Published April 8, 2022 | Version 1.0.0
Dataset Open

Biological data science courses at UMONS, Belgium: student's activity for 2020-2021

  • 1. Numerical Ecology Department, Complexys and InforTech Institutes, University of Mons

Contributors

Project member:

  • 1. Numerical Ecology Department, Complexys and InforTech Institutes, University of Mons

Description

Progression of the students in the different exercises of the biological data science courses at the University of Mons, Belgium for the academic year 2020-2021.

Activity of the students was recorded to monitor their individual progression in asynchronous exercises. The courses were taught in flipped classroom by Philippe Grosjean (philippe.grosjean@umons.ac.be) and Guyliann Engels (guyliann.engels@umons.ac.be) the University of Mons. These authors designed almost all the teaching material, the exercises, and the related software. The courses were also taught at the Campus Charleroi by Raphaël Conotte (raphael.conotte@umons.ac.be) that also contributed to a part of the learnr exercises and of the inline course.

How to use these data?

The README file provides detailed information on the purpose, collection and management of the data.  The data are presented in tabular format in CSV files. Metadata in the `datapackage.json` document the different tables and their fields. It is in the Frictionless data format (https://frictionlessdata.io). You can get a view of a part of these metadata by uploading the file `datapackage.json` into the inline data package creator at https://create.frictionlessdata.io. There is a large set of libraries and tools for different programming languages available at https://frictionlessdata.io/tooling/libraries/. Otherwise, any CSV library should import the data in your favourite software. Please, note that encoding is UTF8. For R, the {learnitdown} package provides specific functions to import these data and/or convert them in a SQLite database (https://www.sciviews.org/learnitdown/).

For any question, send an email at sdd@sciviews.org.

Files

assessments.csv

Files (93.2 MB)

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