A major challenge to contemporary education is to meet the Government’s directive, depicted in OFSTED guidelines and the Department for Education’s Teacher Standards that all our learners make progress, are autonomous and are able to engage in independent learning. However they offer no guidance as to how this can be achieved. The research has built on earlier theories to close the gap between Government measurements of the quality of teaching and twenty-first century educational theories, with particular focus on learning talk. The primary intention of this research was to determine the impact that dynamically dialogic learning conversations, that is learning talk, have on deepening learning, and how they may be used to enable teachers to meet OFSTED’s requirement for all students to make progress. The data for this case study was collected through a process of lesson observations, interviews and focus-group discussions over a period of one year. Sixteen lessons were video-recorded for a variety of topics and the recordings were analysed in depth against established theories of learning and the complex patterns and relationships between the different types of student and teacher learning talk observed in the classroom. The outcome of the analysis is a set of observable characteristics of learning talk which form an Observation Database. The findings support the premise that learning talk in the classroom leads to deeper learning. The Observation Database contains of a set of tools for observing, evaluating and enabling learning talk in the classroom and therefore offers teachers the opportunity to demonstrate OFSTED criteria. The process of developing the Observation Database and the tools developed have been shared both locally and nationally to heighten awareness of learning talk in the classroom and its link to deeper learning.
| Identifer | oai:union.ndltd.org:bl.uk/oai:ethos.bl.uk:665367 |
| Date | January 2014 |
| Creators | Williams, Sharon |
| Publisher | Anglia Ruskin University |
| Source Sets | Ethos UK |
| Detected Language | English |
| Type | Electronic Thesis or Dissertation |
| Source | http://arro.anglia.ac.uk/576179/ |
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