Image recognition: Visual grouping, recognition, and learning

Vision extracts useful information from images. Reconstructing the three-dimensional structure of our environment and recognizing the objects that populate it are among the most important functions of our visual system. Computer vision researchers study the computational principles of vision and aim at designing algorithms that reproduce these functions. Vision is difficult: the same scene may give rise to very different images depending on illumination and viewpoint. Typically, an astronomical number of hypotheses exist that in principle have to be analyzed to infer a correct scene description. Moreover, image information might be extracted at different levels of spatial and logical resolution dependent on the image processing task. Knowledge of the world allows the visual system to limit the amount of ambiguity and to greatly simplify visual computations. We discuss how simple properties of the world are captured by the Gestalt rules of grouping, how the visual system may learn and organize models of objects for recognition, and how one may control the complexity of the description that the visual system computes.

Cue recognition and cue elaboration in learning from examples.

This paper describes the processes used by students to learn from worked-out examples and by working through problems. Evidence is derived from protocols of students learning secondary school mathematics and physics. The students acquired knowledge from the examples in the form of productions (condition-->action): first discovering conditions under which the actions are appropriate and then elaborating the conditions to enhance efficiency. Students devoted most of their attention to the condition side of the productions. Subsequently, they generalized the productions for broader application and acquired specialized productions for special problem classes.

Structure-activity relationships derived by machine learning: the use of atoms and their bond connectivities to predict mutagenicity by inductive logic programming.

We present a general approach to forming structure-activity relationships (SARs). This approach is based on representing chemical structure by atoms and their bond connectivities in combination with the inductive logic programming (ILP) algorithm PROGOL. Existing SAR methods describe chemical structure by using attributes which are general properties of an object. It is not possible to map chemical structure directly to attribute-based descriptions, as such descriptions have no internal organization. A more natural and general way to describe chemical structure is to use a relational description, where the internal construction of the description maps that of the object described. Our atom and bond connectivities representation is a relational description. ILP algorithms can form SARs with relational descriptions. We have tested the relational approach by investigating the SARs of 230 aromatic and heteroaromatic nitro compounds. These compounds had been split previously into two subsets, 188 compounds that were amenable to regression and 42 that were not. For the 188 compounds, a SAR was found that was as accurate as the best statistical or neural network-generated SARs. The PROGOL SAR has the advantages that it did not need the use of any indicator variables handcrafted by an expert, and the generated rules were easily comprehensible. For the 42 compounds, PROGOL formed a SAR that was significantly (P < 0.025) more accurate than linear regression, quadratic regression, and back-propagation. This SAR is based on an automatically generated structural alert for mutagenicity.

Brain localization for arbitrary stimulus categories: a simple account based on Hebbian learning.

A central theme of cognitive neuroscience is that different parts of the brain perform different functions. Recent evidence from neuropsychology suggests that even the processing of arbitrary stimulus categories that are defined solely by cultural conventions (e.g., letters versus digits) can become spatially segregated in the cerebral cortex. How could the processing of stimulus categories that are not innate and that have no inherent structural differences become segregated? We propose that the temporal clustering of stimuli from a given category interacts with Hebbian learning to lead to functional localization. Neural network simulations bear out this hypothesis.

Características del desarrollo de una mirada profesional en estudiantes para profesor de matemáticas en un contexto b-learning

Esta investigación presenta un estudio cuyo objetivo es identificar aspectos que apoyan el desarrollo de la mirada profesional en estudiantes para profesores de matemáticas en un contexto b-learning. Analizamos las producciones de un grupo de estudiantes para profesores de matemáticas de educación secundaria (documentos escritos y participaciones en un debate on-line) cuando analizaban el razonamiento proporcional de estudiantes de educación secundaria. Los resultados indican que la interacción en el debate en línea permitió a algunos estudiantes para profesor mejorar su capacidad de identificar e interpretar aspectos relevantes del pensamiento matemático de los estudiantes de educación secundaria. Estos resultados indican que el desarrollo de “una mirada profesional” del profesor es un proceso complicado pero que la posibilidad de construir un discurso progresivo en línea es un factor importante para su desarrollo.

Development of prospective mathematics teachers’ professional noticing in a specific domain: proportional reasoning

The aim of this research is to identify aspects that support the development of prospective mathematics teachers’ professional noticing in a b-learning context. The study presented here investigates the extent to which prospective secondary mathematics teachers attend and interpret secondary school students’ proportional reasoning and decide how to respond. Results show that interactions in an on-line discussion improve prospective mathematics teachers’ ability to identify and interpret important aspects of secondary school students’ mathematical thinking.

A structural model of cognitive-motivational variables as explanatory factors of academic achievement in Spanish Language and Mathematics

In recent years, several explanatory models have been developed which attempt to analyse the predictive worth of various factors in relation to academic achievement, as well as the direct and indirect effects that they produce. The aim of this study was to examine a structural model incorporating various cognitive and motivational variables which influence student achievement in the two basic core skills in the Spanish curriculum: Spanish Language and Mathematics. These variables included differential aptitudes, specific self-concept, goal orientations, effort and learning strategies. The sample comprised 341 Spanish students in their first year of Compulsory Secondary Education. Various tests and questionnaires were used to assess each student, and Structural Equation Modelling (SEM) was employed to study the relationships in the initial model. The proposed model obtained a satisfactory fit for the two subjects studied, and all the relationships hypothesised were significant. The variable with the most explanatory power regarding academic achievement was mathematical and verbal aptitude. Also notable was the direct influence of specific self-concept on achievement, goal-orientation and effort, as was the mediatory effect that effort and learning strategies had between academic goals and final achievement.

Mathematics Game e-Library for Elementary School, study case: Mexico

One of the most relevant subjects for the intellectual formation of elementary school students is Mathematics where its importance goes back to ancient civilizations and which its importance is underestimated nowadays. This phenomenon occurs in Mexico, where 63.1% of the total population of elementary school students between the third and sixth grade have insufficient/elemental level of mathematics knowledge. This has resulted in the need to use a new mechanism to complement student’s classroom learning. With the rapid growth of wireless and mobile technologies, the mobile learning has been gradually considered as a novel and effective form of learning due to it inherits all the advantages of e-learning as well as breaks the limitations of learning time and space occurring in the traditional classroom teaching. This project proposes the use of a Mathematics Game e-Library integrated by a set of games for mobile devices and a distribution/management tool. The games are developed for running on mobile devices and for cover the six competencies related with the mathematics learning approach established in Mexico. The distribution/management tool allows students to reach contents according to their needs; this is achieved through a core engine that infers, from an initial profile, the games that cover the user’s knowledge gaps.

Aprendiendo a interpretar el aprendizaje de las matemáticas en educación primaria. Características en un contexto B-Learning

El objetivo de esta investigación es identificar características del proceso de instrumentalización del conocimiento de didáctica de la matemática de profesores de educación primaria en un curso de especialización desarrollado en un contexto b-learning. Participaron 65 maestros en un entorno de aprendizaje b-learning integrando debates virtuales y centrados en el análisis del pensamiento matemático de alumnos de educación primaria. El análisis de las participaciones en los debates virtuales y la resolución de las tareas nos han permitido caracterizar el aprendizaje del conocimiento sobre el aprendizaje de las matemáticas como un cambio en el discurso de los estudiantes. Este cambio se puso de manifiesto por la integración paulatina del conocimiento de didáctica de la matemática en la interpretación del pensamiento matemático de los alumnos. Los resultados indican que las aportaciones a los debates en forma de refutaciones favorecieron el proceso de instrumentalización de las ideas teóricas.

The curricular value of mathematics in non-mathematics degree

Higher education should provide the acquisition of skills and abilities that allow the student to play a full and active role in society. The educational experience should offer a series of conceptual, procedural and attitudinal contents that encourage “learning to know, learning to do, learning to be and learning to live together”. It is important to consider the curricular value of mathematics in the education of university undergraduates who do not intend to study mathematics but for whom the discipline will serve as an instrumental. This work discusses factors that form part of the debate on the curricular value of mathematics in non-mathematics degrees.

Inclusion of immersive virtual learning environments and visual control systems to support the learning of students with Asperger syndrome

This paper presents the use of immersive virtual reality systems in the educational intervention with Asperger students. The starting points of this study are features of these students' cognitive style that requires an explicit teaching style supported by visual aids and highly structured environments. The proposed immersive virtual reality system, not only to assess the student's behavior and progress, but also is able to adapt itself to the student's specific needs. Additionally, the immersive reality system is equipped with sensors that can determine certain behaviors of the students. This paper determines the possible inclusion of immersive virtual reality as a support tool and learning strategy in these particular students' intervention. With this objective two task protocols have been defined with which the behavior and interaction situations performed by participant students are recorded. The conclusions from this study talks in favor of the inclusion of these virtual immersive environments as a support tool in the educational intervention of Asperger syndrome students as their social competences and executive functions have improved.

Perspectives of Teachers Regarding the Integration of Mathematics and Science at the Secondary School Level

The integration of mathematics and science in secondary schools in the 21st century continues to be an important topic of practice and research. The purpose of my research study, which builds on studies by Frykholm and Glasson (2005) and Berlin and White (2010), is to explore the potential constraints and benefits of integrating mathematics and science in Ontario secondary schools based on the perspectives of in-service and pre-service teachers with various math and/or science backgrounds. A qualitative and quantitative research design with an exploratory approach was used. The qualitative data was collected from a sample of 12 in-service teachers with various math and/or science backgrounds recruited from two school boards in Eastern Ontario. The quantitative and some qualitative data was collected from a sample of 81 pre-service teachers from the Queen’s University Bachelor of Education (B.Ed) program. Semi-structured interviews were conducted with the in-service teachers while a survey and a focus group was conducted with the pre-service teachers. Once the data was collected, the qualitative data were abductively analyzed. For the quantitative data, descriptive and inferential statistics (one-way ANOVAs and Pearson Chi Square analyses) were calculated to examine perspectives of teachers regardless of teaching background and to compare groups of teachers based on teaching background. The findings of this study suggest that in-service and pre-service teachers have a positive attitude towards the integration of math and science and view it as valuable to student learning and success. The pre-service teachers viewed the integration as easy and did not express concerns to this integration. On the other hand, the in-service teachers highlighted concerns and challenges such as resources, scheduling, and time constraints. My results illustrate when teachers perceive it is valuable to integrate math and science and which aspects of the classroom benefit best from the integration. Furthermore, the results highlight barriers and possible solutions to better the integration of math and science. In addition to the benefits and constraints of integration, my results illustrate why some teachers may opt out of integrating math and science and the different strategies teachers have incorporated to integrate math and science in their classroom.

Conhece o microsoft mathematics? Não?! Então este workshop é para si!

A vertiginosa difusão das TIC e o crescente desenvolvimento de diverso software científico estão a produzir mudanças relevantes nos processos formativos em matemática, estando estas a favorecer a criação de novos e melhores recursos didáticos e de autoaprendizagem, assim como uma nova forma de gerar e difundir conhecimento ou experiências cognitivas (Atencio, 2013). No entanto para tirar partido, a nível pessoal ou profissional, da variedade de recursos que estão ao nosso alcance para aprender/ensinar matemática, como os programas Geogebra, Surfer, GeCla, Microsoft Mathematics etc., é importante conhecê-los e saber trabalhar com eles. Tendo em vista este objetivo, neste Workshop pretende-se “apresentar” o software Microsoft Mathematics, explorá-lo como recurso na resolução de algumas tarefas de matemática, assim como discutir as suas potencialidades e limitações. O software Microsoft Mathematics, inicialmente com a designação Microsoft Math, foi lançado pela Microsoft Corporation em 2006, e surgiu para tentar resolver o problema de muitos alunos brasileiros que tinham dificuldades nas disciplinas que envolviam cálculo. No início estava apenas disponível para uso de uma comunidade estudantil que, com o apoio de empresas e universidades, visava formar alunos na área de tecnologias de informação para o mercado de trabalho. Depois de algumas melhorias, o programa passou a ser disponibilizado para o público em geral e a ser comercializado (Sousa e Araújo (s.d.)). Atualmente a versão 4.0 é a mais recente, é gratuita e está disponível para download na internet no site https://www.microsoft.com/ptpt/ download/details.aspx?id=15702. Do ponto de vista da matemática, o Microsoft Mathematics abrange domínios como a aritmética, o cálculo, a álgebra e a estatística. Por exemplo, permite executar uma diversidade de cálculos: resolver equações, inequações e sistemas de equações, converter unidades de medida, calcular estatísticas básicas (como média e desvio-padrão), efetuar operações com números complexos, calcular derivadas e integrais, realizar operações com matrizes, entre outros, e, em alguns casos, possibilita a consulta da resolução passo a passo. Tem também uma vertente gráfica, podendo representar-se gráficos a duas ou a três dimensões. Esta funcionalidade possibilita, ainda, representar graficamente equações com parâmetros, o que permite visualizar as mudanças em função da variação do valor do parâmetro, que pode ser de grande utilidade, por exemplo, na discussão de sistemas de equações lineares. Em termos de usabilidade, o Microsoft Mathematics tem uma interface simples e facilmente compreensível para o utilizador e a sintaxe para comunicar com o software é quase sempre a que se utiliza em matemática. Torna-se igualmente uma mais-valia quando se pretende produzir documentos em Word com simbologia matemática, pois permite exportar para este aplicativo o trabalho realizado. Conclui-se, assim, que o Microsoft Mathematics é um software educativo que fornece um conjunto de ferramentas que podem constituir um apoio para os estudantes do 3.º ciclo do ensino básico, do ensino secundário e ensino superior, na resolução de tarefas que exigem conhecimentos matemáticos. Pode, ainda, tornar-se um recurso útil para os professores tanto na preparação de aulas como no contexto de sala de aula, na medida em que, para além de facilitar a execução de cálculos, permite explorar alguns conteúdos de uma forma interativa e com maior profundidade.

Sustainable Development and Collective Learning: Theory and a European Case Study. Bruges European Economic Policy (BEEP) Briefing 7/2004

Network governance of collective learning processes is an essential approach to sustainable development. The first section of the article briefly refers to recent theories about both market and government failures that express scepticism about the way framework conditions for market actors are set. For this reason, the development of networks for collective learning processes seems advantageous if new solutions are to be developed in policy areas concerned with long-term changes and a stepwise internalisation of externalities. With regard to corporate actors’ interests, the article shows recent insights from theories about the knowledge-based firm, where the creation of new knowledge is based on the absorption of societal views. This concept shifts the focus towards knowledge generation as an essential element in the evolution of sustainable markets. This involves at the same time the development of new policies. In this context innovation-inducing regulation is suggested and discussed. The evolution of the Swedish, German and Dutch wind turbine industries are analysed based on the approach of governance put forward in this article. We conclude that these coevolutionary mechanisms may take for granted some of the stabilising and orientating functions previously exercised by basic regulatory activities of the state. In this context, the main function of the governments is to facilitate learning processes that depart from the government functions suggested by welfare economics.