Learning Ledger FAQ

Whilst Learning Ledger is really simple to use, everyone wants to know about how we load data, deal with data and get you what you want.

We can’t give away our secrets but we can tell you about Ledger and how we work it for you.

Is Ledger for Leaders or Teachers?

Both!. Teachers are interested in their students in their classes. Heads of Departments might want to look across a subject at year level. Principals might take a more holistic view of data.

Everyone is welcome with self defined Alerts available at teacher and leader level.

Diocese or Department levels can even roll up data to meet their interest.

Really? All learning data in Ledger?

We say YES to learning data from all sources.

There is so much data that schools have and collect. Over 20 data sources is usually the average count. It’s amazing how much diagnostic testing goes on and just how many other sources of grades and pastoral based data pops out of the woodwork. It’s also amazing how none of this data is ever unified in a single view.¬†

Ledger is designed from the ground up NOT to discriminate about what data is and where it comes from. We take a very holistic view of data; ALL DATA IS GOOD DATA and is worthy of aggregation with other data. The common key to all data is an individual student. All data starts with a student link.

We have purpose built connectors for most diagnostic data. NAPLAN, PAT, ALLWELL and all of the formats of tests in these gene pool are ready to load. Pass an excel sheet and your data is loaded into Ledger.

Gradebooks from SIS, LMS or other sources we load via spreadsheet for you. After our first load, we have a data recipe that looks after all future updates. All the other data like Attendance, behaviour, pastoral etc , all comes the same way. We even allow other systems to POST data directly to Ledger so that there is no manual intervention.

If you use CANVAS, we have a connector that collects all gradebook and participation data and publishes that into the Ledger. We need some API keys from you to access Canvas on your behalf.

There is no bottom to data sources however we have seen many. This adds to the value we bring to you. If we have a data recipe, your data is loaded!



Track down detail in Ledger

Each Student has a time line of events built automatically. This is the ledger and every event for each student is recorded and described. 

If you wanted to look into a Term or Month of activity for a Student, one click. If a new student came to your class, one click to see a history. 

Ledger is like a bank statement, every transaction is built from the bottom up. Remember, the devil is always hiding in the detail.

How does data find you?

We meet lots of teachers, all of whom have a hunch about what is happening with students and learning. Seeing across all other data points is very hard and time consuming if you don’t have all the data in one place.

Building out a hunch, backed by data from the whole-of-student view, is one way that data finds you. Data can be drawn from multiple sources to give you the insight you are looking for.

The other way data finds you is via Alerts. You can profile what interests you and each time you enter your dashbaord, your data is refreshed.

Because Ledger knows your data, we make it easy for you to point and click at what you are looking for.

Reconciling student names - how to?
We call it “nom-de-plume” syndrome and every school has it. How many names does a student have across all of the systems in the school. MANY is the answer. In many ways Google and Microsoft have standardised¬† references with 1 email address but that is not the end of the line. We also support SSO.

Names in PAT, NAPLAN, and every other sheet you have – are similar enough to be different to a computer. Computers really are not that smart.

Jack Jones is J.J.Jones, J Jones, Jack J, Jacko, J.J.J, Jack. Jack is all of these people so to look at Jack Jones as a complete set of data, we need to iron out these names as the data comes into Ledger.

The BI people call this ETL and they charge a fortune for it. We call it name matching and we do it as we load data and it’s done. We get the hang of what is going on and we make the problem go away. It is even more exciting when proper names of other nationalities adopt an Australian name like GuanhYo is now Lucy. As long as we can catch this person once, we catch them all the time.

When integrated with Scribo, Formative and Explorer, there is no issue with names. With Canvas and other systems that use SSO , we deal with names nicely. It’s the spreadsheets and the ‘in a hurry’ data sets that we find need some attention. We reconcile everything we can and tell you what we need help with.

Everything goes into Ledger wihout a big data fuss.