In Vocational Education and Training (VET) institutions, teachers face important difficulties in the teaching process due to a
wide variety of student’s special educational needs as well as student’s lack of: the adequate level of basic competence,
motivation, concentration, attention, confidence and background knowledge, among other aspects. Regarding the attention to
these aspects, many studies have reported positive impact of Augmented Reality (AR) applications in primary, secondary and
higher education in terms of student’s motivation, learning gains, collaboration, interaction, learning attitudes and enjoyment,
among others. However, very little has been done in terms of AR applications in VET as well as their impact on wide variety of
student’s special educational needs such as learning difficulties. This paper introduces a marker-based mobile AR application
named Paint-cAR for supporting the learning process of repairing paint on a car in the context of a vocational education
programme of car’s maintenance. The application was developed using a methodology for developing mobile AR applications
for educational purposes from a collaborative creation process (Co-Creation) and based on the Universal Design for Learning
(UDL). A cross-sectional evaluation study was conducted to validate the Paint-cAR application in a real scenarioThis work is supported in part by the Spanish Science and Education Ministry in the Open Co-Creation Project (TIN2014-53082-R). Jorge Bacca, Silvia Baldiris and Ramon Fabregat belong to the BCDS group (ref. GRCT40) which is part of the DURSI consolidated research group COMUNICACIONS I SISTEMES INTELLIGENTS (CSI) (ref. SGR-1469). Jorge Bacca would like to thank the financial support for the Grant (FPI-MICCIN) provided by the Spanish Ministry of Economy and Competitiveness (BES-2012-059846). Authors would like to thank to teachers Joan Clopés (Institut Montilivi) and Narcis Vidal (Institut Narcis Monturiol) that participated in the design of PaintcAR application. The authors also acknowledge the support of NSER
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