2026-06-21T03:41:55Zhttps://riubu.ubu.es/oai/requestoai:riubu.ubu.es:10259/62492022-12-01T11:25:29Zcom_10259_4219com_10259_5086com_10259_2604com_10259_5841col_10259_4220col_10259_5842
Repositorio Institucional de la Universidad de Burgos
author
Sáiz Manzanares, María Consuelo
author
Marticorena Sánchez, Raúl
author
Ochoa Orihuel, Javier
2021-11-29T08:58:19Z
2021-11-29T08:58:19Z
2020-08
1660-4601
http://hdl.handle.net/10259/6249
10.3390/ijerph17155618
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.
eng
Atribución 4.0 Internacional
Advanced learning technologies
Intelligent personal assistant
Blended learning
COVID-19
Effectiveness of Using Voice Assistants in Learning: A Study at the Time of COVID-19
info:eu-repo/semantics/article
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URL
https://riubu.ubu.es/bitstream/10259/6249/1/Saiz-ijerph_2020-3.pdf
File
MD5
c8c76d0f843cba9564066e7b582bb22c
2153790
application/pdf
Saiz-ijerph_2020-3.pdf