measures are agnostic of the community structure, although it is a ubiquitous characteristic encountered in many real-world networks. To overcome this drawback, there is a growing trend to design so-called community-aware centrality measures. Although several works investigate…

A machine learning examination of hydroxyl radical differences among model simulations for CCMI-1

2020

The hydroxyl radical (OH) plays critical roles within the troposphere, such as determining the lifetime of methane (CH4), yet is challenging to model due to its fast cycling and dependence on a multitude of sources and sinks. As a result, the reasons for variations in OH and the resulting methane lifetime (τCH4), both between models and in time, are difficult to diagnose. We apply a neural network (NN) approach to address this issue within a group of models that participated in the Chemistry-Climate Model Initiative (CCMI). Analysis of the historical specified dynamics simulations performed for CCMI indicates that the primary drivers of τCH4 differences among 10 models are the flux of UV li…

Assessment of maize nitrogen uptake from PRISMA hyperspectral data through hybrid modelling

2022

Variété des usages et inégalités d'accès à la formation continue

2005

La formation professionnelle continue est rarement abordée du point de vue de la personne qui se forme. C'est cette approche originale que propose l'enquête Formation continue 2000. Son intérêt est d'observer l'attitude des individus face à la formation continue, leurs contraintes et leurs pratiques. Plus que l'envie personnelle, les propositions et les critères de sélection de l'entreprise ont une réelle influence sur l'accès à la formation des salarié-es. De plus, cette enquête permet d'éclairer les raisons et les circonstances, racontées par les personnes elles-mêmes, qui ont conduit à une absence de formation.

Hands-On Math and Art Exhibition Promoting Science Attitudes and Educational Plans

2017

The current science, technology, engineering, art, math education (STEAM) approach emphasizes integration of abstract science and mathematical ideas for concrete solutions by art. The main aim was to find out how experience of learning mathematics differed between the contexts of school and an informal Math and Art Exhibition. The study participants (N=256) were 12-13 years old from Finland. Several valid questionnaires and tests were applied (e.g., SRQ-A, RAVEN) in pre- and postdesign showing a good reliability. The results based on General Linear Modeling and Structural Equation Path Modeling underline the motivational effects. The experience of the effectiveness of hands-on learning at s…

The Influence of Task and Context-Based Complexity on the Final Choice

2011

In this chapter, we present a new approach for the design of choice task experiments that analyze the final respondent’s choice but not the decision process.1 The approach creates choice tasks with a one-to-one correspondence between decision strategies and the observed choices. Thus, a decision strategy used is unambiguously deduced from an observed choice. Furthermore, the approach systematically manipulates the characteristics of choice tasks and takes into account measurement errors concerning the preferences of the decision makers. We use this approach to generate respondent-specific choice tasks with either low or high complexity and study their influence on the use of compensatory an…