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content/blog/entries/2023-04-26-umsi-how-many-mona-lisas/contents.lr

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### Diagram #1:
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![img](diagram_01.png)
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![Diagram #1: Percentage of Items per License Type](diagram_01.png)
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Diagram #1 shows the distribution of items taken from OER Commons by license
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type. It is clear that the CC-BY license type is the most popular, with 43% of
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### Diagram #2:
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![img](diagram_02.png)
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![Diagram #2: Number of Items by Month since Dec 2015](diagram_02.png)
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Diagram #2 shows when items have been added to the OER Commons API. There is
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little activity from December 2015, up to the beginning of 2023. However, close
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### Diagram #3:
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![img](diagram_03.png)
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![Diagram #3: Percentage of Items by Language](diagram_03.png)
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Diagram #3 shows the percentage of items by language. English is the most used
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language, with about 86% of the items being in English. The other languages
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### Diagram #4:
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![img](diagram_04.png)
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![Diagram #4: Percentage of Items in English per License Type](diagram_04.png)
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Since English is clearly the most popular language, we decided to see the
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license distribution for items that are in English. Diagram #4 shows a similar
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### Diagram #5:
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![img](diagram_05.png)
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![Diagram #5: Percentage of Items in French per License Type](diagram_05.png)
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We continued to look at the distribution of licenses by each language.
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Diagram #5 shows that for the items in French, CC-BY license is the most
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### Diagram #6:
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![img](diagram_06.png)
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![Diagram #6: License Type Breakdown by Primary User](diagram_06.png)
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Diagram #6 shows the distribution of items on OER commons by primary user and
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broken down by license type. The platform predominantly contains items designed
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### Diagram #7:
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![img](diagram_07.png)
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![Diagram #7: Percentage of Items Used by Teachers per License Type](diagram_07.png)
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### Diagram #8:
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![img](diagram_08.png)
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![Diagram #8: Percentage of Items Used by Students per License Type](diagram_08.png)
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### Diagram #9:
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![img](diagram_09.png)
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![Diagram #9: Subject Area by License](diagram_09.png)
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Another aspect analyzed was inspecting the subject areas and the licenses that
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they hold as shown in Diagram #9. Some preliminary data cleaning had to be
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### Diagram #10:
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![img](diagram_10.png)
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![Diagram #10: Material Type Breakdown by Education Level](diagram_10.png)
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Finally, the team analyzed the material types of the items and sorted it by
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education level that the items were created for. Again, some data cleaning was

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