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SAT: How VLE's & Hygiene Factors via Blended Learning can aid long-term unemployed into work (Steven Durant-Burgin)
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19 December 2017
The topic that has been chosen for this project intersects Inclusion, Innovation and partially into Implementation.
Short Abstract for H818 Conference Presentation
How VLE's & Hygiene Factors via Blended Learning can aid long-term unemployed into work.For many years now, welfare to work programmes have worked in similar ways in regards to achieving their Key Performance Indicators. Beatty et al., (2011) states that the welfare to work programmes have a far greater reliance on hitting job targets, than fixing the skills gaps that the long-term unemployed have which hinders them gaining sustainable employment.
Beatty et al., (2011) states that “as the majority of these welfare to work programmes have a ‘one-size-fits-all, top-down’ solutions, whilst well intentions, only provided a few people into employment”. Beatty’s findings are backup up by Carter and Whitworth, (2017) who highlights the “payment-by-results” culture of welfare to work programmes.
This project for the H818 – Open Conference, is to look at how Virtual Learning Environments when used in conjunction with Blended Learning, along with taking identifiable hygiene-factors (using Hertzberg’s Two-Factor Theory) into account, can aid the long-term unemployed gain the skills that they possibly will need in this technological age, where the skills needs to be demonstrated by potential employees for potential employers has grown.
With more businesses using Information Communication Technologies, such as Computers, Mobile Devices and Social Media, the long-term unemployed need to have an understanding of these technologies and how to use them sufficiently to perform the jobs that they want to apply for.
Having worked in the welfare to work sector of training for many years’, the presenter has identified that training that is given to the long-term unemployed has been and still is, geared toward shortened down versions of Level 2 in Customer Service and Retail which have a Guided Learning Hours of 30 hours.
These training courses are class-based and use portfolio-based assessments to demonstrate that learning has taken place. It is doubtful that this way of teaching facilitates learning at its full potential. If we are to give people the possibility to be included in the sustainable job market, we should really look at how we can give the students the best possible opportunity to learn as many skills as possible.
Bloom et al., (2003) had found that many managers of the training companies providing the welfare to work programmes believe that a more “personal approach is a far more effective way of helping those in long-term unemployment than the one-size-fits-all approach”.
With the above to take into account, this presentation will look at how Virtual Learning Environments can increase the skills that the long-term unemployed can learn, whilst also be able to use Herzberg’s Two-Factor Theory to identify the Hygiene-factors (things that cause dissatisfaction for the learners) that the long-term unemployed have towards using Virtual Learning Environments.
With these Hygiene-Factors identified, we will see how using a Blended Learning methodology along with using Motivating-Factors to reduce the Hygiene-Factors, this will help plan a new curriculum delivery model to help aid the long-term unemployed to have far greater opportunities to learn new skills.
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Beatty, C., Fothergill, S., Gore, T. and Powell, R. (2011) ‘Tackling worklessness in Britain’s Weaker Local Economies,
Bloom, H.S., Hill, C.J., Riccio, J.A. (2003), ‘Linking Program Implementation and effectiveness: Lessons from a Pooled sample of Welfare-to-Work Experiments, Journal of policy analysis and Management, Vol. 22 No.4, 551-575 (2003)
Carter, E. and Whitworth, A. (2017) ‘Work Activation Regimes and Well-being of Unemployed People: Rhetoric, Risk and Reality of Quasi-Marketization in the UK Work Programme’, Social Policy and Administration. doi: 10.1111/spol.12206.
Interactive Infographic of Questionnaire Results as of 13th February 2018
21:25 on 13 February 2018