1,452 research outputs found
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Meter Scoping Study
This report presents a summary of metering technology and cost information from past studies in an attempt to identify key barriers to more widespread implementation
STARC: Structured Annotations for Reading Comprehension
We present STARC (Structured Annotations for Reading Comprehension), a new
annotation framework for assessing reading comprehension with multiple choice
questions. Our framework introduces a principled structure for the answer
choices and ties them to textual span annotations. The framework is implemented
in OneStopQA, a new high-quality dataset for evaluation and analysis of reading
comprehension in English. We use this dataset to demonstrate that STARC can be
leveraged for a key new application for the development of SAT-like reading
comprehension materials: automatic annotation quality probing via span ablation
experiments. We further show that it enables in-depth analyses and comparisons
between machine and human reading comprehension behavior, including error
distributions and guessing ability. Our experiments also reveal that the
standard multiple choice dataset in NLP, RACE, is limited in its ability to
measure reading comprehension. 47% of its questions can be guessed by machines
without accessing the passage, and 18% are unanimously judged by humans as not
having a unique correct answer. OneStopQA provides an alternative test set for
reading comprehension which alleviates these shortcomings and has a
substantially higher human ceiling performance.Comment: ACL 2020. OneStopQA dataset, STARC guidelines and human experiments
data are available at https://github.com/berzak/onestop-q
Changing practice in Malaysian primary schools: learning from student teachers’ reports of using action, reflection and modelling (ARM)
This is an Accepted Manuscript of an article published by Taylor & Francis in Journal of Education for Teaching on 15 March 2018, available online at doi: https://doi.org/10.1080/02607476.2018.1433468. Under embargo until 1 August 2019.Curricular and pedagogical reforms are complex inter-linked processes such that curricular reform can only be enacted through teachers teaching differently. This article reports the perspective of emergent Malaysian primary teachers who were expected to implement a Government reform that promoted active learning. The 120 student teachers were members of a single cohort completing a new B.Ed. degree programme in Primary Mathematics designed by teacher educators from Malaysia and the UK. They were taught to use a tripartite pedagogical framework involving action or active learning, supported in practice through reflection and modelling. Drawing on findings from surveys carried out with the student teachers at the end of their first and final placements this article examines evidence for the premise that the student teachers were teaching differently; illustrates how they reported using active learning strategies; and identifies factors that enabled and constrained pedagogic change in the primary classroom. The students’ accounts of using action, reflection and modelling are critiqued in order to learn about changing learning and teaching practice and to contribute to understanding teacher education and early teacher development. The students’ reports suggest diversity of understanding that emphasises the need to challenge assumptions when working internationally and within national and local cultures.Peer reviewe
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HEI school partnership in initial teacher training: the balance of HEI-school responsibilities for, and the nature of, secondary PGCE courses
This study examines the balance of HEI-school responsibilities for secondary PGCE courses, and extends previous work in this dimension of partnership by moving beyond the perspective of HEI course managers through content analysis of HEI course documentation and interviews with HEI course leaders. The views of mentor, school ITT co-ordinator, university tutor, and student participants in these courses were also examined, through a questionnaire survey across ten HEI-school partnerships. More specifically, the aim has been to examine the balance of HEI-school responsibility for: course planning and organisation; the assessment of students' teaching; and the assessment of students' work other than teaching. Here, as in other aspects of the study, the experience of participants has been analysed at the level of the overall course, and from the perspective of each of the participant roles. A second, more extensive, aim of the study has been to establish the nature of these courses, particularly within a framework of what may be ailed 'technical', 'interpretive', and 'critical' conceptions of teaching This model has also been extended to the importance placed upon the foci of students' reflection, and other aspects of the nature of teachers', tutors' and students' work on PGCE courses. The implications of these course characteristics in terms of the forms of teacher professionalism associated with them provides a complementary theme which runs through the study. The latter part of this thesis includes a survey of four School Centred Initial Teacher Training Schemes. Differences between data from the HEI documentation, and the perspectives of HEI course leaders, and the teacher, tutor, and student participants have been examined. The association between the balance of HEI-school responsibilities and the nature of courses was also examined, with particular reference to the evident association of shared HEI-school course responsibilities with course experiences, which may support the development of extended forms of professionalism
The neural dynamics of auditory word recognition and integration
Listeners recognize and integrate words in rapid and noisy everyday speech by
combining expectations about upcoming content with incremental sensory
evidence. We present a computational model of word recognition which formalizes
this perceptual process in Bayesian decision theory. We fit this model to
explain scalp EEG signals recorded as subjects passively listened to a
fictional story, revealing both the dynamics of the online auditory word
recognition process and the neural correlates of the recognition and
integration of words.
The model reveals distinct neural processing of words depending on whether or
not they can be quickly recognized. While all words trigger a neural response
characteristic of probabilistic integration -- voltage modulations predicted by
a word's surprisal in context -- these modulations are amplified for words
which require more than roughly 100 ms of input to be recognized. We observe no
difference in the latency of these neural responses according to words'
recognition times.Our results support a two-part model of speech comprehension,
combining an eager and rapid process of word recognition with a temporally
independent process of word integration
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