About this paper

Appears in:
Pages: 6205-6211
Publication year: 2020
ISBN: 978-84-09-24232-0
ISSN: 2340-1095
doi: 10.21125/iceri.2020.1333

Conference name: 13th annual International Conference of Education, Research and Innovation
Dates: 9-11 November, 2020
Location: Online Conference

USING COVID19 OUTBREAK DATA TO ENGAGE STUDENTS IN THE LEARNING PROCESS

A. Fernández-Morales, M.C. Mayorga-Toledano

Universidad de Málaga (SPAIN)
The complex situation that higher education students faced after the COVID19 outbreak has become a hard challenge for lecturers to keep students engaged in the learning process. Particularly, in the case of the MSc in Actuarial Science at the University of Málaga, our students, as well as many other students in graduate and post-graduate programs in this University, experienced a complete change from a face-to-face to a remote learning mode in a few weeks. At the beginning of the second semester of the academic year 2019-2020, all the courses at the University of Málaga switched to a completely virtual mode as a consequence of the lockdown. In addition, some courses, like the one studied in this paper -Stochastic Processes in the MSc in Actuarial Science- usually demand an extra effort to the lecturers to engage students in the learning process of abstract and complex analytical techniques.

To overcome these two hurdles, with the aim of improving the involvement of our students in the learning process of this course, we included in the study program an individual project, based on COVID19 outbreak data, to be carried out by our students.

Each student was required to design and estimate a discrete time Markov chain with at least three states that describes the evolution of the COVID19 outbreak in Spain during a week. They were provided with a minimum pack of real time data from official sources, but were allowed to use any other relevant information. A second part of the project consisted in performing a prediction for a month of the pandemic in Spain and to critically assess their own estimated model and prediction.

The results of this project have been very positive. By means of a survey conducted at the end of the semester, we found:
(i) that our students found the chosen topic of the project a key element to increase their motivation,
(ii) that they learn more using this kind of data,
(iii) that it helped them to achieve a more complete depiction of the COVID19 phenomenon in Spain.
@InProceedings{FERNANDEZMORALES2020USI,
author = {Fern{\'{a}}ndez-Morales, A. and Mayorga-Toledano, M.C.},
title = {USING COVID19 OUTBREAK DATA TO ENGAGE STUDENTS IN THE LEARNING PROCESS},
series = {13th annual International Conference of Education, Research and Innovation},
booktitle = {ICERI2020 Proceedings},
isbn = {978-84-09-24232-0},
issn = {2340-1095},
doi = {10.21125/iceri.2020.1333},
url = {http://dx.doi.org/10.21125/iceri.2020.1333},
publisher = {IATED},
location = {Online Conference},
month = {9-11 November, 2020},
year = {2020},
pages = {6205-6211}}
TY - CONF
AU - A. Fernández-Morales AU - M.C. Mayorga-Toledano
TI - USING COVID19 OUTBREAK DATA TO ENGAGE STUDENTS IN THE LEARNING PROCESS
SN - 978-84-09-24232-0/2340-1095
DO - 10.21125/iceri.2020.1333
PY - 2020
Y1 - 9-11 November, 2020
CI - Online Conference
JO - 13th annual International Conference of Education, Research and Innovation
JA - ICERI2020 Proceedings
SP - 6205
EP - 6211
ER -
A. Fernández-Morales, M.C. Mayorga-Toledano (2020) USING COVID19 OUTBREAK DATA TO ENGAGE STUDENTS IN THE LEARNING PROCESS, ICERI2020 Proceedings, pp. 6205-6211.
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