Data analytics has seeped into most areas of corporate lives — education notwithstanding. Though data and analytics are not yet used as essential tools in the management and running of schools, colleges and universities in India, it is a fast growing sector that can profit from using data analytics to their advantage.
Analytics can improve operational decision-making while helping to measure institutional performance against goals.
We found the following six areas where data analytics could really aid the education sector.
Building On The Traditional Method Of Collecting And Using Data:
Traditionally, most educational institutes have a broad range of data about their students, usually collected from their admission forms and applications. This data includes any combination of: location, previous learning activities, health concerns, attendance, grades, religion, and caste-based reservation, particularly in India. Most of the institutes do store this data, but a more intelligent system that can and aggregate, compare and track the data can come in handy while tracking the progress of the student.
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Analytics For Educators:
An analytics and data-driven system can help institutions craft learning experiences and curriculum according to ability, learning style and preference of the students as well as the teachers.
Educators can receive feedback on the performance of each individual student and of the class as a whole and adjust their teaching material and action to influence the students better. By examining the feedback data, teachers can spot students who may need additional help or encouragement to spend more time on the content and identify areas where the class as a whole is struggling.
Analytics For Pupils:
“Learning analytics refers to the interpretation of a wide range of data produced by and gathered on behalf of students in order to assess academic progress, predict future performance, and spot potential issues,” says a brief issued by the department of education in the US.
Learning content in most schools and universities is created in advance of the learners taking a course in the form of curriculum, such as, textbooks. This method can be improved, as each learner has differing levels of knowledge when they start a course. An intelligent curriculum can adjust and adapt to the needs of each learner. Instead of a generalised course for an entire class, each student could have his or her own course based on her life experiences, learning pace, and familiarity with the topic. The content in the courses should be as adaptive, flexible, and continually updated. The black box of education can be opened and adapted to the requirements of each learner.
Governance And Management:
One of the basic things that can be regulated and taken control by an intelligent analytics-based programme is the attendance and login times of both students and teachers. Peripheral data analysis could include the use of physical services in a school or university, such as access to library resources and learning help services, among others.
Analytics and data science-fueled programmes can help organisations get deeper insights into the student’s progress, and can thus help them understand their strengths and weaknesses. Programmes such as running predictive analysis to pinpoint students who are at an increased risk of failure, enabling closed-loop student interaction with suggested intervention actions, communications and tracking and providing personalised interventions when needed are some of the advantages.
In universities, where professors, teachers assistants and students have to work together on multiple projects, a smart learning environment can help everyone be on the same page. “Effective, efficient and engaging” conversations would be helpful to support the fusion of technology and pedagogy to create a coherent ecosystem that provides real-time and ongoing exchanges in knowledge and skills.