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Technology can change the ‘One Size Fits All’ model of education: Viros Sharma, ITC Infotech

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“Our education system is based on ‘One Size Fits All’ model, while the human learning reality is entirely opposite. Curriculums of all education boards need to be checked against the baselined skills in the market from relevance and practicality points of view. Learning Analytics has the capability to play a central role in countering these challenges and enabling learning process improvement,” says Viros Sharma, Vice President & Global Business Head – DWBI & Analytics, ITC Infotech in an interaction with Mohd Ujaley.

Edited Excerpts:

Our schools, colleges, and educational bodies such as UGC, AICTE, CBSE, NCERT, NIOS and state boards have humongous amount of data related to students and teachers. In that light, what role do you see for data analytics in education?
Our education system is based on ‘One Size Fits All’ model, while the human learning reality is entirely opposite. Curriculums of all the education boards need to be checked against the baselined skills in the market from relevance and practicality points of view. Each individual student has her own learning style e.g., some like text while others learn from audio-video better. Our courses do not give content delivery options aligned to individual learning patterns and that is a huge area of improvement.

Our teaching methodology is also one way and there is no scope of 360 degree feedback for teaching process and capability improvement. There are no lessons learnt captured by teachers and students across the cities, states and country to analyse the common areas of focus and improvement that can benefit the entire education system. Learning Analytics has the capability to play a central role in countering these challenges and enabling Learning Process improvement.

What kinds of data, have schools traditionally tracked, which can be analysed?
Traditionally, data related to enrolment, attendance and marks are captured in our schools and that can become a good starting point for analysis and decision making. Data pertaining to demographics like age, gender, socio-economic status, previous academic record, grades, schools that student attended, cities that student went for studies.  Similarly, patterns of attendance can help in the correlation of attendance with scores to identify the target scores and related minimum of number of classes required and optimize the course delivery speed, when there is a large number of students under the weather or impacted due to seasonal viral fever. Also, correlation of marks with subjects, chapters and questions along with teachers’ experience, qualification and timetable can help us improve the course content, teaching methodology – examples, ideal number of hours spent on a particular part of courseware etc.

If an educational organisation adopt analytic, what kind of changes the deployment of analytics tools are likely to bring in education and learning outcomes?
Analytics needs process adjustments, IT applications and digitization. It will need cultural change towards data driven decisioning. What is measure is what controlled and improved. All the organisations will have to start measuring related key performance indicators aligned to their vision and mission. Analytics can bring effectiveness and efficiency in learning management system, could provide customised teaching aligned to student micro segments’ learning inclinations and a transparent and real-time measures at board, state, city, institution and individual levels. It also helps in teacher growth models based on feedback and student performance and industry participation oriented KPIs leading to relevance of courses and increase in industry absorption level. Analytics has potential to give direction for curriculum development and delivery and identification of commonality at the all levels in different boards for same leading to seamless grade portability across all boards.

What are the major factors that are driving the demand for data analytics in education?
Data abundance is beyond human comprehension and analytics tools make it possible to manage it. Data types (including Portal and Social data) make it extremely difficult to integrate, organise, analyse, visualize and trigger action – all this is possible with the help of analytics and hence its demand is naturally growing.

What are the major obstacles facing education data and analytics?
Some of the basic hurdle to development of data analytics are privacy laws, data sharing, planning and execution in a coherent manner, cultural shift from hunch based decisions to data driven decision, and inefficiency protection by comfort zone oriented, ritualistic system.

Privacy issue could be address by creating a process which seek individual consent at the time of data capturing.  Analysis needs to be done in an anonymous manner – data encryption, data masking, aggregate level analysis are some of the techniques that help Learning Analytics coexist with privacy laws.

Other than privacy, there is less awareness about how to use data analytics. How this can be overcome?
To overcome this challenge, teachers, administrators and students must be provided with BI reports regularly. They should also be given training and usage log analysis must be institutionalised for better awareness and hence adoption levels.

Majority of education institutes or groups in India are challenged by limited funding. Hence, they are unable to afford costly, propriety software (analytics software). How we can address this challenge of affordability?
This is indeed a challenge but i feel that consortiums of educational institutes can go for joint implementation of Learning Analytics that will reduce the per student cost. Analytics as a Service model is another possibility from System Integrators organisations or independent software vendors point of view, which lead to lower cost for end-user.

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