Data-driven decision making is all about making decisions that are backed up by solid, verifiable data and not observations. Strategic decision making, which was popularized in the 1980s and 1990s, has transformed into a sophisticated concept. It bears the name of big data. With the help of advanced analytic techniques, it is possible to take a close look at large and varied data sets so as to uncover hidden patterns or correlations. At present, big data and analytics are used for instructional applications in the context of higher education. Due to the fact that there is not sufficient evidence regarding the way in which the investment can pay off, big data and learning analytics have not yet been adopted.
Collecting and analyzing large chunks of data is one of the best approaches to improving the learning process. The problem is that educational sectors do not take advantage of the opportunities to invest in big data analytics and language processing. Basically, they do not do what it takes to improve their competitiveness and productivity.
When it comes down to higher education, online and software based learning tools are used to a high degree. Students have tablets and utilize various applications, as well as numerous software-based learning tools to follow lectures, take notes, and even find adjuvant information. Technology is currently shaping the future of education. The phenomenon has resulted in an outburst of data. This information can be used to enhance educational effectiveness and support research on learning. Data mining is highly useful in the field of education, being used to predict the learning behavior of students and optimizing instructional sequences.
Universities and other institutions of higher education draw thousands of students each year, but they do not bother to learn about big data. If necessary to provide a definition, we would have to say that big data describes large datasets whose size exceeds the capability of typical database software tools to capture and examine it. Taking into consideration the emergence of online learning environments, it is important to develop analytics capabilities.
It is essential to get as many details as possible about individual student interactions with regard to web-based learning activities. It is interesting to note what students do to gain a broad understanding of chemistry. In addition to reading the material before going to class and using flashcards, they take private lessons with online tutors. Students like the fact that they are able to receive instruction at anytime and anywhere. It is not necessary for them to try to coordinate schedules with their tutors or come across a convenient location.
There is nothing more important than gathering the large amounts of data and processing it through analytic methods. There are many benefits as far as big data and learning analytics is concerned. It is possible to gain insight into complex situations or problems, such as rates of participation, work schedules or grades.
