The study investigated the effects of two generative learning activities on students’ academic achievement of the part-whole representation of rational numbers while using virtual manipulatives. Third-grade students were divided randomly in two groups to evaluate the effects of two generative learning activities: answering-questions and generating-examples while using two virtual manipulatives related to part-whole representation of rational numbers. The study employed an experimental design with pre- and post-tests. A 2x2 mixed analysis of variance (ANOVA) was used to determine any significant interaction between the two groups (answering questions and generating-examples) and between two tests (pre-test and immediate post-test). In addition, a 2x3 mixed analysis of variance (ANOVA) and a Bonferroni post-hoc analysis were used to determine the effects of the generative strategies on fostering comprehension, and to determine any significant differences between the two groups (answering-questions and generating-examples) and among the three tests (pre-test, immediate post-test, and delayed posttest). Results showed that an answering-questions strategy had a significantly greater effect than a generating-examples strategy on an immediate comprehension posttest. In addition, no significant interaction was found between the generative strategies on a delayed comprehension tests. However a difference score analysis between the immediate posttest scores and the delayed posttest scores revealed a significant difference between the answering-questions and the generating-examples groups suggesting that students who used generating-examples strategy tended to remember relatively more information than students who used the answering-questions strategy. The findings are discussed in the context of the related literature and directions for future research are suggested. / Ph. D.

No description available.

In this dissertation, the object of research is the advanced generative learning objects (AGLOs), models and processes related to them. The objective of the research is to develop and to investigate the methods that enable to formalize the designing of advanced generative learning objects and using them in teaching/learning of informatics effectively. Scientific novelty: 1. AGLOs expand the informatics learning variability aspects (pedagogical, social, technological, and content). Based on those insights, it is possible to adapt and apply software engineering and computer science methods in the e-learning domain. 2. To our best knowledge, feature-based modelling in the informatics learning domain has been performed systematically for the first time. Such an approach evaluates the domain variability, aggregates and verifies the created models. 3. Formalization of the models at two levels (feature-based and executable specification) provides pre-conditions for automated tools design. 4. From the viewpoint of automatic educational content creation, AGLO extends the concept of reusability in e-learning. The specialized learning environments with integrated AGLO implement the visual transformation of a real task into its physical process, thus providing a high level of motivation and effective learning. / Darbe tiriami informatikos (programavimo) mokymuisi skirti išplėstiniai generatyviniai mokymosi objektai (IGMO) ir su jais susiję informaciniai specifikavimo/atvaizdavimo, transformavimo modeliai ir procesai. Darbo tikslas yra pateikti ir ištirti metodiką, įgalinančią formalizuoti išplėstinių generatyvinių mokymosi objektų kūrimą ir efektyvų jų naudojimą mokant informatikos (programavimo). Darbo mokslinis naujumas: 1. IGMO išplečia informatikos mokymosi sritį naujais aspektais (pedagoginiais, socialiniais, technologiniais, turinio), aprašomais terminu mokymosi variantiškumas. Tai įgalino pagrįstai adaptuoti ir naujai pritaikyti programų inžinerijos ir kompiuterijos principus ir metodus e.mokymosi sričiai. 2. Požymiais grįstas sisteminis informatikos (programavimo) mokymosi srities modeliavimas, mūsų žiniomis, atliktas pirmą kartą. Jis įvertina mokymosi variantiškumą ir agreguoja bei verifikuoja įvairialypius modelius. Tai sudaro prielaidas sistemingam IGMO kūrimui. 3. Modelių formalizavimas dviejuose lygmenyse (požymių modelių ir vykdomųjų specifikacijų) sudaro sąlygas automatizuotiems įrankiams kurti. 4. IGMO išplečia pakartotinio panaudojimo koncepciją e.mokymesi turinio automatinio kūrimo požiūriu. Sukurtos specializuotos heterogeninės mokymosi aplinkos, į kurias integruoti IGMO, įgyvendina realaus uždavinio vizualinę transformaciją į fizinį procesą bei užtikrina aukštą mokinių motyvaciją ir efektyvų mokymąsi.

Darbe tiriami informatikos (programavimo) mokymuisi skirti išplėstiniai generatyviniai mokymosi objektai (IGMO) ir su jais susiję informaciniai specifikavimo/atvaizdavimo, transformavimo modeliai ir procesai. Darbo tikslas yra pateikti ir ištirti metodiką, įgalinančią formalizuoti išplėstinių generatyvinių mokymosi objektų kūrimą ir efektyvų jų naudojimą mokant informatikos (programavimo). Darbo mokslinis naujumas: 1. IGMO išplečia informatikos mokymosi sritį naujais aspektais (pedagoginiais, socialiniais, technologiniais, turinio), aprašomais terminu mokymosi variantiškumas. Tai įgalino pagrįstai adaptuoti ir naujai pritaikyti programų inžinerijos ir kompiuterijos principus ir metodus e.mokymosi sričiai. 2. Požymiais grįstas sisteminis informatikos (programavimo) mokymosi srities modeliavimas, mūsų žiniomis, atliktas pirmą kartą. Jis įvertina mokymosi variantiškumą ir agreguoja bei verifikuoja įvairialypius modelius. Tai sudaro prielaidas sistemingam IGMO kūrimui. 3. Modelių formalizavimas dviejuose lygmenyse (požymių modelių ir vykdomųjų specifikacijų) sudaro sąlygas automatizuotiems įrankiams kurti. 4. IGMO išplečia pakartotinio panaudojimo koncepciją e.mokymesi turinio automatinio kūrimo požiūriu. Sukurtos specializuotos heterogeninės mokymosi aplinkos, į kurias integruoti IGMO, įgyvendina realaus uždavinio vizualinę transformaciją į fizinį procesą bei užtikrina aukštą mokinių motyvaciją ir efektyvų mokymąsi. / In this dissertation, the object of research is the advanced generative learning objects (AGLOs), models and processes related to them. The objective of the research is to develop and to investigate the methods that enable to formalize the designing of advanced generative learning objects and using them in teaching/learning of informatics effectively. Scientific novelty: 1. AGLOs expand the informatics learning variability aspects (pedagogical, social, technological, and content). Based on those insights, it is possible to adapt and apply software engineering and computer science methods in the e-learning domain. 2. To our best knowledge, feature-based modelling in the informatics learning domain has been performed systematically for the first time. Such an approach evaluates the domain variability, aggregates and verifies the created models. 3. Formalization of the models at two levels (feature-based and executable specification) provides pre-conditions for automated tools design. 4. From the viewpoint of automatic educational content creation, AGLO extends the concept of reusability in e-learning. The specialized learning environments with integrated AGLO implement the visual transformation of a real task into its physical process, thus providing a high level of motivation and effective learning.

By augmenting an existing static medium (a graphic organizer) with attributes such that learners were able to sort or rearrange information in multiple ways, two new types of “dynamic” graphic organizers were created. An experiment was performed to investigate the effectiveness of these dynamic graphic organizers as instructional tools. One-hundred-sixty-one students were recruited for participation in the study from a two-year community college and a four-year public university in the southeast United States. Participants were randomly assigned to one of three graphic organizer treatment groups: static, sortable, and shuffle-sortable. Response accuracy and response latency measurements for three types of mental tasks (factual, comparative, and inferential) were compared across the three treatment groups. A multivariate analysis of variance showed no significant difference between the three graphic organizer types for response accuracy. A within-groups analysis of variance showed no significant differences in response accuracy between mental tasks within the static or sortable treatment groups. However, analysis of variance indicated that accuracy for inferential judgments was lower than that for factual judgments in the shuffle-sortable group. With respect to response latency, a multivariate analysis of variance revealed no significant difference between the three treatment groups. A within-groups analysis of variance showed significant differences in response latency between factual and inferential judgment-making for both the sortable and shuffle-sortable treatments. The sortable treatment had the most pronounced differences in latency between mental tasks, whereas no significant differences in response latency were observed within the static treatment. Participants in the two dynamic treatments reported much higher percentages of affirmative responses to the question, “Did you think your graphic organizer was an effective instructional tool?” with 82.7% and 81.5% responding “yes” for the Sortable and Shuffle-sort groups, respectively, and only 60.0% responding “yes” for the Static group. The graphic organizers in the study are known as adjunct displays and therefore each was associated with an accompanying text passage. Participants had the capability of viewing the accompanying text passage at will within the constraints of a five-minute graphic organizer study period. Analysis of variance revealed that participants in the shuffle-sortable group spent significantly less time viewing the text passage than participants in the static group, possibly because the overhead associated with the shuffle-sortable graphic organizer’s user interface controls consumed time or mental resources that would have otherwise been used to view the text. The results of this study suggest that dynamic graphic organizers are equivalent to traditional static graphic organizers, at least for the educational subject matter used in this study (comparative text comprising 204 words describing six fictitious species of fish, their attributes, and the relationships between these attributes) for measures related to accuracy. Additionally, participants in the two dynamic graphic organizer treatments took advantage of the affordances offered by those treatments (88.5% of the Sortable group sorted, 75.9% of the Shuffle-sort group sorted, and 88.9% of the Shuffle-sort group shuffled). This study may benefit both instructional designers and educational researchers as new curricula are designed and new instructional tools are studied, respectively.

As disciplinas de projeto requerem uma grande variedade de conhecimentos para sua realização. Para atender às necessidades didático-pedagógicas do ensino de projeto de produto, o processo de ensino-aprendizagem deve contar com material educacional capaz de fornecer ao aluno todas as informações necessárias para o seu desenvolvimento. A utilização de objetos de aprendizagem pode facilitar o processo de produção e entrega de materiais educacionais, assim como sua reutilização e recontextualização em diferentes cenários. Tal processo é possibilitado pelo atual estágio de desenvolvimento das Tecnologias de Informação e Comunicação (TICs), que permitem fácil acesso a produtos e serviços a elas relacionados. As TICs, aliadas às teorias de design instrucional, proporcionam o surgimento de novas gerações de Ensino a Distância (EaD), que agregam conteúdos educacionais a serviços baseados na web. Tal combinação dá origem a uma modalidade híbrida de ensino, unindo ferramentas de ensino presencial e a distância (Blended Learning). Este trabalho propõe uma ferramenta para a elaboração e a disponibilização de objetos de aprendizagem generativos integrada ao sistema HyperCAL online (sistema de comunicação e distribuição de conteúdo, baseado na web, desenvolvido e utilizado pelo Departamento de Design e Expressão Gráfica da Universidade Federal do Rio Grande do Sul — DEG-UFRGS). Desta forma, estes objetos podem ser reutilizados e recontextualizados para a elaboração de materiais educacionais. Nesta ferramenta, os objetos de aprendizagem generativos são estruturas construídas em XML, baseados no conceito learning design, funcionando como uma camada de interação entre os outros tipos de objeto de aprendizagem, organizando o conteúdo a ser disponibilizado. Para fins de validação da ferramenta criada, foi proposto um protótipo de unidade de aprendizagem de Projeto de Produto. Este protótipo teve como base um leaming design elaborado a partir de Padrões Pedagógicos levantados na fundamentação teórica do presente trabalho. Estes Padrões foram analisados, selecionados e organizados dentro de uma Linguagem de Padrões construída por um grupo de professores que atuam em disciplina do DEG-UFRGS, ligadas às linguagens e práticas de projeto, através das técnicas de cardsorting e grupo focal. / Design courses require a wide range of knowledge for its realization. To meet the needs of the didactic and pedagogical teaching of industrial design, the teaching-learning process must have educational material able to provide the student with all the information necessary for their development. The use of learning objects can facilitate the process of production and delivery of educational materials and their reuse and recontextualization in different scenarios. Such process is due to the current development stage of Information and Communication Technologies (ICTs), which allow easy access to products and services related to them. ICTs, combined with instructional design theories, lead to the emergence of new generations of distance learning, which add educational content to web based services. From this combination rises a hybrid mode of education, which combines tools for face-toface and distance learning (Blended Learning). This research proposes a tool for the development and provision of generative learning objects integrated into HyperCAL online (a web-based system of communication and content distribution, developed and used by the Departamento de Design e Expressão Gráfica da Universidade Federal do Rio Grande do Sul - DEG-UFRGS). Thus, these objects can be reused and recontextualized for the development of educational materials. In this tool, the generative learning objects are structures built on XML, based on the learning design concept, running as an interaction layer between the other types of learning object, organizing the content to be available. For the validation of the tool set, a prototype unit of learning of industrial design was proposed. This prototype was based on a learning design made upon pedagogical patterns raised in the theoretical foundation of this work. These patterns were analyzed, selected and arranged in a pattern language, built by a group of teachers who work in the disciplines of the DEG-UFRGS linked to the industrial design activity, through the card sorting and focus group techniques.

As disciplinas de projeto requerem uma grande variedade de conhecimentos para sua realização. Para atender às necessidades didático-pedagógicas do ensino de projeto de produto, o processo de ensino-aprendizagem deve contar com material educacional capaz de fornecer ao aluno todas as informações necessárias para o seu desenvolvimento. A utilização de objetos de aprendizagem pode facilitar o processo de produção e entrega de materiais educacionais, assim como sua reutilização e recontextualização em diferentes cenários. Tal processo é possibilitado pelo atual estágio de desenvolvimento das Tecnologias de Informação e Comunicação (TICs), que permitem fácil acesso a produtos e serviços a elas relacionados. As TICs, aliadas às teorias de design instrucional, proporcionam o surgimento de novas gerações de Ensino a Distância (EaD), que agregam conteúdos educacionais a serviços baseados na web. Tal combinação dá origem a uma modalidade híbrida de ensino, unindo ferramentas de ensino presencial e a distância (Blended Learning). Este trabalho propõe uma ferramenta para a elaboração e a disponibilização de objetos de aprendizagem generativos integrada ao sistema HyperCAL online (sistema de comunicação e distribuição de conteúdo, baseado na web, desenvolvido e utilizado pelo Departamento de Design e Expressão Gráfica da Universidade Federal do Rio Grande do Sul — DEG-UFRGS). Desta forma, estes objetos podem ser reutilizados e recontextualizados para a elaboração de materiais educacionais. Nesta ferramenta, os objetos de aprendizagem generativos são estruturas construídas em XML, baseados no conceito learning design, funcionando como uma camada de interação entre os outros tipos de objeto de aprendizagem, organizando o conteúdo a ser disponibilizado. Para fins de validação da ferramenta criada, foi proposto um protótipo de unidade de aprendizagem de Projeto de Produto. Este protótipo teve como base um leaming design elaborado a partir de Padrões Pedagógicos levantados na fundamentação teórica do presente trabalho. Estes Padrões foram analisados, selecionados e organizados dentro de uma Linguagem de Padrões construída por um grupo de professores que atuam em disciplina do DEG-UFRGS, ligadas às linguagens e práticas de projeto, através das técnicas de cardsorting e grupo focal. / Design courses require a wide range of knowledge for its realization. To meet the needs of the didactic and pedagogical teaching of industrial design, the teaching-learning process must have educational material able to provide the student with all the information necessary for their development. The use of learning objects can facilitate the process of production and delivery of educational materials and their reuse and recontextualization in different scenarios. Such process is due to the current development stage of Information and Communication Technologies (ICTs), which allow easy access to products and services related to them. ICTs, combined with instructional design theories, lead to the emergence of new generations of distance learning, which add educational content to web based services. From this combination rises a hybrid mode of education, which combines tools for face-toface and distance learning (Blended Learning). This research proposes a tool for the development and provision of generative learning objects integrated into HyperCAL online (a web-based system of communication and content distribution, developed and used by the Departamento de Design e Expressão Gráfica da Universidade Federal do Rio Grande do Sul - DEG-UFRGS). Thus, these objects can be reused and recontextualized for the development of educational materials. In this tool, the generative learning objects are structures built on XML, based on the learning design concept, running as an interaction layer between the other types of learning object, organizing the content to be available. For the validation of the tool set, a prototype unit of learning of industrial design was proposed. This prototype was based on a learning design made upon pedagogical patterns raised in the theoretical foundation of this work. These patterns were analyzed, selected and arranged in a pattern language, built by a group of teachers who work in the disciplines of the DEG-UFRGS linked to the industrial design activity, through the card sorting and focus group techniques.

As disciplinas de projeto requerem uma grande variedade de conhecimentos para sua realização. Para atender às necessidades didático-pedagógicas do ensino de projeto de produto, o processo de ensino-aprendizagem deve contar com material educacional capaz de fornecer ao aluno todas as informações necessárias para o seu desenvolvimento. A utilização de objetos de aprendizagem pode facilitar o processo de produção e entrega de materiais educacionais, assim como sua reutilização e recontextualização em diferentes cenários. Tal processo é possibilitado pelo atual estágio de desenvolvimento das Tecnologias de Informação e Comunicação (TICs), que permitem fácil acesso a produtos e serviços a elas relacionados. As TICs, aliadas às teorias de design instrucional, proporcionam o surgimento de novas gerações de Ensino a Distância (EaD), que agregam conteúdos educacionais a serviços baseados na web. Tal combinação dá origem a uma modalidade híbrida de ensino, unindo ferramentas de ensino presencial e a distância (Blended Learning). Este trabalho propõe uma ferramenta para a elaboração e a disponibilização de objetos de aprendizagem generativos integrada ao sistema HyperCAL online (sistema de comunicação e distribuição de conteúdo, baseado na web, desenvolvido e utilizado pelo Departamento de Design e Expressão Gráfica da Universidade Federal do Rio Grande do Sul — DEG-UFRGS). Desta forma, estes objetos podem ser reutilizados e recontextualizados para a elaboração de materiais educacionais. Nesta ferramenta, os objetos de aprendizagem generativos são estruturas construídas em XML, baseados no conceito learning design, funcionando como uma camada de interação entre os outros tipos de objeto de aprendizagem, organizando o conteúdo a ser disponibilizado. Para fins de validação da ferramenta criada, foi proposto um protótipo de unidade de aprendizagem de Projeto de Produto. Este protótipo teve como base um leaming design elaborado a partir de Padrões Pedagógicos levantados na fundamentação teórica do presente trabalho. Estes Padrões foram analisados, selecionados e organizados dentro de uma Linguagem de Padrões construída por um grupo de professores que atuam em disciplina do DEG-UFRGS, ligadas às linguagens e práticas de projeto, através das técnicas de cardsorting e grupo focal. / Design courses require a wide range of knowledge for its realization. To meet the needs of the didactic and pedagogical teaching of industrial design, the teaching-learning process must have educational material able to provide the student with all the information necessary for their development. The use of learning objects can facilitate the process of production and delivery of educational materials and their reuse and recontextualization in different scenarios. Such process is due to the current development stage of Information and Communication Technologies (ICTs), which allow easy access to products and services related to them. ICTs, combined with instructional design theories, lead to the emergence of new generations of distance learning, which add educational content to web based services. From this combination rises a hybrid mode of education, which combines tools for face-toface and distance learning (Blended Learning). This research proposes a tool for the development and provision of generative learning objects integrated into HyperCAL online (a web-based system of communication and content distribution, developed and used by the Departamento de Design e Expressão Gráfica da Universidade Federal do Rio Grande do Sul - DEG-UFRGS). Thus, these objects can be reused and recontextualized for the development of educational materials. In this tool, the generative learning objects are structures built on XML, based on the learning design concept, running as an interaction layer between the other types of learning object, organizing the content to be available. For the validation of the tool set, a prototype unit of learning of industrial design was proposed. This prototype was based on a learning design made upon pedagogical patterns raised in the theoretical foundation of this work. These patterns were analyzed, selected and arranged in a pattern language, built by a group of teachers who work in the disciplines of the DEG-UFRGS linked to the industrial design activity, through the card sorting and focus group techniques.

Presented thesis explores the ground at the intersection of three topics: education, relational thinking and economics. Within the sphere of economic education it investigates the use of concepts known from (i) conceptual metaphor theory, (ii) psychological model of analogical reasoning, (iii) model of generative learning from educational psychology and (iv) existing research on use of metaphors and analogies in natural sciences education. Thesis shows the potential of metaphorical origin of economic terminology for teaching economic concepts and educational use of economic media content. At the same time it proposes a notation for visualizing metaphorical mappings between domains. It addresses economic interpretation from the viewpoint of the relationship between theoretical economic models and actual economic situations, as well as from the viewpoint of the relationship between mathematical structure of the model and its economic meaning. In the first case, it shows interpretative skill, being framed within the revised Bloom taxonomy, as a complex cognitive task, in the second case it develops model of economic interpretation of mathematical structures on the basis of psychological model of analogical reasoning. In both cases it formulates highlights students should know about the analogical nature of economic models. On the basis of the model of generative learning it develops a set of visual methaphors applicable in the introductory topics of microeconomics and macroeconomics and examines effects of their use in the classes of economics. By undertaking such research it initiates the exploration of paths leading in the directions suggested by the theoretical analysis.

The task of Phone recognition is a fundamental task in Speech recognition and often serves a critical role in bench-marking purposes. Researchers have used a variety of models used in the past to address this task, using both generative and discriminative learning approaches. Among them, generative approaches such as the use of Gaussian mixture model-based hidden Markov models are always favored because of their mathematical tractability. However, the use of generative models such as hidden Markov models and its hybrid varieties is no longer in fashion owing to a large inclination to discriminative learning approaches, which have been found to perform better. The only downside is that these approaches do not always ensure mathematical tractability or convergence guarantees as opposed to their generative counterparts. So, the research problem was to investigate whether there could be a process of augmenting the modeling capability of generative Models using a kind of neural network based architectures that could simultaneously prove mathematically tractable and expressive. Normalizing flows are a class of generative models that have been garnered a lot of attention recently in the field of density estimation and offer a method for exact likelihood computation and inference. In this project, a few varieties of Normalizing flow-based hidden Markov models were used for the task of Phone recognition on the TIMIT dataset. It was been found that these models and their mixture model varieties outperformed classical generative model varieties like Gaussian mixture models. A decision fusion approach using classical Gaussian and Normalizing flow-based mixtures showed competitive results compared to discriminative learning approaches. Further analysis based on classes of speech phones was carried out to compare the generative models used. Additionally, a study of the robustness of these algorithms to noisy speech conditions was also carried out. / Uppgiften för fonemigenkänning är en grundläggande uppgift i taligenkänning och tjänar ofta en kritisk roll i benchmarkingändamål. Forskare har använt en mängd olika modeller som använts tidigare för att hantera denna uppgift genom att använda både generativa och diskriminerande inlärningssätt. Bland dem är generativa tillvägagångssätt som användning av Gaussian-blandnings modellbaserade dolda Markov-modeller alltid föredragna på grund av deras matematiska spårbarhet. Men användningen av generativa modeller som dolda Markov-modeller och dess hybridvarianter är inte längre på mode på grund av en stor lutning till diskriminerande inlärningsmetoder, som har visat sig fungera bättre. Den enda nackdelen är att dessa tillvägagångssätt inte alltid säkerställer matematisk spårbarhet eller konvergensgarantier i motsats till deras generativa motsvarigheter. Således var forskningsproblemet att undersöka om det kan finnas en process för att förstärka modelleringsförmågan hos generativa modeller med hjälp av ett slags neurala nätverksbaserade arkitekturer som samtidigt kunde visa sig matematiskt spårbart och uttrycksfullt. Normaliseringsflöden är en klass generativa modeller som nyligen har fått mycket uppmärksamhet inom området för densitetsberäkning och erbjuder en metod för exakt sannolikhetsberäkning och slutsats. I detta projekt användes några få varianter av Normaliserande flödesbaserade dolda Markov-modeller för uppgiften att fonemigenkänna i TIMIT-datasatsen. Det visade sig att dessa modeller och deras blandningsmodellvarianter överträffade klassiska generativa modellvarianter som Gaussiska blandningsmodeller. Ett beslutssmältningsstrategi med klassiska Gaussiska och Normaliserande flödesbaserade blandningar visade konkurrenskraftiga resultat jämfört med diskriminerande inlärningsmetoder. Ytterligare analys baserat på klasser av talsignaler utfördes för att jämföra de generativa modellerna som användes. Dessutom genomfördes en studie av robustheten hos dessa algoritmer till bullriga talförhållanden.