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Educational Analytics

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Teqnium's talk on "Educational Analytics" at eIndia Education Summit (July 2013).

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Educational Analytics

  1. 1. It is time for Educational Analytics. DR. SREERAMA KV MURTHY Talk given at eIndia Education Summit, 24th July 2013, Hyderabad International Convention Centre.
  2. 2. 1. Quality institutions of the future must be data-driven. Good institutions must invest in comprehensive data collection, warehousing, reporting & analytics infrastructures. Near real time data needs to be made available, to Heads, Faculty, Placement team as well as Students. Case Study (2012)Concept Implementation Steps Informed decision making & better accountability at all levels, irrespective of size of institution Clear definition & tracking of performance metrics Expected Benefits
  3. 3. 2. Predictive Analytics can help students choose the right courses / programs. Deploy smart counseling at upper primary & secondary school levels What programs suit your interests? What programs are you likely to be successful at? Case Study (2012)Concept Implementation Steps Reduce dropout rates in subsequent years Prevent issues of weak learning Expected Benefits
  4. 4. 3. Learning impact can & should be measured, especially for our teachers. Integrate continuous measurement during & after teacher training. Quantify learning impact on the teacher. At all levels: higher education, vocational skills, K-12 Case Study (2012)Concept Implementation Steps Quality trickle-down Cost-to-benefit measurement of funds deployed for teacher training. Expected Benefits
  5. 5. 4. Digital Learning allows unprecedented measurement, and hence personalization. Implement e-learning wherever feasible. Deploy platforms that support extensive data collection & reporting. Aim for individualized, personalized training. Keep the learners continually in-the-know on where they stand. Case Study (2013) Concept Implementation Steps Better learner engagement. Accelerated learning. Expected Benefits

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