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5

I'd recommend: to have limited number of complexity levels. Because having a lot of those create cognitive barrier. As complexity is not absolute category, people will interpret it subjectively and think a lot before making decision. It's better to use 3 or 4 levels to name levels in appropriate way. Labels allow to refer to levels in clear way and to ...


4

I agree with Charles; the same chart but with the axes reversed makes more sense to me. I tend to think of time in terms of timelines, which your chart just isn't doing for me right now. I also think you want some way to indicate continuities within broken time chunks, so it's clear that the kid didn't wake up briefly at midnight. download bmml source ...


3

Another alternative - one that gets rid of the discontinuity at midnight (or 10am) - would be a spiral visualization, with one day per circuit. Here's a picture of a spiral visualisation from an earlier UX answer of mine: You could use 24 hours per circuit, and show history over 7 or 10 days easily. The same time of day always shows at the same angle, ...


3

Since you have two lists and there is no information on which one is primary, I think that diff like this will work good: Pros: It shows both lists unmodified It shows resulting list It highlights items which are added It shows common part of the lists Cons: Three lists instead of one Colors could be tuned up to your needs (for example, you may ...


2

Google deprecated the whole Image Charts API, which allowed for the rendering of sparklines and many other visualizations. It was not specifically aimed at removing sparklines alone. The API was part of a larger group of "old" APIs that were deprecated at the same time. Based on this context, it seems to be an engineering decision.


2

You're focusing heavily on the word "accuracy", but you're discussing the topic of skills. In an educational setting, the word "proficiency" better represents the goals of teaching, and teachers often measure proficiency by reporting the students' accuracy on tests. I would try to use the more appropriate word, as it will help reduce confusion. Also, ...


2

What you describe seems a diff-like application. You could use a similar view, two columns and the matching items hightlighted. As for the similarity algorithm, if ListA is {A} and ListB is {A,B} lists would be 50% similar, then it could be: coincidences / (ListA length + ListB length + conincidences) * 100


2

You should just use some descriptive words like "Simple," "Intermediate," and "Complex." A number of stars is just that: A number. And if you use a number, than you have to explain the unit of measurement. Why do that when natural language offers words specifically meant for this situation? For the best implementation, I would give each word a tooltip that ...


1

Word clouds are completely useless. Two patterns here (making a bunch of assumptions about your needs) might be: Perform semantic analysis on the answers to strip away filler words (and possibly group together phrases), and then display words by frequency in a simple bar chart. Bar charts are one of the easiest-to-understand visualizations of categorical ...


1

The classical way is a Venn diagram: (Source: Wikipedia) For quantification of set similarity/dissimilarity, you can look at Sørensen–Dice coefficient or Jaccard index. Their parameterization is the Tversky index.


1

Well, the "best" way will depend on your needs and the overall style of the dashboard (what are users used to see - are there more similar visualizations?), but generally speaking, you can: Flip the semantics, i.e. worse rankings will result in a smaller slice. Simply use a meter bar instead of a donut.


1

For user trends, the stacked graph seems to be appropriate, because your different data share the same unit, and the sum of the values is a meaningful value (total number of users). It makes it slightly easier to express both changes in percentage and total number, although at the cost of direct comparison. However, some quesitons remain - see my comment.


1

Well, I was struggling with this problem. I don't recommend to use log scale, first not all users will understand this scale, second one, if you have values that are close the difference between them won't be noticeable on the graph. I recommend two solutions: break graphs: but we need to remember to change the scale, scale must be adjusted not to the ...



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