My thoughts on Educational Data

For me, I'm not clearly sure about what data engineering is actually meant to be. Of course there is a clear answer in respect to 'what' you should be doing as a data engineer. However, the skillsets of a data engineer depends on the environment one's surrounded by.

To me, I'm surrounded by an educational environment. Not one like udemy or coursera and such where online lectures are the primary source, but a bootcamp where data consumption is limited heavily on the company resource.

That is not to say that data isn't being created during the 'consumption' of such business. But the truth is that when the absolute quantity of data source isn't very high, extraction of data is itself very limited.

Take a student, for example, this student during the course of 7 months of bootcamp is met with variety of choices and tools. And we have to establish that to a student there are two types of time being spent.

First is when actually learning, or being educated. The other is when left alone to digest the material.

In the case of lectures, quizzes, tests, or even self-guided lessons, the student's time can be identified with the former category while the time spent alone, after studies, searching through the web can be seen as the latter.

And moreover, we must assume that both of these categories are needed for a student to be able to actually learn. For the former allows the student new knowledge and the latter allows the student to digest such new knowledge.

The trick is to balance the two so that the student can 1) continue obtain new knowledge 2) persist new knowledge.

Now that the matter of the necessity of such balance is dealt with (albeit little), we now can realize that given a course of study in a period of time, we can make out the average time of such balanced categories as well as the total amount of time spent on each category (may differ by student).

In these aspects, it is obvious that we can't simply make a single student to continuously listen to lectures, solves quizzes, receive tests and so on. And as to the data which needs the consumer's participation, it can be said that it is limited to the actual time the student is given to actively learn (being educated). This is such since if the student is left alone to digest material, the student has the freedom to do what he or she wants and therefore a predefined data format cannot be made.

To a data engineer interested in creating a data ecosystem where data continuously flows in and out of the system allowing advanced and in-depth analysis, it becomes very hard to squeeze data from its' consumers.

And working from such an environment as a data engineer, it is often unclear as to what and how data should be obtained. Of course there are the regular 'why not the student grades? Or student participation?' but such data is not as useful as one expects it to be. Basically, if a single cohort has around 60 students and there are 6 cohorts in a given year, there are 360 students' data to analyze. But education is not a dead fossil. It evolves and changes, it moves and breathes like a living thing. The very core of humanity revolves around this concept of 'change' of which education is not an exception. And as a company, not a government school, the size of data one can analyze has to be obtained elsewhere.

Conclusion

My idea is still far from clear. I have a fear that maybe education related data can only be historical and may only teach us what shouldn't be done. Not being able to foretell the future or estimate what could happen is quite devastating since one would like to believe that data is the driving force... just like history where one is able to learn from it.

There are still work to be done. Working in the meta-phase can be such work. Collecting data from students activities, maybe log data or event sourcing to tell the general direction of work one should focus on.

Whatever the case, the situation I currently stand on will not change in such quick notice and my thoughts will keep on changing as long as I bear the responsibilities of an educational data engineer.