Various tools are needed for teaching computer science on the subject of data. The usual tools used in the classroom, such as databases and spreadsheet programs, may illustrate some aspects of the subject, but are not sufficient for more comprehensive data analysis, prediction based on data, or data protection and security. For this reason, the research project has developed two tools that can be used to illustrate other aspects of the topic:
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Snap!Twitter 2.0
Snap!Twitter was an extension for the block-based programming language Snap!. This extension offered students, as well as other interested parties, an easy way to enter data stream analysis using the example of data that Twitter made available to the public. The analysis could take place with live data from Twitter. Since version 2 Snap!Twitter was completely usable in the browser. Snap!Twitter is not available anymore since Twitter does not offer a suitable API access for free anymore and as prices are too high for this purpose. -
Snap!DSS
Snap!DSS extends the block-based programming language Snap!. with the ability for more comprehensive data stream analysis. Snap!DSS goes further than SnapTwitter and allows not only the analysis of this single data source, but can also be flexibly used and extended for processing various data sources. For example, a combination with the acquisition of sensor data by means of simple microcontroller boards is a good option. In addition to these in-house developments, other tools can of course also be used in data-oriented computer science lessons. The following list, which will be further supplemented in the future, should give some suggestions: -
Orange
The Orange data analysis tool was developed at the University of Ljubljana for professional data analysis. However, because it comes from bioinformatics and is designed for non-computer scientists, it is not too complex for school lessons, thanks to its data flow-oriented description of the analysis and the fact that it does not require any programming by the users. Examples for the use in teaching can be found in the teaching concept “Data Mining in Computer Science Teaching” (cf. teaching material).