192,645 research outputs found
Teacher training processes and teachers' competence : A sociological study in the primary school
The paper describes part of a study whose aim was to investigate the relation between
modalities of teacher training and modalities of pedagogic practice implemented in the science classroom. The study is focused on primary school context and analyses the evolution of teachers performance in terms of their acquisition of recognition and realisation rules, i.e.
coding orientation, to specific scientific learning contexts.
Theoretically, the study is based on Bernstein’s theory of pedagogic discourse (1999, 2000)which provided the concepts to characterise the modalities of teacher training and of classroom pedagogic practices and to analyse teachers’ evolution in terms of recognition and realisation rules. The sample was made up of four teachers and their four socially
heterogeneous school classes. An action-research methodology was followed.The results suggest that the teacher training implemented was favourable to the teachers’
professional development and their competence to lead all children to a high level of scientific development. The efficiency of the training process has to be mostly attributed to the strong classification of the researcher-teachers relation and to the strong framing of evaluation criteria, selection and sequence, together with weak framing of hierarchical rules and pacing.Fundação Calouste Gulbenkian, Instituto de Inovação Educacional e Fundação para a Ciência e Tecnologia (FCT)
Learning Sentence-internal Temporal Relations
In this paper we propose a data intensive approach for inferring
sentence-internal temporal relations. Temporal inference is relevant for
practical NLP applications which either extract or synthesize temporal
information (e.g., summarisation, question answering). Our method bypasses the
need for manual coding by exploiting the presence of markers like after", which
overtly signal a temporal relation. We first show that models trained on main
and subordinate clauses connected with a temporal marker achieve good
performance on a pseudo-disambiguation task simulating temporal inference
(during testing the temporal marker is treated as unseen and the models must
select the right marker from a set of possible candidates). Secondly, we assess
whether the proposed approach holds promise for the semi-automatic creation of
temporal annotations. Specifically, we use a model trained on noisy and
approximate data (i.e., main and subordinate clauses) to predict
intra-sentential relations present in TimeBank, a corpus annotated rich
temporal information. Our experiments compare and contrast several
probabilistic models differing in their feature space, linguistic assumptions
and data requirements. We evaluate performance against gold standard corpora
and also against human subjects
Diversity, Disadvantage and Differential Outcomes: An analysis of Samoan students narratives of schooling
Social justice discourses, particularly those attentive to the politics of difference, suggest that the perspectives of least-advantaged groups need to be taken into account when endeavouring to realise social justice in education for these groups. In this paper, we analyse narratives on schooling produced by one cohort of least-advantaged students, namely Samoan students attending state-designated disadvantaged secondary schools in Queensland, Australia. Specifically, the narratives of educational disadvantage provided by Samoan students are analysed. The focus is on 'the what' (the knowledge to be transmitted) and 'the how' (the teacher-student relations) of pedagogy in state-designated disadvantaged schools. Attention is paid to the contradictory and ambivalent discourses inherent in these narratives, particularly in terms of realising socially just pedagogic practices
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Generating monologue and dialogue to present personalised medical information to patients
Citizenship, community, and counter-terrorism : UK security discourse, 2001-2011
This paper analyses a corpus of UK policy documents which sets out national security policy as an exemplar of the contemporary discourse of counter-terrorism in Europe, the USA and worldwide. A corpus of 148 documents (c. 2.8 million words) was assembled to reflect the security discourse produced by the UK government before and after the 7/7 attacks on the London Transport system. To enable a chronological comparison, the two sub-corpora were defined: one relating to a discourse of citizenship and community cohesion (2001-2006); and one relating to the ‘Preventing Violent Extremism’ discourse (2007-2011). Wordsmith Tools (Scott 2008) was used to investigate keywords and patterns of collocation. The results present
themes emerging from a comparative analysis of the 100 strongest keywords in each sub- corpus; as well as a qualitative analysis of related patterns of the collocation, focusing inparticular on features of connotation and semantic prosody
Culture and E-Learning: Automatic Detection of a Users’ Culture from Survey Data
Knowledge about the culture of a user is especially important for the design
of e-learning applications. In the experiment reported here, questionnaire
data was used to build machine learning models to automatically predict the
culture of a user. This work can be applied to automatic culture detection
and subsequently to the adaptation of user interfaces in e-learning
Neural Discourse Structure for Text Categorization
We show that discourse structure, as defined by Rhetorical Structure Theory
and provided by an existing discourse parser, benefits text categorization. Our
approach uses a recursive neural network and a newly proposed attention
mechanism to compute a representation of the text that focuses on salient
content, from the perspective of both RST and the task. Experiments consider
variants of the approach and illustrate its strengths and weaknesses.Comment: ACL 2017 camera ready versio
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Youth Voice in the work of Creative Partnerships
This report summarises the findings of an 18-month research project into ‘Youth Voice in the work of Creative Partnerships ‘, 2007-9, conducted by Sara Bragg, Helen Manchester, Dorothy Faulkner at the Open University, funded by the Arts Council England.
Creative Partnerships (CP) was established in 2002 and is a ‘flagship creative learning programme’. It aims to foster innovative, long term collaborations between schools (often in areas of socio-economic deprivation) and creative practitioners. In particular CP states that it places young people ‘at the heart of what we do’ and claims that its programmes are most effective when young people are actively involved in leading and shaping them.
CP highlights three key areas: involving young people in governance (the design, delivery and evaluation of the programme of work); building and maintaining ‘positive relationships’ with young people; working as ‘co-constructors of learning’ with them.
The report maps existing youth voice initiatives in Creative Partnerships in those three areas. In addition, it considers the nature of the links between creativity and participation; explores issues of access to youth voice, such as patterns of inclusion and exclusion; explores what skills, experiences, identities and relationships are developed through participation. More broadly it attempts to understand, analyse and theorise youth voice, starting from the empirical but aiming to interpret the features of particular activities or projects to understand them more fully
Agents for educational games and simulations
This book consists mainly of revised papers that were presented at the Agents for Educational Games and Simulation (AEGS) workshop held on May 2, 2011, as part of the Autonomous Agents and MultiAgent Systems (AAMAS) conference in Taipei, Taiwan. The 12 full papers presented were carefully reviewed and selected from various submissions. The papers are organized topical sections on middleware applications, dialogues and learning, adaption and convergence, and agent applications
Parsing Argumentation Structures in Persuasive Essays
In this article, we present a novel approach for parsing argumentation
structures. We identify argument components using sequence labeling at the
token level and apply a new joint model for detecting argumentation structures.
The proposed model globally optimizes argument component types and
argumentative relations using integer linear programming. We show that our
model considerably improves the performance of base classifiers and
significantly outperforms challenging heuristic baselines. Moreover, we
introduce a novel corpus of persuasive essays annotated with argumentation
structures. We show that our annotation scheme and annotation guidelines
successfully guide human annotators to substantial agreement. This corpus and
the annotation guidelines are freely available for ensuring reproducibility and
to encourage future research in computational argumentation.Comment: Under review in Computational Linguistics. First submission: 26
October 2015. Revised submission: 15 July 201
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