%0 Conference Proceedings
%T A Model for Prioritization and Prediction of Impact of Digital Literacy Training Programmes and Validation
%+ Indian Institute of Technology Delhi (IIT Delhi)
%A Joseph, Nimish
%A Kar, Arpan, Kumar
%A Ilavarasan, P., Vigneswara
%Z Part 3: Analytics for Smart Governance
%< avec comité de lecture
%( Lecture Notes in Computer Science
%B 16th Conference on e-Business, e-Services and e-Society (I3E)
%C Delhi, India
%Y Arpan Kumar Kar
%Y P. Vigneswara Ilavarasan
%Y M. P. Gupta
%Y Yogesh K. Dwivedi
%Y Matti Mäntymäki
%Y Marijn Janssen
%Y Antonis Simintiras
%Y Salah Al-Sharhan
%I Springer International Publishing
%3 Digital Nations – Smart Cities, Innovation, and Sustainability
%V LNCS-10595
%P 227-238
%8 2017-11-21
%D 2017
%R 10.1007/978-3-319-68557-1_21
%K Digital India
%K Digital literacy
%K National digital literacy mission
%K Knowledge
%K Comfort
%K Frequency
%K Training
%K Impact
%K Linear regression
%K AHP
%Z Computer Science [cs]
%Z Computer Science [cs]/Networking and Internet Architecture [cs.NI]Conference papers
%X The Government of India through its various programmes like Digital India aims to provide digital literacy to all its citizens. Towards this mission, National Digital Literacy Mission and Digital Saksharata Abhiyan conducted various training programmes throughout the country. The authors collected details of 5 lakh participants, who successfully completed the training programme and to learn the quality of the training and identify its impact 30,003 participants were interviewed based on a systematic sampling. This study based on the survey and interview identifies a model to predict and validate the impact of similar Digital Literacy training programmes in India. The various components identified in this study were then ranked based on the participant responses using the analytical hierarchy process. The various constructs identified for assessing the quality of training includes conduct, delivery and content, and perceived value. The impact of training was measured using knowledge gained, comfort level achieved and frequency of usage. To identify the impact of training a simple linear regression technique was also used.
%G English
%Z TC 6
%Z WG 6.1
%2 https://inria.hal.science/hal-01768498/document
%2 https://inria.hal.science/hal-01768498/file/978-3-319-68557-1_21_Chapter.pdf
%L hal-01768498
%U https://inria.hal.science/hal-01768498
%~ IFIP-LNCS
%~ IFIP
%~ IFIP-TC
%~ IFIP-WG
%~ IFIP-TC6
%~ IFIP-WG6-1
%~ IFIP-I3E
%~ IFIP-LNCS-10595