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With the increasing amount of lectures that are available in production, it can happen that lectures which make use of a lot of features of MaMpf (like tagging, structuring with chapters and sections, tables of contents and references for videos, quizzes...) are overlooked in a sea of lectures that do not. One way to improve the situation would be to calculate some kind of score that measures the above things and award badges to lectures depending on this and enable users to sort accordingly.
The text was updated successfully, but these errors were encountered:
Could you maybe make a proposal with the following content?
What priority does this feature have to you?
For what "level" of inheritance should this score be calculated? For lectures? Or even individual media? (My understanding is that the answer is "lecture")
Detailed and complete list of all features that should contribute to the score and how a score for each feature is calculated, i.e. define a metric for each, e.g. "tagging: number of tags used throughout the whole lecture" (but that wouldn't be a good metric in my opinion). Or: table of content -> is this is binary choice, you either have it or not, or more fine-grained? etc.
Weighing factors for the features. How do they contribute to the total score? E.g. you might find it more important that lectures have a table of content than the fact that they have chapters...
How do we communicate this transparently to users and to editors? Do we break down how the score was calculated in the frontend for them? Do we only show badges for generic users indicating some kind of "excellence" (and only say something like "makes use of a lot of MaMpf features, e.g. table of content, quizzes etc.")? And only editors get a detailed view in the backend? Or something completely different?
Should this new ranking become the default sorting mechanism in the frontend?
With the increasing amount of lectures that are available in production, it can happen that lectures which make use of a lot of features of MaMpf (like tagging, structuring with chapters and sections, tables of contents and references for videos, quizzes...) are overlooked in a sea of lectures that do not. One way to improve the situation would be to calculate some kind of score that measures the above things and award badges to lectures depending on this and enable users to sort accordingly.
The text was updated successfully, but these errors were encountered: