The Swedish curriculum emphasizes the importance of pupils’ active learning, influence over the education and communicative skills in language learning. The Storyline approach has since its entry in the educational context in the 1960s, influenced teaching all over the world. The approach emphasizes pupils’ interest, meaning-making processes and creativity and thus agrees well with the content of the Swedish curriculum. This research overview aims to offer insight into how the Storyline approach can affect pupils in an English as a second language context, in different ways. It focuses primarily on how the Storyline approach can promote pupils’ second language acquisition, what impact the story and its characters have on pupils’ motivation and what effects the aesthetics in Storyline have on pupils. It also gives an overview of challenges that pupils and teachers might encounter while working with a Storyline project. The findings of the study indicate that the Storyline approach, through group work and communicative, meaningful tasks, promote pupils’ learning of English. Moreover, the context of the story and the characters seem to enhance pupils’ intrinsic motivation to learn the English language and the aesthetics can make pupil active agents in their learning process and mediate their knowledge. However, the Storyline approach also involves different challenges for both pupils and teachers, such as trying to find a balance between the teacher’s and the pupils’ control, keeping the story and the characters alive throughout the whole project, dealing with lack of time, group work issues and presenting the work in front of other pupils.

Machine translation is a fundamental technology that is gaining more importance each day in our multilingual society. Companies and particulars are turning their attention to machine translation since it dramatically cuts down their expenses on translation and interpreting. However, the output of current machine translation systems is still far from the quality of translations generated by human experts. The overall goal of this thesis is to narrow down this quality gap by developing new methodologies and tools that improve the broader and more efficient deployment of machine translation technology. We start by proposing a new technique to improve the quality of the translations generated by fully-automatic machine translation systems. The key insight of our approach is that different translation systems, implementing different approaches and technologies, can exhibit different strengths and limitations. Therefore, a proper combination of the outputs of such different systems has the potential to produce translations of improved quality. We present minimum Bayes¿ risk system combination, an automatic approach that detects the best parts of the candidate translations and combines them to generate a consensus translation that is optimal with respect to a particular performance metric. We thoroughly describe the formalization of our approach as a weighted ensemble of probability distributions and provide efficient algorithms to obtain the optimal consensus translation according to the widespread BLEU score. Empirical results show that the proposed approach is indeed able to generate statistically better translations than the provided candidates. Compared to other state-of-the-art systems combination methods, our approach reports similar performance not requiring any additional data but the candidate translations. Then, we focus our attention on how to improve the utility of automatic translations for the end-user of the system. Since automatic translations are not perfect, a desirable feature of machine translation systems is the ability to predict at run-time the quality of the generated translations. Quality estimation is usually addressed as a regression problem where a quality score is predicted from a set of features that represents the translation. However, although the concept of translation quality is intuitively clear, there is no consensus on which are the features that actually account for it. As a consequence, quality estimation systems for machine translation have to utilize a large number of weak features to predict translation quality. This involves several learning problems related to feature collinearity and ambiguity, and due to the ¿curse¿ of dimensionality. We address these challenges by adopting a two-step training methodology. First, a dimensionality reduction method computes, from the original features, the reduced set of features that better explains translation quality. Then, a prediction model is built from this reduced set to finally predict the quality score. We study various reduction methods previously used in the literature and propose two new ones based on statistical multivariate analysis techniques. More specifically, the proposed dimensionality reduction methods are based on partial least squares regression. The results of a thorough experimentation show that the quality estimation systems estimated following the proposed two-step methodology obtain better prediction accuracy that systems estimated using all the original features. Moreover, one of the proposed dimensionality reduction methods obtained the best prediction accuracy with only a fraction of the original features. This feature reduction ratio is important because it implies a dramatic reduction of the operating times of the quality estimation system. An alternative use of current machine translation systems is to embed them within an interactive editing environment where the system and a human expert collaborate to generate error-free translations. This interactive machine translation approach have shown to reduce supervision effort of the user in comparison to the conventional decoupled post-edition approach. However, interactive machine translation considers the translation system as a passive agent in the interaction process. In other words, the system only suggests translations to the user, who then makes the necessary supervision decisions. As a result, the user is bound to exhaustively supervise every suggested translation. This passive approach ensures error-free translations but it also demands a large amount of supervision effort from the user. Finally, we study different techniques to improve the productivity of current interactive machine translation systems. Specifically, we focus on the development of alternative approaches where the system becomes an active agent in the interaction process. We propose two different active approaches. On the one hand, we describe an active interaction approach where the system informs the user about the reliability of the suggested translations. The hope is that this information may help the user to locate translation errors thus improving the overall translation productivity. We propose different scores to measure translation reliability at the word and sentence levels and study the influence of such information in the productivity of an interactive machine translation system. Empirical results show that the proposed active interaction protocol is able to achieve a large reduction in supervision effort while still generating translations of very high quality. On the other hand, we study an active learning framework for interactive machine translation. In this case, the system is not only able to inform the user of which suggested translations should be supervised, but it is also able to learn from the user-supervised translations to improve its future suggestions. We develop a value-of-information criterion to select which automatic translations undergo user supervision. However, given its high computational complexity, in practice we study different selection strategies that approximate this optimal criterion. Results of a large scale experimentation show that the proposed active learning framework is able to obtain better compromises between the quality of the generated translations and the human effort required to obtain them. Moreover, in comparison to a conventional interactive machine translation system, our proposal obtained translations of twice the quality with the same supervision effort. / González Rubio, J. (2014). On the effective deployment of current machine translation technology [Tesis doctoral]. Universitat Politècnica de València. https://doi.org/10.4995/Thesis/10251/37888

The U.S. Marshallese population is one of the fastest growing Pacific Islander populations in the United States. The purpose of this study was to identify how U.S. Marshallese students could be empowered and engaged in their learning through clearly identified indicators that educators could apply within their classrooms and schools. The indicators have been established on a historical, cultural, and linked perceptions of student learning as identified by U.S. Marshallese students and teachers. Pacific Islanders consisted of a variety of populations with varying cultures and ethnic diversity. This study has been conducted using a postpositivism worldview, Marshallese migration is not a limited phenomenon of displacement, but a migratory change that must be embraced by communities and educators. Educators must understand how to empower and engage U.S. Marshallese students in their learning. This study was designed utilizing an interpretative descriptive naturalistic ethnography qualitative research design with middle school students and teachers to gather qualitative data from U.S. Marshallese students that will lead to a contextual understanding of empowering and engaging U.S. Marshallese students in their learning. The findings of this qualitative research study can be applied by educators to empower and engage U.S. Marshallese students in their learning on a daily basis in schools and classrooms. Culture understanding, positive relationship building, and the design of culturally connected intrinsically student motivated learning activities is the foundation and critical component of empowering and engaging U.S. Marshallese students in school and classrooms for improved student learning.

Agricultural and educational researchers recognize the critical value of an integrated, multidisciplinary approach to education in building a food-secure world, reducing poverty, and conserving and enhancing natural resources. However, schools generally contribute little to communities in the context of food growing and environmental learning. The main objective of this qualitative research was to explore the role of school-community relationships in enabling environmental learning in the context of food growing activities. Findings suggest that the role of school-community links in enhancing environmental learning is more likely where community members are actively involved in school programs that have an emphasis on an experiential learning approach. However, this depends to a large extent on the availability of parents or concerned community members and their willingness to engage in voluntary school-based activities. Factors that could potentially strengthen the role of school-community links in supporting environmental learning include: allowing space for informal learning, mediating learning in civil society settings, ongoing facilitation by a committed coordinator, community buy-in and accountability, and addressing public interests through tangible benefits. A major challenge is to find an appropriate balance between social justice and practical food security concerns, while remaining true to ecological considerations.

Title: Educational projects focused on the area of Milíčov forest and ponds. This graduation thesis deals with project education in the field of natural monument Milíčov forest and ponds. It directly borders with southern city housing estate. Result of this work is a collection of materials focusing on environmental education and upbringing pupils on 2nd stage of basic schools, which are located near this monument. These are mainly a methodology for teachers, manual to the project education, worksheets for pupils and creative solution of worksheets for teachers. The starting point for creating projects has been a partial study, questionnaire and open discussion with students. Teoretical part at its beginning describes general conservation and special nature protection, to place issues in a boarder context. The historical aspect is also mentioned. In the thesis are also defined Milíčov forests and ponds characteristics, taking into account their rarities. It is mainly dealt with occurring of important species and specially protected species in this area. In my work is also given the emphasis on the General educational program, environmental education, analysis of schoolbooks and organizational forms of teaching. I bear on didactic theory of which I issued in projects creating. Keywords: General...

Text in English / In a quest to identify best practices in teaching courses in English for Specific Purposes (ESP), this study investigated effective teaching of an online English module in an Open Distance Learning (ODL) environment. Although ODL is attractive to both students and lecturers, there are significant problems regarding how learning, teaching, interaction and assessment should be conducted in this context. The problems are exacerbated by the limited knowledge of using the online systems and constraints linked to time spent on tasks. The study adopted the qualitative research approach, using a case study design and data collected from three research instruments, namely online questionnaires, an online observation schedule and a content analysis schedule. The research population in the current study comprised students, lecturers, and e-tutors based at one ODL university. In order to engender best practices of effective teaching in an ODL environment, the Community of Inquiry (Col) framework and Zone of Proximal Development (ZPD) theory were applied to the research findings of the current study. The findings indicate that effective teaching of an online English module in an ODL context could take place when content is effectively structured; assessment reflects course content; there is teamwork and collaboration amongst lecturers; students effectively interact with the material, lecturers/e-tutors, and with each other. The findings of this study add to the volume of research on best practices for effective online ESP teaching in ODL higher learning institutions. / English Studies / D. Litt. et Phil. (English)

Les villes sont confrontées à de nombreuses problématiques environnementales. Leurs gestionnaires ont besoin d'outils et d'une bonne connaissance de leur territoire. Un objectif est de mieux comprendre comment s'articulent les trames grise et verte pour les analyser et les représenter. Il s'agit aussi de proposer une méthodologie pour cartographier la structure urbaine à l'échelle des tissus en tenant compte de ces trames. Les bases de données existantes ne cartographient pas la végétation de manière exhaustive. Ainsi la première étape est d'extraire la végétation arborée et herbacée à partir d'images satellites Pléiades par une analyse orientée-objet et une classification par apprentissage actif. Sur la base de ces classifications et de données multi-sources, la cartographie des tissus se base sur une démarche d'extraction de connaissances à partir d'indicateurs issus de l'urbanisme et de l'écologie du paysage. Cette méthodologie est construite sur Strasbourg puis appliquée à Rennes. / Climate change presents cities with significant environmental challenges. Urban planners need decision-making tools and a better knowledge of their territory. One objective is to better understand the link between the grey and the green infrastructures in order to analyse and represent them. The second objective is to propose a methodology to map the urban structure at urban fabric scale taking into account the grey and green infrastructures. In current databases, vegetation is not mapped in an exhaustive way. Therefore the first step is to extract tree and grass vegetation using Pléiades satellite images using an object-based image analysis and an active learning classification. Based on those classifications and multi-sources data, an approach based on knowledge discovery in databases is proposed. It is focused on set of indicators mostly coming from urbanism and landscape ecology. The methodology is built on Strasbourg and applied on Rennes to validate and check its reproducibility.

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We present a new course titled “Introduction to the Mathematical Sciences.” The course content is 1/3 algebra, 1/3 statistics, and 1/3 computer science and is taught in a laboratory environment on computers. The course pedagogy departs radically from traditional mathematics courses taught in the U.S. and makes extensive use of spreadsheet software to teach algebraic and statistical concepts. The course is currently offered in area high schools and two-year postsecondary institutions with financial support from a Blandin Foundation grant (referenced under BFG). We will present empirical evidence that indicates students in this course learn more algebra than students in a traditional semester-long algebra course. Additionally, we present empirical evidence that students learn statistical and computer science topics in addition to algebra. We will also present the model of developing this course which depended on increasing future student success in a variety of disciplines at the post-secondary level of study.

There has been a growing need in environmental education to develop students' ability and will to take part in democratic processes that enable them take environmental action in their local environment. This study examined learner action competence in waste management practices in two primary school contexts in the Eastern Cape, South Africa. An interpretive case study design is used to probe how learner participation in Eco-School waste management practices enabled the acquisition of knowledge in purposeful learning and action experiences that developed the vision and agency of informed action. The research was centred on two guiding questions: 1. How informed, purposeful and action-orientated is learner participation in Eco-School waste management activities? 2. What Eco-School waste management activities are fostering active participation towards a learner-led agency? Educators in the two schools were interviewed and Eco-School portfolios were examined for evidence of the learning activities and learner achievement. This provided the contextual data for reviewing focus group interviews to probe what was significant to learners, what they came to know and how they had contributed to the process of developing better waste management in the Eco-School context. The evidence generated in the study was used to identify the roles of the various players, the significant activities and processes that enabled and constrained the emergence of learner-led agency. The main findings in the study were that teacher intentionality and school management ethos were significant in engaging learners in meaningful waste management activities in both cases. The study also revealed that although most of the waste management activities in both cases were teacher-initiated, there were spaces open for learner initiatives. However, it appeared that the activity based waste management practices mostly allowed learners to learn how to do waste management more than allowing them to find out more about the scope and nature of ii the problem of waste. This then resulted in learners talking more about what they were doing with waste than talking about what they knew about waste. There were differences in the way in which learners approached waste in the two cases. In the one case, Kingswood Junior School learners used waste artistically and carried out activities that allowed for better use of waste resources like paper while in the other School, Grahamstown SDA School, learners approached waste as a resource for making money. However, in both cases, learners appeared to enjoy the positive experiences of doing things that contributed to a cleaner environment and were of benefit to others and this gave them a sense of pride to share their experiences with others. This study was significant as it allowed me to probe learner participation and examine the development of their action competence through listening to the voices of the learners themselves and understanding what was important to them about the knowledge they gained and their vision of better waste management.