Application of Voice Personal Assistants in the Context of Smart University

Los asistentes personales de voz basados en técnicas avanzadas de comprensión del lenguaje natural se muestran como un recurso prometedor frente al reto del diseño de plataformas virtuales de aprendizaje. Específicamente, estos recursos pueden servir de apoyo para la mejora del proceso de enseñanza-aprendizaje. El objetivo principal de este trabajo ha sido el de estudiar los desafíos actuales para la utilización de este tipo de asistentes en el ámbito de las universidades inteligentes. Asimismo, se ha analizado cómo esta nueva tecnología puede ayudar a los estudiantes en su proceso de aprendizaje y grado de satisfacción. Los resultados de este trabajo se presentan en tres artículos de investigación publicados en revistas científicas indexadas en Web of Science. También se aporta un Registro de la Propiedad Intelectual registrado en el Ministerio de Cultura de España, en la categoría de programa de ordenador, cuyos derechos fueron cedidos a la Universidad de Burgos.Personal voice assistants based on advanced natural language comprehension techniques are shown as a promising resource with regard to the challenge of designing virtual learning platforms. In particular, these resources can support the improvement of the teaching-learning process. The main objective of this work has been to study the current challenges for the use of this type of assistant in the field of smart universities. Likewise, it has been analyzed how this innovative technology can help students in their learning process and their degree of satisfaction. The results of this work are presented in three research articles published in scientific journals indexed on the Web of Science. Also, an Intellectual Property Registry registered with the Ministry of Culture of Spain in the category of computer programs is provided, whose rights were transferred to the University of Burgos

Effectiveness of Using Voice Assistants in Learning: A Study at the Time of COVID-19

The use of advanced learning technologies in a learning management system (LMS) can greatly assist learning processes, especially when used in university environments, as they promote the development of Self-Regulated learning, which increases academic performance and student satisfaction towards personal learning. One of the most innovative resources that an LMS may have is an Intelligent Personal Assistant (IPA). We worked with a sample of 109 third-grade students following Health Sciences degrees. The aims were: (1) to verify whether there will be significant differences in student access to the LMS, depending on use versus non-use of an IPA. (2) To verify whether there will be significant differences in student learning outcomes depending on use versus non-use of an IPA. (3) To verify whether there will be significant differences for student satisfaction with teaching during the COVID-19 pandemic, depending on use versus non-use of an IPA. (4) To analyze student perceptions of the usefulness of an IPA in the LMS. We found greater functionality in access to the LMS and satisfaction with teaching, especially during the health crisis, in the group of students who had used an IPA. However, both the expansion of available information and the usability of the features embedded in an IPA are still challenging issues.Consejería de Educación de la Junta de Castilla y León (Spain) (Department of Education of the Junta de Castilla y León), Grant number BU032G19, and grants from the University of Burgos for the dissemination and the improvement of teaching innovation experiences of the Vice-Rectorate of Teaching and Research Staff, the Vice-Rectorate for Research and Knowledge Transfer, 2020, and the Departamento de Ciencias de la Salud the University of Burgos (Spain). And the support for the dissemination of research results for teachers and doctorands of the Vice-Rectorate for Research and Knowledge Transfer, 2020

Using Advanced Learning Technologies with University Students: An Analysis with Machine Learning Techniques

The use of advanced learning technologies (ALT) techniques in learning management systems (LMS) allows teachers to enhance self-regulated learning and to carry out the personalized monitoring of their students throughout the teaching–learning process. However, the application of educational data mining (EDM) techniques, such as supervised and unsupervised machine learning, is required to interpret the results of the tracking logs in LMS. The objectives of this work were (1) to determine which of the ALT resources would be the best predictor and the best classifier of learning outcomes, behaviours in LMS, and student satisfaction with teaching; (2) to determine whether the groupings found in the clusters coincide with the students’ group of origin. We worked with a sample of third-year students completing Health Sciences degrees. The results indicate that the combination of ALT resources used predict 31% of learning outcomes, behaviours in the LMS, and student satisfaction. In addition, student access to automatic feedback was the best classifier. Finally, the degree of relationship between the source group and the found cluster was medium (C = 0.61). It is necessary to include ALT resources and the greater automation of EDM techniques in the LMS to facilitate their use by teachers.This research was funded by the MINISTERIO DE CIENCIA E INNOVACIÓN, grant number PID2020-117111RB-I00

Moodle LMS Integration with Amazon Alexa: A Practical Experience

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.Vice-Rectorate of Teaching and Research Staff, the Vice-Rectorate for Research and Knowledge Transfer, 2020, at the University of Burgos (Spain)