Having a quick look at IBMs approach to data analysis (David Loshin, March 2011), it is quite obvious that the education world is not dealing with the growth of unstructured data in the way businesses do.
Whereas businesses are developing competitive business intelligence solutions, schools either reach "analysis paralysis" or chose the data they want to support a gut feeling decision.
Data is about delivering actionable intelligence and yet most schools are still dealing with posthumous data. Data that reports on the past. Schools must move on to the analytics sphere to develop strategies that will drive student progress forward (at least!).
Reports have to focus on what needs to be done in order to achieve.
The result of predictive analytics formulated as actionable intelligence can be integrated directly into the existing reporting process by synchronising data from different sources:
•SOWs
•Specifications
•Class based assessments
•vLe interactive exercises results
This requires a robust architecture tuned to the framework for reporting. It must be coherent and this has a direct impact on how raw data is mined. It is all about delivering actionable intelligence. It requires an architecture which enables a continuous synchronization of data from multiple sources.
Alternatively it requires you to bring the functionality of your SIMS database to the 21st century rather than going on automating 20th century processes.
Do not use your data manager to crunch data, use him/her to deliver processes which will deliver data at any time. Get him/ her to bring SIMS into the 21st century.
Intelligent data is what it is all about.
By adding multidimensional data analysis to this architecture schools will be able to link another set of data sources:
•Class/ teacher results
•Contextual results
•SOWs
•Line manager
•INSET/ CPD record
•Examiners report
Rather than creating more data, this technique identifies patterns. Patterns are a good foundation to drive organizational optimization (as IBM puts it).
This optimization is driven by a series of questions:
•What? Use multidimensional mapping to see what is what. If you deal with student progress, where are they?
•Why? Why are those patterns present? Why are students under-achieving?
•What if? This is where managed innovation comes in
•What next? What is the objective?
•How? What needs to be done to meet this objective
Opening the way to analytics will open the door to profiling. This will enable schools to model student progress in different situations... Profiling will enable you to predict problems and make sure they do not occur.
The really amazing thing is that these tools are here right now. They are not magic. Businesses have been using them for a while. The key issue is management. Is management ready to let analytics rip and present them with a real picture of their school?
As usual, the answer has nothing to do with technology. It is about managers lowering their guard in order to be able to...learn.
Get in touch if you want to know more.
Whereas businesses are developing competitive business intelligence solutions, schools either reach "analysis paralysis" or chose the data they want to support a gut feeling decision.
Data is about delivering actionable intelligence and yet most schools are still dealing with posthumous data. Data that reports on the past. Schools must move on to the analytics sphere to develop strategies that will drive student progress forward (at least!).
Reports have to focus on what needs to be done in order to achieve.
The result of predictive analytics formulated as actionable intelligence can be integrated directly into the existing reporting process by synchronising data from different sources:
•SOWs
•Specifications
•Class based assessments
•vLe interactive exercises results
This requires a robust architecture tuned to the framework for reporting. It must be coherent and this has a direct impact on how raw data is mined. It is all about delivering actionable intelligence. It requires an architecture which enables a continuous synchronization of data from multiple sources.
Alternatively it requires you to bring the functionality of your SIMS database to the 21st century rather than going on automating 20th century processes.
Do not use your data manager to crunch data, use him/her to deliver processes which will deliver data at any time. Get him/ her to bring SIMS into the 21st century.
Intelligent data is what it is all about.
By adding multidimensional data analysis to this architecture schools will be able to link another set of data sources:
•Class/ teacher results
•Contextual results
•SOWs
•Line manager
•INSET/ CPD record
•Examiners report
Rather than creating more data, this technique identifies patterns. Patterns are a good foundation to drive organizational optimization (as IBM puts it).
This optimization is driven by a series of questions:
•What? Use multidimensional mapping to see what is what. If you deal with student progress, where are they?
•Why? Why are those patterns present? Why are students under-achieving?
•What if? This is where managed innovation comes in
•What next? What is the objective?
•How? What needs to be done to meet this objective
Opening the way to analytics will open the door to profiling. This will enable schools to model student progress in different situations... Profiling will enable you to predict problems and make sure they do not occur.
The really amazing thing is that these tools are here right now. They are not magic. Businesses have been using them for a while. The key issue is management. Is management ready to let analytics rip and present them with a real picture of their school?
As usual, the answer has nothing to do with technology. It is about managers lowering their guard in order to be able to...learn.
Get in touch if you want to know more.
