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Blended learning system for efficient professional driving

, ADN Mobile Solutions, Spain ; , , Informatics Department, Spain ; , Electrical and Computer Engineering Department, Spain ; , ADN Mobile Solutions, Spain ; , Business Administration Department, Spain ; , , ADN Mobile Solutions, Spain

Computers & Education Volume 78, Number 1, ISSN 0360-1315 Publisher: Elsevier Ltd


One of the most important expenses in bus and truck transport companies is the cost of fuel. A small increase in the price of petrol can have a very negative effect on the companies' balance sheet. Apart from that, road transport companies are targeted due to their influence on air pollution. All of this has made the reduction in fuel consumption the most important priority for this type of companies. One of the cheapest measures to reduce fuel burning is efficient driving. According to various studies, more efficient driving could reduce fuel consumption by more than 5%. This article presents a blended learning method which makes use of an on-board tutoring system, an e-learning platform and traditional courses to guide professional drivers to more efficient driving. Through visual and acoustic recommendations, the tutoring system helps drivers achieve more efficient driving in real-time. The on-board system is complemented with a Web portal where drivers can check their driving and receive recommendations for further improvement and a set of traditional seminars imparted by experts in the area. To evaluate the performance of the whole learning system, the driving of 34 professional drivers of the Urban Bus Company (EMTUSA) in the City of Gijón (Spain) has been monitored and analyzed over a period of 12 months. The results of the study showed an improvement in driving efficiency and a reduction in fuel consumption of almost 7% compared to the previous year.


Rionda, A., Pañeda, X.G., García, R., Díaz, G., Martínez, D., Mitre, M., Arbesú, D. & Marín, I. (2014). Blended learning system for efficient professional driving. Computers & Education, 78(1), 124-139. Elsevier Ltd. Retrieved May 29, 2023 from .

This record was imported from Computers & Education on January 29, 2019. Computers & Education is a publication of Elsevier.

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