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    Por favor, use este identificador para citar o enlazar este ítem: http://hdl.handle.net/10259/6250

    Título
    Moodle LMS Integration with Amazon Alexa: A Practical Experience
    Autor
    Ochoa Orihuel, Javier
    Marticorena Sánchez, RaúlAutoridad UBU
    Sáiz Manzanares, María ConsueloAutoridad UBU
    Publicado en
    Applied Sciences. 2020, V. 10, n. 19, 6859
    Editorial
    MDPI
    Fecha de publicación
    2020-09
    ISSN
    2076-3417
    DOI
    10.3390/app10196859
    Résumé
    The frequency of interaction between teachers and students through Learning Management Systems (LMSs) is continuously rising. However, recent studies highlight the challenges presented in current LMSs to meet the specific needs of the student, regarding usability and learnability. With the motivation to support the research of effectiveness when using a Voice User Interface (VUI) for education, this paper presents the work done (RQ1) to build the basic architecture for an Alexa skill for educational purposes, including its integration with Moodle, and (RQ2) to establish whether Moodle currently provides the necessary tools for voice-content creation for develop voice-first applications, aiming to provide new scientific insight to help researchers on future works of similar characteristics. As a result of this work, we provide guidelines for the architecture of an Alexa skill application integrated with Moodle through safe protocols, such as Alexa’s Account Linking Web Service, while our findings ratify the need for additional tooling within Moodle platform for voice-content creation in order to create an appealing voice experience, with the capabilities to process Moodle data structures and produce sensible sentences that can be understood by users when spoken by a voice device.
    Palabras clave
    Moodle LMS
    Amazon Alexa
    Education
    e-learning
    Intelligent personal assistant
    Voice-content
    Usability
    Materia
    Informática
    Computer science
    Enseñanza
    Teaching
    URI
    http://hdl.handle.net/10259/6250
    Versión del editor
    https://doi.org/10.3390/app10196859
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