wiki:DataMining

Mining the KLP data

The KLP data can provide a lot more action items than it does at present. Currently it is used more as a progress report on the programmes.

Student Migration

When child leaves one school and joins another school (both within the purview of KLP), it should be possible for us to link these two children together. Student migration is a rich field of study in the larger perspective of education.

At risk children

The library data can provide data about children who are at risk of dropping out of the school system.

Other Big Questions

  1. Effectiveness of the programs and organizations.
  2. Underserved versus overserved geographic areas.
  3. Efficiency of programs and organizations.
  4. Gaps that can be filled by philanthropy and social entrepreneurship.
  5. Education profiles by cluster, block, district, etc.
  6. Generating citizen involvement on a specific issue - education. How many citizens from where will support? We need to find out from our "share your story" which parts of the state are more active than others and based on this we can generate specific programmes to catalyze demand.
  7. Why certain clusters / blocks / districts do better than others and what can we learn from them.
Last modified 8 years ago Last modified on 03/15/10 20:10:37