Suggestion: Uniformity of Distribution of New Vocabulary

Hello. I’ve been using Lingq with small pauses for almost a year now and I find it super. I noticed that one of the most important things is the choice of the right content and to do so I’ve been using the percentage of unknown vocabulary; however, I often found this indicator to be a bit misleading. You see, I noticed that my studying is at its peak at times when new words appear in sentences consisting almost solely of familiar vocabulary rather than sentences all highlighted in yellow or blue. The problem is that even if new material is indicated to consist of let’s say 10% of new words, it often happens that the majority of this vocabulary is contained within a small portion of sentences leaving the majority of the text with almost no new vocabulary at all. Not only is reading of such sentences just as ineffective as going through more difficult materials, but it also makes the remaining sentences too easy. This can be both frustrating and boring at times. I’m not implying that reading of such texts is useless; I just think we could be more effective connecting users with the suitable content, as I believe texts with more even distribution of vocabulary will enhance the learning process.

My suggestion is to add another indicator to the text description about uniformity of distribution of new vocabulary. This could be a simple graph diagram displaying which parts of the text contain what proportion of unknown words. I believe it would dramatically help users filter out the more ineffective material, or at least postpone it until the momentum is right for users to get the most out of their reading, and for the time being focus on the more effective materials. Let me know what you think.

Greetings from Slovakia!