Strong minimax lower bounds for learning

Minimax lower bounds for concept learning state, for example, thatfor each sample size $n$ and learning rule $g_n$, there exists a distributionof the observation $X$ and a concept $C$ to be learnt such that the expectederror of $g_n$ is at least a constant times $V/n$, where $V$ is the VC dimensionof the concept class. However, these bounds do not tell anything about therate of decrease of the error for a {\sl fixed} distribution--concept pair.\\In this paper we investigate minimax lower bounds in such a--stronger--sense.We show that for several natural $k$--parameter concept classes, includingthe class of linear halfspaces, the class of balls, the class of polyhedrawith a certain number of faces, and a class of neural networks, for any{\sl sequence} of learning rules $\{g_n\}$, there exists a fixed distributionof $X$ and a fixed concept $C$ such that the expected error is larger thana constant times $k/n$ for {\sl infinitely many n}. We also obtain suchstrong minimax lower bounds for the tail distribution of the probabilityof error, which extend the corresponding minimax lower bounds.

Learning as movements in interspace

My research issues (in rearch project for PhD-degree, named Drama in School) concern how learning takes place in drama education in compulsory school. One part is to explore and problematize approaches to learning (in and through drama). In this paper will the concept learning be discussed by using a thought derived from Deleuze and Guattari’s nomad philosophy. They describe learning as a movement in the interspace. Focus is on process and inquiry, not on achievement of predetermined skills and competences. 

”Käsitteitä tarpeen mukaan". Kirjallisuustieteelliset käsitteet lukion kirjallisuudenopetuksessa

Tavoitteeni tässä tutkimuksessa oli selvittää, miten kirjallisuustieteellisiä proosa-anayysin käsitteitä opetetaan opetussuunnitelman mukaisissa lukion äidinkielen ja kirjallisuuden oppikirjoissa ja miten hyvin kokelaat hallitsivat kertoja-käsitteen tekstitaidon ylioppilaskokeessa keväällä 2007. Samalla pohdin, minkälainen kirjallisuustieteellinen käsitteistö palvelisi tekstianalyysin opetusta koulussa, koska Lukion opetussuunnitelman perusteet 2003 ja äidinkielen ylioppilaskoe edellyttävät äidinkielen ja kirjallisuuden opetukselta ja oppilailta käsitteiden käyttöä. Tutkimusaineistonani olivat kaikki kuusi käytössä olevaa lukion äidinkielen ja kirjallisuuden oppikirjaa ja 440 kpl kevään 2007 äidinkielen tekstitaidon ylioppilaskokeen vastaustekstiä. Oppikirjoja tarkastelin soveltamalla niiden arviointiin Lev S. Vygotskin ajatuksia arkikäsitteiden ja tieteellisten käsitteiden opettamisesta ja Hans Aeblin esittämiä teoreettisia malleja käsitteiden opettamisesta ja oppimisesta. Tutkimukseni osoittaa, että opetussuunnitelmassa mainittujen proosa-analyysin käsitteiden kertoja, näkökulma, motiivi, aihe ja teema opetus on epätäsmällistä. Oppikirjoissa ei ole otettu huomioon sitä, että käsitteenoppiminen on monivaiheinen prosessi. Myöskään problematiikkaa, joka aiheutuu kyseisten käsitteiden määrittelyn kirjavuudesta ja käytöstä sekä arkikielen käsitteinä että tieteellisinä käsitteinä, ei oppikirjoissa käsitellä. Sama näkyy ylioppilaskoeaineistossa: oppilaat eivät hallitse käsitettä kertoja tieteellisenä käsitteenä. Tietoisuus kirjallisuustieteellisten käsitteiden määrittelyn problematiikasta ja arkikäsitteiden ja tieteellisten käsitteiden ontologisista kategorioista on onnistuneen käsitteenoppimisen edellytys. Kirjallisuustieteelliset käsitteet ovat metakäsitteitä, jotka edellyttävät oppilaiden metakäsitteellisen tietoisuuden ja motivaation hyödyntämistä opetuksessa, jossa olisi sovellettava monipuolisesti eri oppimiskäsitysten parhaita puolia hyödyntäviä lähestymistapoja, erilaisia pedagogisia diskursseja. Koulujen kirjallisuudenopetusta suunniteltaessa ja kirjallisuustieteellisiä käsitteitä opetettaessa on otettava huomioon niin kirjallisuustieteen kuin kasvatustieteen näkökulma. Opetussuunnitelman ja ylioppilaskokeen asettama vaatimus käsitteiden käytöstä on kohtuuton, mikäli ei sovita, miten käsitteet määritellään ja mitä käsitteitä kokelaiden oletetaan ylioppilaskokeessa hallitsevan. Kirjallisuustieteellisten käsitteiden puutteellisen opetuksen oppikirjoissa ja niiden epämääräisen käytön ylioppilaskokeen tehtävänannoissa ja arvioinnissa voi kärjistyneimmillään nähdä oppilaan oikeusturvakysymyksenä

Capturing Emergent Semantics from Social Annotation Systems

The ongoing growth of the World Wide Web, catalyzed by the increasing possibility of ubiquitous access via a variety of devices, continues to strengthen its role as our prevalent information and commmunication medium. However, although tools like search engines facilitate retrieval, the task of finally making sense of Web content is still often left to human interpretation. The vision of supporting both humans and machines in such knowledge-based activities led to the development of different systems which allow to structure Web resources by metadata annotations. Interestingly, two major approaches which gained a considerable amount of attention are addressing the problem from nearly opposite directions: On the one hand, the idea of the Semantic Web suggests to formalize the knowledge within a particular domain by means of the "top-down" approach of defining ontologies. On the other hand, Social Annotation Systems as part of the so-called Web 2.0 movement implement a "bottom-up" style of categorization using arbitrary keywords. Experience as well as research in the characteristics of both systems has shown that their strengths and weaknesses seem to be inverse: While Social Annotation suffers from problems like, e. g., ambiguity or lack or precision, ontologies were especially designed to eliminate those. On the contrary, the latter suffer from a knowledge acquisition bottleneck, which is successfully overcome by the large user populations of Social Annotation Systems. Instead of being regarded as competing paradigms, the obvious potential synergies from a combination of both motivated approaches to "bridge the gap" between them. These were fostered by the evidence of emergent semantics, i. e., the self-organized evolution of implicit conceptual structures, within Social Annotation data. While several techniques to exploit the emergent patterns were proposed, a systematic analysis - especially regarding paradigms from the field of ontology learning - is still largely missing. This also includes a deeper understanding of the circumstances which affect the evolution processes. This work aims to address this gap by providing an in-depth study of methods and influencing factors to capture emergent semantics from Social Annotation Systems. We focus hereby on the acquisition of lexical semantics from the underlying networks of keywords, users and resources. Structured along different ontology learning tasks, we use a methodology of semantic grounding to characterize and evaluate the semantic relations captured by different methods. In all cases, our studies are based on datasets from several Social Annotation Systems. Specifically, we first analyze semantic relatedness among keywords, and identify measures which detect different notions of relatedness. These constitute the input of concept learning algorithms, which focus then on the discovery of synonymous and ambiguous keywords. Hereby, we assess the usefulness of various clustering techniques. As a prerequisite to induce hierarchical relationships, our next step is to study measures which quantify the level of generality of a particular keyword. We find that comparatively simple measures can approximate the generality information encoded in reference taxonomies. These insights are used to inform the final task, namely the creation of concept hierarchies. For this purpose, generality-based algorithms exhibit advantages compared to clustering approaches. In order to complement the identification of suitable methods to capture semantic structures, we analyze as a next step several factors which influence their emergence. Empirical evidence is provided that the amount of available data plays a crucial role for determining keyword meanings. From a different perspective, we examine pragmatic aspects by considering different annotation patterns among users. Based on a broad distinction between "categorizers" and "describers", we find that the latter produce more accurate results. This suggests a causal link between pragmatic and semantic aspects of keyword annotation. As a special kind of usage pattern, we then have a look at system abuse and spam. While observing a mixed picture, we suggest that an individual decision should be taken instead of disregarding spammers as a matter of principle. Finally, we discuss a set of applications which operationalize the results of our studies for enhancing both Social Annotation and semantic systems. These comprise on the one hand tools which foster the emergence of semantics, and on the one hand applications which exploit the socially induced relations to improve, e. g., searching, browsing, or user profiling facilities. In summary, the contributions of this work highlight viable methods and crucial aspects for designing enhanced knowledge-based services of a Social Semantic Web.

A formação de conceitos no ensino de graduação em enfermagem à luz da teoria da aprendizagem significativa

The Theory of Meaningful Learning (TML) described by David Paul Ausubel offers a proposal for the teaching strategies to provide a more active and effective student learning. The projection of the TML practice is demonstrated through the development of concept maps (CM) technique, created by Joseph Donald Novak, which presents as a strategy, method or schematic feature, which is an indicator to identify the cognitive organization of the knowledge acquired by students. The survey was conducted in the light of TML in relation to learning concepts involving students of undergraduate nursing in a public university in the state of Rio Grande do Norte. Thus, the study aimed to compare the concept learning of students of undergraduate nursing, when subjected to different forms of education, to point approaches that promote more effective and meaningful results. It was a quasi - experimental study with a qualitative analysis, conducted with students of the Undergraduate Nursing of the Universidade Federal do Rio Grande do Norte (UFRN), approved by the Research Ethics Committee/UFRN Certification of Presention for Ethics Appreciation (CPEA) in 11706412.3.0000.5537. The study took place at two different times and involved content on complications mediate postoperative surgical wound in the same discipline with students who attended the 5th semester of the degree course in Nursing. For the viability of data collection, in the second half of 2013, we used the technique of CM, to represent the concept of complications mediate postoperative surgical wound covered in the classroom. CM were built at a different time from that of the discipline, with the support of tutors and preceded by a brief description and explanation about the form of preparation and application. In this study were subjected, 31 students of undergraduate nursing, registered in the discipline of Integral Attention to health I. In the first stage, 18 students participated in the survey, they had the teaching intervention based on TML, and in the second stage, all students participated in the lesson provided curriculum with the responsible teacher of the subject, on the same issue occurred. At the end of each meeting, the students 11 developed concept maps with the aid of software Cmap Tools®. Data analysis happened upon the technique of content analysis, supported by a conceptual map "glass", previously developed by researchers and aid in the preparation of the categories in which the concepts found were classified. The study found that the teaching intervention based on TML with the help of CM, managed to develop in students a more expressive teaching learning process than just classroom curriculum with the traditional teaching method, and also that the association between the intervention motion teaching with the traditional method and the use of the technique of CM encourages the student the ability to articulate the various acquired knowledge as well as apply them in real situations

Sentidos e significados do conceito de divisão provenientes de Atividade Orientadora de Ensino

Pós-graduação em Docência para a Educação Básica - FC

Cognitive Interventions with Children with Special Needs - Transfer effects and multidisciplinary perspectives

Our last study with regularly developed children demonstrated a positive effect of working memory training on cognitive abilities. Building upon these findings, the aim of this multidisciplinary study is to investigate the effects of training of core functions with children who are suffering from different learning disabilities, like AD/HD, developmental dyslexia or specific language impairment. In addition to working memory training (BrainTwister), we apply a perceptual training, which concentrates on auditory-visual matching (Audilex), as well as an implicit concept learning task. We expect differential improvements of mental capacities, specifically of executive functions (working memory, attention, auditory and visual processing), scholastic abilities (language and mathematical skills), as well as of problem solving. With that, we hope to find further directions regarding helpful and individually adapted interventions in educational settings. Interested parties are invited to discuss and comment the design, the research question, and the possibilities in recruiting the subjects.

Using Sensitivity as a Method for Ranking the Test Cases Classified by Binary Decision Trees

Usually, data mining projects that are based on decision trees for classifying test cases will use the probabilities provided by these decision trees for ranking classified test cases. We have a need for a better method for ranking test cases that have already been classified by a binary decision tree because these probabilities are not always accurate and reliable enough. A reason for this is that the probability estimates computed by existing decision tree algorithms are always the same for all the different cases in a particular leaf of the decision tree. This is only one reason why the probability estimates given by decision tree algorithms can not be used as an accurate means of deciding if a test case has been correctly classified. Isabelle Alvarez has proposed a new method that could be used to rank the test cases that were classified by a binary decision tree [Alvarez, 2004]. In this paper we will give the results of a comparison of different ranking methods that are based on the probability estimate, the sensitivity of a particular case or both.

Uma proposta de ensino de frações no 6º ano do ensino fundamental a partir da teoria histórico-cultural

This text presents developed in the Graduate Program in Science and Mathematics Education at the Federal University of Uberlândia, in which it was intended to answer the question: What are the pedagogical implications for the fractions concept learning for students of the 6th grade of elementary school that the teaching guide activities can provide? The objectives of this research were: a) analyze the possible pedagogical implications for the learning of the fraction's concept for students of the 6th grade of elementary school through guiding teaching activities; b) using the conceptual connections of the fraction to enable students to develop an abstract thought and c) investigate whether guiding teaching activities reflect on 'how to think' and 'how to do' of the student. Five teaching activities have been developed (MOURA, 2002) from the perspective of teaching guiding activity (TGA) and had as object of study the teaching of fractions for students in 6th year of elementary school. They have been prepared and proposed activities in which it was intended to investigate the use of history of mathematics as an aid in learning the conceptual fraction links (CARAÇA, 1951) by students. Such activities, for analysis, were organized into episodes and scenes (MOURA, 2004) and discussed how students deal with the measurement of whole quantity (all) and subunits (part); how they represent in verbal or written language. It is hoped that the research is set up as an important contribution to mathematics teaching area and may contribute to the initial and continuing training of mathematics teacher sand the formation of theoretical thinking of elementary school students.

Diagnóstico del rendimiento académico de estudiantes de una escuela de educación superior en México

El objetivo del artículo es realizar un diagnóstico sobre la percepción de los factores que intervienen en el rendimiento académico de los estudiantes de cinco carreras universitarias en una escuela de educación superior en México, para así reconocer las áreas de oportunidad que permitan sugerir políticas y estrategias para elevar su rendimiento. Se utilizó una muestra de 1651 estudiantes, se obtuvieron los datos a partir de un cuestionario con treinta preguntas que estudian la percepción del rendimiento académico en escala tipo Likert. Se realizó un análisis factorial exploratorio que permitiera reducir los datos, facilitar la interpretación y validar el instrumento. Se identificaron tres factores: a) el rol de los profesores, b) la evaluación y c) la motivación de los estudiantes. Se llevó a cabo un análisis comparativo por carrera. Se encontró que los estudiantes perciben que la mayoría de los maestros no se preocupan por la condición de los jóvenes en situación de reprobación. Además, casi no motivan y carecen de expresiones de sentimientos de orgullo por los logros académicos de los estudiantes. La mitad de los participantes piensa que los docentes no cubren el temario en su totalidad. Se detectó que los estudiantes poseen una alta motivación siendo esto positivo porque son alumnos dedicados y responsables. Se concluye realizando una serie de sugerencias y explicando las implicaciones que tiene este trabajo para las instituciones de educación superior.

Interactional strategies between terminologist and domain specialist. Putting order into our universe: the concept of Blended Learning

A presente comunicação visa discutir as mais-valias de um desenho metodológico sustentado numa abordagem conceptual da Terminologia aplicado ao exercício de harmonização da definição do cenário educativo mais promissor do Ensino Superior actual: o blended learning. Sendo a Terminologia uma disciplina que se ocupa da representação, da descrição e da definição do conhecimento especializado através da língua a essência deste domínio do saber responde a uma necessidade fundamental da sociedade actual: putting order into our universe, nas palavras de Nuopponen (2011). No contexto descrito, os conceitos, enquanto elementos da estrutura do conhecimento (Sager, 1990) constituem um objecto de investigação de complexidade não despicienda, pois apesar do postulado de que a língua constitui uma ferramenta fundamental para descrever e organizar o conhecimento, o princípio isomórfico não pode ser tomado como adquirido. A abordagem conceptual em Terminologia propõe uma visão precisa do papel da língua no trabalho terminológico, sendo premissa basilar que não existe uma correspondência unívoca entre os elementos atomísticos do conhecimento e os elementos da expressão linguística. É pela razões enunciadas que as opções metodológicas circunscritas à análise do texto de especialidade serão consideradas imprecisas. Nesta reflexão perspectiva-se que o conceito-chave de uma abordagem conceptual do trabalho terminológico implica a combinação de um processo de elicitação do conhecimento tácito através de uma negociação discursiva orientada para o conceito e a análise de corpora textuais. Defende-se consequentemente que as estratégias de interacção entre terminólogo e especialista de domínio merecem atenção detalhada pelo facto de se reflectirem com expressividade na qualidade dos resultados obtidos. Na sequência do exposto, o modelo metodológico que propomos sustenta-se em três etapas que privilegiam um refinamento dessa interacção permitindo ao terminólogo afirmar-se como sujeito conceptualizador, decisor e interventor: (1) etapa exploratória do domínio-objecto de estudo; (2) etapa de análise onamasiológica de evidência textual e discursiva; (3) etapa de modelização e de validação de resultados. Defender-se-á a produtividade de uma sequência cíclica entre a análise textual e discursiva para fins onomasiológicos, a interacção colaborativa e a introspecção.

Experiential learning instruments : an examination of the concept of the instrumental approach in experiential learning

Experiential Learning Instruments (ELls) are employed to modify the leamer's apprehension and / or comprehension in experiential learning situations, thereby improving the efficiency and effectiveness of those modalities in the learning process. They involve the learner in reciprocally interactive and determining transactions with his/her environment. Experiential Learning Instruments are used to keep experiential learning a process rather than an object. Their use is aimed at the continual refinement of the learner's knowledge and skill. Learning happens as the leamer's awareness, directed by the use of Ells, comes to experience, monitor and then use experiential feedback from living situations in a way that facilitates knmvledge/skill acquisition, self-correction and refinement. The thesis examined the literature relevant to the establishing of a theoretical experiential learning framework within which ELls can be understood. This framework included the concept that some learnings have intrinsic value-knowledge of necessary information-while others have instrumental value-knowledge of how to learn. The Kolb Learning Cycle and Kolb's six characteristics of experiential learning were used in analyzing three ELls from different fields of learning-saxophone tone production, body building and interpersonal communications. The ELls were examined to determine their learning objectives and how they work using experiential learning situations. It was noted that ELls do not transmit information but assist the learner in attending to and comprehending aspects of personal experience. Their function is to telescope the experiential learning process.

Particle Competition and Cooperation in Networks for Semi-Supervised Learning with Concept Drift

Concept drift is a problem of increasing importance in machine learning and data mining. Data sets under analysis are no longer only static databases, but also data streams in which concepts and data distributions may not be stable over time. However, most learning algorithms produced so far are based on the assumption that data comes from a fixed distribution, so they are not suitable to handle concept drifts. Moreover, some concept drifts applications requires fast response, which means an algorithm must always be (re) trained with the latest available data. But the process of labeling data is usually expensive and/or time consuming when compared to unlabeled data acquisition, thus only a small fraction of the incoming data may be effectively labeled. Semi-supervised learning methods may help in this scenario, as they use both labeled and unlabeled data in the training process. However, most of them are also based on the assumption that the data is static. Therefore, semi-supervised learning with concept drifts is still an open challenge in machine learning. Recently, a particle competition and cooperation approach was used to realize graph-based semi-supervised learning from static data. In this paper, we extend that approach to handle data streams and concept drift. The result is a passive algorithm using a single classifier, which naturally adapts to concept changes, without any explicit drift detection mechanism. Its built-in mechanisms provide a natural way of learning from new data, gradually forgetting older knowledge as older labeled data items became less influent on the classification of newer data items. Some computer simulation are presented, showing the effectiveness of the proposed method.

Semi-supervised learning with concept drift using particle dynamics applied to network intrusion detection data

Concept drift, which refers to non stationary learning problems over time, has increasing importance in machine learning and data mining. Many concept drift applications require fast response, which means an algorithm must always be (re)trained with the latest available data. But the process of data labeling is usually expensive and/or time consuming when compared to acquisition of unlabeled data, thus usually only a small fraction of the incoming data may be effectively labeled. Semi-supervised learning methods may help in this scenario, as they use both labeled and unlabeled data in the training process. However, most of them are based on assumptions that the data is static. Therefore, semi-supervised learning with concept drifts is still an open challenging task in machine learning. Recently, a particle competition and cooperation approach has been developed to realize graph-based semi-supervised learning from static data. We have extend that approach to handle data streams and concept drift. The result is a passive algorithm which uses a single classifier approach, naturally adapted to concept changes without any explicit drift detection mechanism. It has built-in mechanisms that provide a natural way of learning from new data, gradually "forgetting" older knowledge as older data items are no longer useful for the classification of newer data items. The proposed algorithm is applied to the KDD Cup 1999 Data of network intrusion, showing its effectiveness.