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JavaRush Students Big Data

Published in the Random EN group
The source of data is information on the number of JavaRush students who have reached a certain level (as of 02/01/2022), published in the article “ Interesting Figures ”. In this article, we will “add color” to the dry numbers published in the article above, and so to speak, we will visually show on graphs the “trend” of changes in the number of students when completing levels of the JavaRush training course. First, let's look at the graph to see the change in the number of students who have reached a certain level. JavaRush Students Big Data - 1 From this line chart, we have generally noticed that the number of students is systematically decreasing as they progress through new levels. It is also worth noting that the greatest decrease in the number of students who have “overstepped” a certain level occurs at the very first levels. Since to analyze the statistics of student activity in the JavaRush quest, data current as of 01/01/2022 was taken , then in the future, the total number of students will increase, and therefore, when writing this article, I would like to identify patterns that will not change over time. Therefore, in the following line charts we will look at the change in the number of JavaRush students, expressed as a percentage in relation to the total number of users who “got” to level 0. And in fact, although over time the number of users will grow, but the stereotypes of people’s thinking and behavior (that is, the patterns of people’s psychotypes) will not change, and therefore in the “percentage ratio” there will most likely not be a sharp change. JavaRush Students Big Data - 2 For the purity of the experiment, we want to emphasize that we placed the statistics for levels 21-30 in a line chart called “% of students who passed Multithreading”, and the statistics for levels 31-41 in the chart “% of students who passed Collections”. Just like on the Quest Map the quests “ Java Multithreading ” and “ Java Collections”" are placed in parallel, then, as a result, the data from the above two tables can be confused with each other - that is, the statistics on "Collections" are indicated on the "Multithreading" diagram and vice versa. But in fairness, let's say that for statistical assessment this is ultimately not so important, anyway, if you completed these two quests, then you reached level 41, and if you stopped somewhere, then the “point” stopped. In the five above diagrams, we are interested in two things: 1) the angle of inclination of the curve (the greater, the more students "stopped" at a certain level). 2) readings on the "Y" axis, that is, the percentage of the total number of all students who "passed" a certain level. What can we say: a) at the first three levels Zero 0-2 at each level, half of the students “stopped.” b) from levels 4 to 10, while “the problems were still easy,” the number of students decreased “moderately.” c) at levels 11-40, the decrease in students partially increased (as can be seen from the slope of the curve at these line charts, which [the curved blue line on the chart] is a little more "downward sloping" than say the curved blue line on the Zero 3-10 chart. d) only 2 out of 10 users who started taking the quest went to the “paid” JavaRush courses. e) only 3% of the original number of “interested” completed the Zero quest. e) only every third person who started completing this [that is, Core or Multithreading] quest reached the end of the Core, Multithreading quests. g) the last quest “before the internship” (that is, Collections) was completed only by every 9 of those who initially started completing the Collections quest. The reason for this is that one of the conditions for enrollment in an internship is reaching level 35 and above. On the graph we see that after reaching level 35, many students did not “learn the theory further”, but most likely went for an internship in the hope of subsequently successfully completing it and “continuing to improve their knowledge” in the future as a Java developer. Next we will have the most interesting diagram (already a bar diagram). On the next “screen” we will see the number of students who “did not pass” a certain level. These data are interesting to us precisely because the basis for calculating the values ​​is the rule that if, for example, 100 students reached level n, and 90 students “reached” the next level n +1, then 10% “stopped” at level n from students who initially reached this level. That is, we took the number of students who reached this level as 100%. New level - the number of students who reached this “new” level was taken as 100%. Visually, this can be compared to the fact that “say, 10 people entered the room,” and “only, say, 9 of them found the door to the exit to the next room, and at the same time, 1 of the 10 who initially entered the room remained in the room.” JavaRush Students Big Data - 3 Brief conclusions from the information indicated in the diagram above: a) as stated earlier, at each of the levels 0-2, half of the students “left”. b) on average, about 10% of the students initially “enrolled” at this level stopped at one particular level. c) “little things are not important, little things decide everything”: at the first level of the new quest (11 Level Java Core, 21 level Java Multithreading, 31 Level Java Collections, the number of “dropped out” students was 1.5 - 2 times higher than the average “dropout rate for level" at 10%. That is, I arrived at a new quest, tried it, and with a creaky realization that the "knowledge" was not allowed further, and there was not enough "black matter" to open the next lecture. d) two out of ten students stopped at level 35, who came here. Reason: achieving level 35 is “sufficient” to be able to receive an assignment for subsequent enrollment in an internship if it [the internship assignment] is successfully completed. Since the target audience of our article is JavaRush students, that is, developers who, so to speak, “not with a word, but with a line of code” prove their intention to become a Java Junior|Middle|Senior Developer, then in the last diagram in this article we would like to look at glass, say it is "half full". That is, in the next diagram, we will display the percentage of the total number of students who reached the level that successfully passed this level and moved on (that is, in fact, this is the data from the previous histogram, but considered “from a different angle”). JavaRush Students Big Data - 4 Let us clarify once again, if we say 100 students reached level n, 80 students successfully passed this level, then the bar on the diagram will display 80%. Moreover, if only 60 out of 80 students who got to the level successfully pass the next level, then the bar of the diagram at this level will already show 75%. What will the information from the last screen tell us? Here's what: on average, 85-90% of students who come to the level successfully pass it. The largest number of “stops” at a level was at the beginning of the quest (levels 0-4) and at the end of the quest (level 40). Brief summary of the article: 1. Only every fifth of all interested users intends to complete the quest (third level and higher). 2. On average, at each level, 10% of students drop out. 3. 20% of the developers who have reached level 35 do not regret completing the quest further, but go straight to an internship. 4. When you pass each new level, you “overtake” another 10% of other developers in the marathon for the future of receiving an offer for your first or subsequent job in the IT industry. 5. No more than 0.085% of the total number of initially interested persons completed the entire quest. 6. Systematic practice and the credo “never give up” will first bring you to the elite number of those who have completed the JavaRush quest, and then (if you continue to improve your skills at work) will bring you to the elite number of Java Developers who will choose vacancies at will. 7. Success in learning Java is more like a marathon, during which, imperceptibly, but consistently, the vast majority of those who “started the race” leave the race before reaching the finish line. 8. You don’t need to “run the marathon the fastest,” you just need to keep running, going further and further through the levels. PS I apologize if the information provided in this article does not agree with your personal beliefs. All information provided here is only the subjective opinion of the author and is not the “ultimate truth”.
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