Abstract
While there is large body of work examining efficacy of Virtual Labs in engineering education, studies to date have lacked modeling Blended Labs (BL) – mix of Virtual Labs (VL) and Physical Labs (PL) for science experimentation at the university engineering level. Using Rogers theory of perceived attributes, this paper provides a research framework that identifies the attributes for BL adoption in a social group comprising of (N=246) potential adopter undergraduate engineering students. Using Bass model the study also accounts for the interinfluence of related group of potential adopter faculties who are likely to exert positive influence on students. The results revealed that acceptance of BL as an innovation and its learning outcomes are strongly associated with innovation attributes like Relative Advantage, Compatibility, Ease of Use, Department and Faculty support. Learning outcomes are very positive under BL when compared to PL, though within BL, ordering of PL and VL was not significant. For certain innovation attributes gender differences were significant. Overall students expressed much more positive attitude to adopt BL model for learning than using only PL.
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Acknowledgements
This project derives direction and ideas from the Chancellor of Amrita University, Sri Mata Amritanandamayi Devi. This work is in part funded by Amrita University and National Mission on Education through ICT (NME ICT), Govt. of. India. The authors would like to acknowledge the contributions of faculty and staff at Amrita University whose feedback and guidance was invaluable.
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© 2014 Institute for Computer Sciences, Social Informatics and Telecommunications Engineering
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Raman, R., Achuthan, K., Nedungadi, P., Ramesh, M. (2014). Modeling Diffusion of Blended Labs for Science Experiments Among Undergraduate Engineering Students. In: Bissyandé, T., van Stam, G. (eds) e-Infrastructure and e-Services for Developing Countries. AFRICOMM 2013. Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering, vol 135. Springer, Cham. https://doi.org/10.1007/978-3-319-08368-1_28
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DOI: https://doi.org/10.1007/978-3-319-08368-1_28
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