Using Big Data to Reduce Dropout in Schools

Dropouts in school is a big issue, because there is always a reason behind it that can be solved, if even we manage to identify this reason, and that’s precisely the challenging part. Education is very important, in any society. It enables to learn and develop our skills and competencies, to have a better job, it makes us self-dependent, helps to be socially integrated, enhance one’s confidence, and it makes the world a safer and better place. So, managing to link academical issues with unfavorable external factors or environments thanks to recent technology, would have an important positive impact on, of course, the individual itself, but also the society as a whole, and it would represent an important innovation in the schooling system.

But there are limitations to big data, such as the availability of big data, because we do not have data for everything. Plus, “in addition to issues of availability, we also typically only have access to certain kinds of data. Big data is essentially capturing and examining patterns, and typically it tells us more about what people actually do, but even if it is of great value, this is not sufficient for all kinds of social science research. We also need to understand the meanings of that behavior which cannot be inferred simply from tracking specific patterns” (Rebecca Eynon, ‘The Rise of Big Data: What Does It Mean for Education, Technology, and Media Research?’, pp.237-240).

So how and in which fields, can social entrepreneurs, using big data help reducing dropouts in schools? In this essay, using research methods such as interviews, I will show how social entrepreneurs in the educational sector can act and implement management implications into schools by using big data to improve educational methods, develop new programs and find and face the problems of struggling students to avoid dropouts. First, I will talk about how big data enables to customize school programs for each student, then how to find the right teaching method thanks to surveillance technology and how big data helps analyzing behavior and do predictive analysis to increase efficiency, and finally how it can also be used for career predictions.

Unique Individuals with Their Own Datasets

Indeed, every person has its own personality, hobbies, likes, dislikes and also learning preferences. Of course, teachers already try to adapt their learning style to everybody, but in a class, everyone is still so much different that differences will persist, and some will have more difficulties than others, and some, on the contrary, will get bored, etc. Of course, the more students there is in one class, the more this phenomenon will be observed and problematical.

Big data allows to have information about each student’s individual intellectual capacities, personal knowledges but also about its hobbies and personal life. So, this information can be used to offer a personalized learning process for each student. Students would more be seen as unique individuals, than as a ‘class’. Big data would create a new schooling and teaching system, far from the actual obsolete tailored one. Thanks to big data, the teachers easily have access to students’ data and statistics. So, they can intervene rapidly to compensate student’s weaknesses. Indeed, teachers have a real-time trace of each student’s performances, so they can help them more easily to improve their results and notes.

But in order to put this in place, schools need have a way to analyze each student and find out how they learn, their strengths and weaknesses. And this has to be made on a long-term period, with other specific factors, to have the most accurate and trustworthy information. The more data educators have, the more tools they have to help their students.

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The Right Teaching Method Thanks to Surveillance Technology

One of the reasons why some students fail and drop out of school can also be due to some classes and inappropriate teaching methods. But it is hard to evaluate a teacher’s class and effectiveness, as the only measurement is the student’s involvement, participation and grades in that class. But now, thanks to that surveillance technology, teacher could have access to data that actually show if their classes and teaching methods, and more specifically, which lectures or which activities are appropriate and working, or if not, which ones aren’t and why. This data can, for instance, show how well teacher manage to keep their student’s attention during their class, or how long it took for a student to start getting correct answers, or also identify at which moment a student started to be lost or confused. These kinds of information could help teacher to know where they can improve, and this analysis also permit to get performance statistics. Indeed, this would motivate teachers to improve or find alternative ways to capture the attention of their students and make the lecture be more interesting for them, because they would know specifically why and when something is not working or less efficient.

Big Data That Analyses Behavior

Behavior can also tell a lot about a student’s situation, and whether or not she is going to potentially drop out of school or not. So, big data will enable to gather information from the school and combine them in order to understand one’s behavior. For instance, if a student has problems at home such as with his/her parents, financial troubles, or if he/she gets bullied at school or simply has a lack of support at home or at school, those are factors that will very likely have consequences on the student’s behavior and academic success. Also, some of the most common psychological issues students face today are substance abuse, learning disabilities, attention/hyperactivity disorders, and autism-spectrum disorders. Today, educators simply make some assumptions about the causes of one’s behavior, but now with big data they could have real trustworthy sources to back up their theories. Indeed, big data enables to gather enough information and analysis to find trends that educators could use to intervene.

Predictive Analysis to Increase Efficiency

You can start making prediction analysis when you have collected data from a long enough period. Short-term data cannot give information accurate enough to predict a solid, reliable future. For example, thanks to surveillance data, teacher can notice that during certain periods (for instance, before holidays) students are less concentrated and more distracted. So, during these periods, teachers should adapt and make lectures plans to get the most out of this time to bring students to focus. It would, for example, not be the right time to start a new topic because students will be distracted and therefore miss some important information about the beginning, so, the basis of the new topic, and this will probably be needed to be catch up later, and so, a loss time. It would be better to do reviews or activities created to help students concentrate more easily. Big data could also be used to predict if a student could potentially have difficulties or fail a subject. The more information is collected on a student, at school, at home, his/her personal background, the easiest it will be to foresee if he/she is going have difficulties in certain classes.

Career Predictions

Understanding a student’s behavior and managing to make him/her concentrated and interested in lectures is a really good thing. But, if a student still doesn’t understand what this could bring to them in the future and what they could do afterwards, it would not make much sense for him/her and still could be a factor for dropping out of school. Therefore, if social entrepreneurs would bring big data into school not only for the academical part but also future, destiny and career-oriented part, it would assuredly help students find an aim to what they are currently learning and strongly motivated them.

This will be possible thanks to big data through analyzing almost all the characteristics of a person, not only academical, but also personal. And by combining those, we could find what lecture the students paid the best attention in, their abilities and limits, what they liked and disliked the most, what kind of careers they are interested in, why and what would actually best fit to them. Plus, as they would sooner or later have to make a choice regarding not only career, but also potentially higher education, this deep and complete analysis of individual data will give accurate and very helpful answers that would help and guide them to make the right choice. Furthermore, social entrepreneurs could also use big data to predict future needs on the job market. For instance, a study shows that 85% of the jobs in 2030 do not exist today. So, big data could prepare students to future jobs that are not even existing now, and this can also give them hope by showing that the availability of jobs in the current market is not an exhausted list, and that they might be made for something that is not to be found in the market yet, but would be needed in the future. Indeed, big data could inform and anticipate predictive needs for a future job market. This would enable students to better visualize the future market they will be working in, learn and focus in consequence, and not just according to simple, unprecise assumptions.

Conclusion

Education is one of the most important sectors in the society, it shapes the future. Therefore, many social entrepreneurs invest in education and dedicate their time and work in order to improve the school system, which is a priority. And improving the education system means using all the tools available like the latest advanced technology such as big data. This enables social entrepreneurs and educators to use their time more efficiently, and to be more productive and innovative, while finding new methods to improve the educational system by finding cause to effect relation in order to reduce or avoid dropouts. So, big data could be a very useful, if not an essential tool in schools, because it enables teachers and educators in one click to have access to a wide range of school driven, but also personal data about each student. This enables to act fast and efficiently in order to customize programs and orient in the best way each student individually and avoid dropouts. Indeed, we retain from big data that it is a real-time follow up of student’s performances which helps them to improve their results and interests by acting more intelligently and by detecting, and so, avoiding problems. But one of the important limits of big data is the ethical issue. Indeed, some consider that big data is good for many things like market studies and science, but that it doesn’t deserve its place in education, because of privacy issues. Indeed, they consider that privacy and big data cannot coexist, because the data is so big that everyone is personally identifiable from multiple angles, even once you remove ‘personally identifying information’. This means it is ultimately a threat to pupils and students. But if this privacy policy barrier is removed, and so, respected, there is definitely a place for big data in education. The question is, will schools get the funding they need to implement it? Without methods to accurately measure data and compile it, with professionals, social entrepreneurs to implement and analyze it, big data will never find a place. But if it does, the educational experience could be revolutionized and improved greatly.