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Transitioning to ICT Enabled Continuous and Comprehensive evaluation – Reducing teacher workload

Publication Type : Conference Paper

Thematic Areas : Learning-Technologies

Publisher : in press, 3rd International Conference on Machine Learning and Computing, Singapore .

Source : In press, 3rd International Conference on Machine Learning and Computing", Singapore (2011)

Keywords : Continuous and Comprehensive evaluation, ICT

Campus : Amritapuri

School : School of Engineering

Center : AmritaCREATE

Department : Computer Science and Engineering

Year : 2011

Abstract : Teacher workload has been a recurrent concern in education in England and Wales for a number of years. One possible solution that has been put forward is the greater use of information and communications technology (ICT). In the spring of 2002, the Department for Education and Skills (DfES) launched a 1‐year initiative called the Transforming School Workforce (TSW) Pathfinder Project, and this was evaluated by a team from the University of Birmingham. One of the ways of reducing teachers' workload envisaged by the DfES was increased use of ICT. The data presented in this article comes from the aforementioned evaluation and concerns teachers changing perceptions of, access to, issues relating to training in, and use of ICT, and their beliefs concerning the use of ICT. Overall, teachers believed the TSW Project helped to reduce workload, making them more productive as teachers. Changes likely to have contributed to this included: far greater access to ICT facilities both in terms of hardware at home, and sole access at school; increased daily use of ICT by teachers; an increase in teachers' confidence in the use of ICT and changes in teachers' views on the quality of ICT training (although their satisfaction with training received was still not high).

Cite this Research Publication : R. Raman and Prema Nedungadi, “Transitioning to ICT Enabled Continuous and Comprehensive evaluation – Reducing teacher workload”, in in press, 3rd International Conference on Machine Learning and Computing", Singapore, 2011.

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