Ten Australian elementary teachers' discourse and reported pedagogical practices during cooperative learning

This article describes the types of discourse 10 Australian grade 4-6 teachers used after they had been trained to embed cooperative learning in their curriculum and to use communication skills to promote students' thinking and to scaffold their learning. One audiotaped classroom social science lesson involving cooperative learning was analyzed for each teacher. We provide vignettes from 2 teachers as they worked with groups and from 2 student groups. The data from the audiotapes showed that the teachers used a range of mediated-learning behaviors in their interactions with the children that included challenging their perspectives, asking more cognitive and metacognitive questions, and scaffolding their learning. In turn, in their interactions with each other, the children modelled many of the types of discourse they heard their teachers use. Follow-up interviews with the teachers revealed that they believed it was important to set expectations for children's group behaviors, teach the social skills students needed to deal with disagreement in groups, and establish group structures so children understood what was required both from each other and the task. The teachers reported that mixed ability and gender groups worked best and that groups should be no larger than 5 students. All teachers' programs were based on a child-centered philosophy that recognized the importance of constructivist approaches to learning and the key role interaction plays in promoting social reasoning and learning.

Teaching and learning German language and culture in higher education in Britain:problems, challenges and didactical implications. A case study

The aim of this thesis is to explore key aspects and problems of the institutionalised teaching and learning of German language and culture in the context of German Studies in British Higher Education (HE). This investigation focuses on teaching and learning experiences in one department of German Studies in the UK, which is the micro-context of the present study, in order to provide an in-depth insight into real-life problems, strengths and weaknesses as they occur in the practice of teaching and learning German. Following Lamb (2004) and Holliday (1994), the present study acts on the assumption that each micro-context does not exist in vacuo but is always embedded in a wider socio-political and education environment, namely the macro-context, which largely determines how and what is taught. The macro-analysis of the present study surveys the socio-political developments that have recently affected the sector of modern languages and specifically the discipline of German Studies in the UK. It demonstrates the impact they have had on teaching and learning German at the undergraduate level in Britain. This context is interesting inasmuch as the situation in Britain is to a large extent a paradigmatic example of the developments in German Studies in English-speaking countries. Subsequently, the present study explores learning experiences of a group of thirty-five first year students. It focuses on their previous experiences in learning German, exposure to the target language, motivation, learning strategies and difficulties encountered, when learning German at the tertiary level. Then, on the basis of interviews with five lecturers of German, teaching experience in the context under study is explored, problems and successful teaching strategies discussed.

Using computer concordancing for the learning of French as a second language

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Semi-supervised learning of statistical models for natural language understanding

Natural language understanding is to specify a computational model that maps sentences to their semantic mean representation. In this paper, we propose a novel framework to train the statistical models without using expensive fully annotated data. In particular, the input of our framework is a set of sentences labeled with abstract semantic annotations. These annotations encode the underlying embedded semantic structural relations without explicit word/semantic tag alignment. The proposed framework can automatically induce derivation rules that map sentences to their semantic meaning representations. The learning framework is applied on two statistical models, the conditional random fields (CRFs) and the hidden Markov support vector machines (HM-SVMs). Our experimental results on the DARPA communicator data show that both CRFs and HM-SVMs outperform the baseline approach, previously proposed hidden vector state (HVS) model which is also trained on abstract semantic annotations. In addition, the proposed framework shows superior performance than two other baseline approaches, a hybrid framework combining HVS and HM-SVMs and discriminative training of HVS, with a relative error reduction rate of about 25% and 15% being achieved in F-measure.

E-Support for English Language Course to Enhance University Students’ Learning.

The peculiarities of English language teaching for students at higher educational establishment using some elements of distance learning, developed by the author, are described in this article. The results of students’ questioning, received at the end of the experimental teaching, are suggested and analyzed. The conclusions are formulated and the further ways of teaching English with e-support are outlined.