Institutes of education deal with huge volumes of data about the students assembled from application forms, admission forms, learning statistics and more. Big data refers to the massive amount of information that we create on a daily basis. Big data has become so colossal that traditional data management tools, like Excel spreadsheets and manual record-keeping, are no longer able to keep up.
Secure storage of this data is highly essential but so is its intelligent aggregation, comparison, tracking and analysis which is only made possible by data analytics that helps to keep track of the progress of every student individually. Analytics driven Data Management can be most effectively used by the following broad category of people: Students, Educators, Management, Governing Bodies.
Data analytics for students refers to the collection and analysis of a huge volume of data assembled from students in order to track and assess the individual learning progress and academic record of every student besides predicting their academic future and locating and working on potential academic issues.
Through student`s data we can develop as many curricula as many students we have. Based on their preferences/ skills it is possible to develop a recommenders system where different students could, such as, follow different ways to learn the same content.
With the advent of Data analytics and Digital medium, Adaptive Content has become yesterday's reality and Adaptive learning that caters to individual student is today's reality. Designing adaptive learning experiences enables learners to continue their studies, receive feedback, and navigate difficult content even without direct or immediate access to an instructor.
Educators, decision makers and stakeholders are leveraging data analytics programs to identify institutional problems and spot opportunities for positive change. Software programs enable analysis and interpretation that spans a diverse range of demographics, and from there you can develop new strategies to propel your institution forward.
Learning analytics can transform models and pedagogical approaches. The general idea is to innovate i.e., to aggregate support to student`s success. It is not the goal of this approach to substitute the teacher. It may assist faculty in tailoring their teaching to optimize learning resources and organizing courses that facilitate student`s engagement.
An education system powered by data analytics helps institutional mentors in devising and crafting scholastic experiences and study curriculum in accordance to individual ability, learning approach, preference, and performance of students. The teachers can get individual feedback on the performance of every student and of the entire class and modify their mode of teaching in accordance to cater to the learning needs of every student in the class.
Searching through a wall-to-wall arrangement of file cabinets is messy and time consuming. Since big data relies on a technological infrastructure to capture, store and manage information, it’s much easier to find what you’re looking for. Data analytics, along with the right software, will help you create a more collaborative environment. Since data is available in one centralized location, all you need is internet access to find what you need.
Proper resource allocation is crucial in higher education, and your data is the key to efficiency. Data has traditionally required manual sorting and transcription, which is time consuming and can take weeks if not months. And if you need customized reports compiled on a regular basis, this can take just as long.
Your employees’ time can likely be spent doing more beneficial tasks. An analytics program will automate a lot of this tedious work and the luxury of digital information makes accessing data quick and easy, which can save you money in the long run.
Data analytics can be efficiently employed to supervise and visualize the educational and behavioral pattern of every student. The data is analyzed to pinpoint the best educational practices and then the rest of the students are encouraged to adopt the same practices and study in a similar approach to attain maximum academic success.
Data analytics can be efficiently employed to track the usage of technology, devices, hardware, and software through the entire day and then assessing the results to determine which delivers the best. An educational environment powered by data analytics aids in keeping professors, teachers, students, assistants and everyone else working together on different projects on the same platform. Effective and efficient use of data analytics for the fusion of pedagogy and technology helps to develop a coherent, analytical and powerfully driven ecosystem that makes provision for real-time exchange of skills and knowledge.
Ensuring data flow is absolutely essential for big data analytics. Poor internet connectivity and poorly integrated data systems make it difficult to access data and ensure data flow. It will be counterproductive if poor quality and incorrectly formatted data are used for educational analytics.
Educating and training educators is another major and time-consuming challenge for the application of big data to the education sector. Even to get all teachers and mentors to cooperate and show eagerness is itself a big milestone.
With big advantages and opportunities to use big data analytics, more institutions and organizations are striving to steer ahead of challenges, and embracing it for achieving better outcomes.
With data analytics, there’s no need to rely on blind faith when making decisions. You’ll have numbers and statistics to back up your decisions, which can lead to more successful outcomes.
Data analytics tools depend on the same type of technological infrastructure to capture, store and organize information, so it’s easy to find what you need.
Since your data lives in one place, there’s no need to search through dozens of files and folders to find one report, making the process much quicker.
The purpose of leveraging big data is to improve the student results. With big data in the education sector, you can monitor activities such as how long they take to answer a question, which sources they use for preparation and which questions they skip on the exam.
Predictive analytics enables an organization’s stakeholders to think ahead with algorithms that extrapolate from past data to determine what changes are likely over the months and years to come.