Usability and Instrucional Design in Emergency Remote Teaching with Moodle

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Abstract

Decisions involving the creation of classes in virtual learning environments are conditioned by different variables. This article analyzes the relationship between the implementation of resources and activities in the virtual learning system Moodle and the ease that professors have in using this technology. By using a quantitative approach, the System Usability Scale (LEWIS, 2018) and the observation of Federal University of Paraíba’s professors' virtual classrooms during the remote emergency teaching in 2020, it was possible to identify a considerable ease of use of the system, but low variety of resources and activities.

References

DA SILVA, Leo Victorino. Tecnologias Digitais de Informação e Comunicação na Educação: três perspectivas possíveis. Revista de Estudos Universitários-REU, v. 46, n. 1, p. 143-159, 2020.

FILATRO, Andrea. Design Instrucional contextualizado: educação e tecnologia. São Paulo: Senac. 2004

KLUYVER, Thomas et al. Jupyter development team. 2016. Jupyter Notebooks—a publishing format for reproducible computational workflows. https://eprints. soton. ac. uk/403913/.[Google Scholar], 2016.

LEWIS, J. R. The System Usability Scale: Past, Present, and Future. International Journal of Human-Computer Interaction, [s. l.], v. 34, n. 7, p. 577–590, 2018. Disponível em: <https://doi.org/10.1080/10447318.2018.1455307>

MARTINS, A. I. et al. European Portuguese Validation of the System Usability Scale (SUS). Procedia Computer Science, [s. l.], v. 67, n. Dsai, p. 293–300, 2015. Disponível em: <http://dx.doi.org/10.1016/j.procs.2015.09.273>

MCKINNEY, Wes et al. Pandas: a foundational Python library for data analysis and statistics. Python for High Performance and Scientific Computing, v. 14, n. 9, 2011.

MOREIRA, J. António; HENRIQUES, Susana; BARROS, Daniela Melaré Vieira. Transitando de um ensino remoto emergencial para uma educação digital em rede, em tempos de pandemia. Dialogia, p. 351-364, 2020.

OLIPHANT, Travis E. A guide to NumPy. USA: Trelgol Publishing, 2006.

PLOTLY TECHNOLOGIES INC. (Montréal). Collaborative data science Publisher: plotly technologies inc. Plotly Technologies Inc. 2015. Disponível em: https://plot.ly. Acesso em: 31 mar. 2021.

REISER, Robert A. A History of Instructional Design and Technology. ETR&D, Vol. 49, No. 2, p. 57–67, 2001.

TOSI, Sandro. Matplotlib for Python developers. Packt Publishing Ltd, 2009.

TUKEY, John W. et al. Exploratory data analysis. 1977.

VALLAT, Raphael. Pingouin: statistics in Python. Journal of Open Source Software, v. 3, n. 31, p. 1026, 2018.

VAN ROSSUM, Guido; DRAKE, Fred L. Introduction To Python 3: Python Documentation Manual Part 1. CreateSpace, 2009.

WASKOM, M. Seaborn: Statistical Data Visualization—Seaborn 0.9. 0 Documentation. Sphinx 1.7, v. 4, 2018.

Published

2022-03-20

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Article