Visualization Research: Scoping review on data visualization courses
3rd Valencia International Biennial of Research in Architecture. Changing priorities
2022
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Example: if you select the 1-year option for an article published in 2019 and a metric category shows 90%, that means that the article or review is performing better than 90% of the other articles/reviews published in that journal in 2019. If you select the 3-year option for the same article published in 2019 and the metric category shows 90%, that means that the article or review is performing better than 90% of the other articles/reviews published in that journal in 2019, 2018 and 2017.
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Example: if you select the 1-year option for an article published in 2019 and a metric category shows 90%, that means that the article or review is performing better than 90% of the other articles/reviews published in that journal in 2019. If you select the 3-year option for the same article published in 2019 and the metric category shows 90%, that means that the article or review is performing better than 90% of the other articles/reviews published in that journal in 2019, 2018 and 2017.
Citation Benchmarking is provided by Scopus and SciVal and is different from the metrics context provided by PlumX Metrics.
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- Usage137
- Downloads98
- Abstract Views39
Conference Paper Description
Understanding data visualization as one of the foundational skills of the 21st century, this research aimed to define up-to-date guidelines to effectively teach data visualization courses and–from there–developed the first version of a new data visualization course. To do so, it faced the following questions: What is the current role of data visualization in higher education? What have been the main trends in data visualization courses in higher education? What methodologies have been used to teach data visualization courses? What difficulties have been identified in data visualization courses? What recommendations have been offered by previous professors that have taught this kind of courses? Considering this broad set of questions, the research was developed as a scoping review that served to collect hundreds of publications from where 22 peer-reviewed articles published between 2008 and 2021 were finally selected and analyzed. Among the most important results, the research found that data visualization interest in higher education has been growing exponentially and data visualization courses prioritize practical exercises over theoretical content. Some of the most common recommendations synthetized through the review suggested to select topics that the students should find interesting to promote their engagement. Also, several authors recommended to start the visualization process as soon as possible and spend the least possible time on learning tools. Finally, the results of this review should be useful to support and promote new data visualization courses while they were already used to create the first iteration of a graduate and upper-level undergraduate professional elective course on data visualization under the title Visualization Research. The review and assessment of this course will be the next step of this research process.
Bibliographic Details
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