Emerging technology and teaching methodologies in virtual learning environments
As the first part of this research, the theories of constructivism and connectivism were explored, focusing on the most prominent authors in the field. The study highlights key concepts and the emergence of emerging technologies (ICTs). The objective of the research is to analyze emerging technologies and the teaching methodologies used by instructors in the Bachelor's Degree in Information Systems Engineering, which is delivered virtually to first-, second-, third-, and fourth-year students at the Faculty of Informatics Mazatlán. A sample of 30 faculty members from the institution was selected for the initial phase. A hybrid methodology was employed, incorporating a questionnaire consisting of 10 Likert-scale items (ranging from Strongly Disagree to Strongly Agree) and four open-ended questions to collect qualitative data. The results indicate that the most commonly used emerging technologies are the Internet of Things (96.7%) and collaborative platforms (93.3%). This suggests that instructors primarily use these technologies for assignments and extracurricular activities, often without providing feedback. Regarding preferred teaching methodologies, the findings reveal that 25% of faculty members favor expository methods, teamwork, and summative assessment. It is recommended to conduct further research on faculty training for the effective implementation of teaching methodologies tailored to each type of emerging technology.
Authors
- Lucio Guadalupe Quirino Rodríguez (ORCID: https://orcid.org/0009-0009-5128-1870)
- Andrés Ultreras-Rodríguez (ORCID: https://orcid.org/0000-0003-0621-9508)
- Héctor Luis López López (ORCID: https://orcid.org/0000-0002-9401-9807)
- Victor Manuel Martínez García (ORCID: https://orcid.org/0009-0008-2647-9386)
Institutions
- Universidad Autónoma de Sinaloa (MX)
Publication Details
- Journal
- Metaverse Basic and Applied Research
- Published
- 2024-12-31
- DOI
- https://doi.org/10.56294/mr2024.91
- Primary Topic
- Big Data and Business Intelligence
- Type
- article
- Field-Weighted Citation Impact
- 0.00