How to structure K-12 learning data to create student learning stories – Part 2

How to structure K-12 learning data to create student learning stories – Part 2

Open up learning data so that teachers are free to see

Part two of a three post series looks deeper inside the data closet and possibilities of K-12 schools. Lurking in all corners is data from multiple sources that when unleashed, often compete for attention. All of a sudden BIG DATA syndrome lurches forward into an unsuspecting audience. Keeping data terminology simple is of paramount importance. Post 3 will discuss how to run with the energy you will unlock in this post and deliver a framework for teachers.

I often ask teachers who come along to “data for learning” sessions in schools, “What data really matters to you?, “What data visibility would help you to help your students?” Surprisingly, most teachers don’t lead with “All I need is Power BI and a consultant to develop charts and data analytics”. Resoundingly teachers see their priority as doing the best they can to help their students achieve the absolute best they can. As true as that is, I  never really get an answer. “What have you got?” is the most common response. It’s like a standoff; “show us what you have and we will take a look”. It is a reasonable response considering many schools don’t have a system for organising, packing and unpacking data in a way that everyone feels a part of culturally. This unfortunately describes many of the to-and-fro data machinations schools go through when dealing with data.

More times than not, data in schools is rarely imagined as a fountain of collaborative knowledge. Data is thought of as more like secret silos of collective recount and just another thing to manage and transpose.  Not all teachers know where to go to access data or indeed what they could ask for. Online systems like OARS and SCOUT, and many others, open a limited window into data that external providers want you to be happy with. These systems have multiple logins and access points to remember and never really bring data back into practical frame of reference for teachers. Data is described and displayed as envisioned by developers. For example, SCOUT can tell you about one student at a time, not the class or cohort.  Most times, less than 20% of teachers in a school access these systems. That means 80% of teachers don’t have the time and find access too hard. Not a good run rate for any measure of progress.

So, how do we progress? There is an element of conscious incompetence when it comes to knowing what data there is and what value it holds. Another way of saying this is that many teachers don’t know what they don’t know. Until a ‘Kondo’ declutter event happens both in the physical data closet, and in our thinking, there will be no new windscreen through which teachers can explore a hunch or find a new direction. The current rear vision mirror, useful for lane changing in traffic, will persist. I recommend a simple Kondo-style approach to data organising, starting with a common framework to build momentum.

Data Domains

We can’t advance data conversations without a framework that underpins data. We can’t continually talk about ‘stuff’ nor can we declutter our ‘stuff’ into a containerised system if we don’t have containers. I believe there are six primary data domains in every school. That’s six ways we can declutter data.

  1. Diagnostic  
  2. Behavioural – Attendance – Compliance  
  3. Pastoral wellness – Participation  
  4. Academic growth
  5. Targeted skills development –  Formative – reading , writing , maths – and ‘apps’ for that
  6. Observation – Cognitive capture

The list of Data sources I highlighted in Post 1, all neatly slot into these Domains. In all categorisation challenges, the key phrase to remember  is ‘less is more’.

Finally I get to build out my metaphor for Blog 2.  De-boned, these domains represent the six faces of a Rubik cube. The Rubik cube represents the complete student learning data story of each school.

When teachers ask , “what teaching and learning data do we have?” the answer is that we have six Data Domains. Imagine each one as a side of a Rubik cube.  

Data Sources

NAPLAN, PAT and ALLWELL are great examples of Diagnostic Data Sources. Every Data source logically belongs in one of the six Data Domains and is a row or box on the Diagnostics Domain face of the cube. Each Data Source has a context, year and other surrounding metadata that makes it  either unique or simply more of the same thing. Let’s label the Diagnostic domain as Orange in color and each Diagnostic Data Source as a row on the Diagnostic cube face. The rows could be organised by year or more granular learning breakdowns like Type of Test, Reading, Writing, Comprehension (that’s the easy part done by data people).

There it is.  We have a base structure into which the initial clutter of diagnostic data Sources are organised. When teachers want Diagnostic information, there is a Domain in which all diagnostic Data Sources live and everyone uses the same terminology.  Make sense? Now it’s time to go one more level.

Data Elements

The clutter and detail found in most Data Sources is actually in the Data Elements, the pieces of information and specific content contained inside each Data Source. NAPLAN, for example, is a very rich source of many data elements. From Band to Scaled Score to question correctness, multiple data Elements exist within each data source. Don’t worry about the elements now. Good data storage will offer you choices around these data elements, hopefully in a big menu, tick box format.

Your initial burning question can now can now be expanded confidently, knowing you have the right ‘stuff’ in the right place.

  1. I am after Diagnostic information ( Domain)
  2. From NAPLAN 2018 ( Data Source)
  3. ..and I would like to see Band, Scaled Score and Raw Score for Reading (Data Elements).

Now, all you have to decide is the volume of data  you want. Do you want this information for:

  • A Student or Students?
  • A Class, your Classes? (because you are a teacher with a roster so that would really help)
  • A Cohort / House / Year or other aggregation?

How to think about data across Domains and Sources and then run free.

Imagine this new Rubik Super-Cube in your hands. You have data from your six Data Domains in sight. For a student you can see across all Domains of data, as you can for a cohort or class. The Cube metaphor implies that all volumes of data across all six Domains is available at any level of  inquiry. Be it, Student, Class, Cohort, Subject, House or Year, the query is the same. The only difference is the amount of information you want to look into.

With this metaphorical magic in your head, you can now frame any question using your general intelligence, something you have and computers don’t.

“Can I see Pastoral data on Personal Development (a row Data Source from Pastoral Domain- Yellow) against the Reading results from NAPLAN 2018 (a row Data Source from Diagnostic Domain- Orange)?” I usually add ‘Please’ but Computers don’t know that word either.

Imagine twisting  your Rubik Pastoral – Personal Development Data Source row across the face of the Diagnostic – Reading Data Source. You have your view side by side and the cognitive ability to run with it. As with a real Rubik cube, your twists and turn combinations are up to your imagination.


The only remaining question is what Data Elements you would like to see from each Data Source? This will define the level of detail you want from each Data Source to quench your insatiable thirst for learning growth insights.

Everything improves from a solid and consistent starting framework. These examples are just some simple starting gymnastics that you can do with organised Data Domains and Data Sources.

To recap the main points in this post.

  1. There are six Domains of data in K-12 Schools.
  2. In each Domain, there are multiple Data Sources. Start by finding a few but do understand that when a new Data Source arrives, it will fit into a Domain. That’s the Kondo ‘less is more’ way!
  3. In Each Data Source, there are Data Elements to see. This is Post 3.

The real excitement comes when your school has a platform approach to data, one that allows everyone to confidently explore data up, down and across the cube,  the way they want to. I started at the top of this post with and image of the end game.

In my final post, I will talk about how all of these Cube formats with Domain and Sources completely mixed, all make sense. Sometimes the answers you seek come from multiple Domain, Source and Element data pieces. Why not? The structure of the data should support the interest you have.

When you have a framework in motion  you can construct any combination of inquiry. The most important feature of any system is the ease at which you can snap back to a fully solved puzzle and start again. This would be like having Marie Kondo come back into the room and declutter all over again. Yes indeed, this is mandatory!

Mark Stanley is CEO and Founder of Literatu. :

It’s time for K-12 schools to “Kondo” their data into simple student learning stories – Part 1

It’s time for K-12 schools to “Kondo” their data into simple student learning stories – Part 1

Declutter your data to find real student learning stories

Part one of three posts introduces the idea that for K-12 schools to be successful in using data to grow learning they need to declutter their thinking, and data. Giving  teachers a clear line of vision into each student’s learning story is the Kondo goal. Posts 2 and 3 will discuss how to get a Kondo mindset working at your school to progressively build a beautifully organised learning support space.

Marie Kondo’s decluttering philosophy has people everywhere re-thinking how simplicity trumps clutter and stress. This simple idea of people being in control of all of their ‘stuff’ moves to the top of everyone’s to do list as soon as they read Marie’s  book or watch her TV series. Decluttering applies to our book collections, Facebook friends, and even our family members. The same simple principle applies to K-12 schools and the data they collect in cluttered, stress-driven systems.

In a nutshell: Schools should decide on and organise the learning data that brings joy to teachers’ lives every day, and release what doesn’t. If there is no alignment to teaching and learning, there is no joy in data for teachers. Don’t clutter an already busy life.

The popularity of Kondo’s approach proves how good it feels to eliminate excess in our lives and get back to what matters. If Marie Kondo came to your school to help, what would your goal be? I would suggest a great ‘Kondo’ goal challenge; to have a learning story for every student, in a single accessible and uncluttered space! The one place Kondo hasn’t tackled, however, might be the most cluttered of all: our minds. Let’s get some clear thinking around how we could approach our first goal.

Step 1 . What level of visibility into a single student learning story would delight teachers right now?

Step 1 is not a trick question.  I asked a Learning Director at a large school how many data sources the school collected or had access to, somewhere. In about 20 seconds flat, we had a list.

NAPLAN – for 10 years (across four domains), PAT Early Years, PAT-M, PAT-R, PAT Spelling and Vocab and Science for many years and cohorts, E-WRITE, MYAT, ALLWELL M, R, C, Flourishing, Education Perfect, Mathspace, Mathletics, Maths Online, Probe, PM Benchmark, Soundwaves, Edumate, Observations, Snapshot, Valid Science, PISA and Canvas.

Like every school, there is always lots of data and with that data comes cluttered thinking around what could and should be done with it. All of these data sources can’t have the same importance to a teacher at once. The sheer process of streamlining can unleash a barrage of decisions that don’t really add value to achieving your goal: Should we include all of our data not just some? Why not build a data warehouse? If we have that, we really need this as well! Can we have charts and dashboards across all data? Before you give yourself a chance to declutter, your mind is again full of clutter.

If you focus your thinking around what data makes the biggest immediate impact to teachers, what would that be?  In our experience with many schools, we can highlight what we get asked, in the order we get asked. The ultimate goal is always to build a single student view that delivers clarity and relevance to every teacher, reducing their mental clutter of worrying about what they don’t know. Some teachers suffer from real FOMO stress.

  1. Diagnostic data. There is a lot of good data available from multiple sources. It’s accurate, complete and accessible. This data usually resides in the same closet space, a shared drive full of excel spreadsheets. The clutter, however, is in the data itself. It is hard to shape into a single learning story from multiple formats and scales. NAPLAN, PAT, ALLWELL and PISA offer the most accurate insights in many formats. Decluttering is a simple process when you know how.
  2. Pastoral data has a high priority for visibility and clarity. This data lives in systems that are often inconsistent in detail and context. Pastoral data comes from legacy SIS attendance, extra curricula and behavioural data, surveys and specialised assessments each providing different angles of view across each student’s plane. Importantly, this data is not prescriptive. Pastoral data ignites the cognitive experience of teachers with a backdrop of insights into potential barriers and opportunities. Again, a clear alignment to each student keeps this relevant and simple.
  3. Report data. Yes, the classic academic reporting data built twice a year, usually, is still the big apple that seldom falls far from the tree. The importance of this data is truly realised when it can be easily compared to diagnostic and pastoral data. It’s the process of alignment of these sources that brings the most joy.
  4. Reliable data from other systems. This is typically where clutter and fragmented information re-enters the mix often through multiple Gradebooks. LMS data, formative and specialised application data is usually fragmented and, yes, cluttered with all sorts of ‘stuff’’. The challenge with this data is to work out what part of teacher joy it contributes to, if at all?

Schools suffer at the hands of clutter so much so that SAU (Schooling as usual) is all teachers can do with the information they have. What would happen if Marie Kondo came to talk to you about the clutter in your data closets? Would she focus on decluttering the data closet or the real clutter that may be holding us all back; what we think teachers need to live joyously and FOMO free?

In Part 2 of this series we will talk about how to organise your important data, taking  what you need and delighting teachers with simple uncluttered access. What joy!

Mark Stanley is CEO and Founder of Literatu.


Traditional costs and benefits of data analytics in K-12 education needs disruption

Traditional costs and benefits of data analytics in K-12 education needs disruption

Has anyone ever noticed how the cost of consolidation of data rises in proportion to the value that is delivered? Surely this has to be a new space for disruptive technologies to fix. Technology should really be democratising data availability and access in schools, breaking the paradigm that if you don’t have a big budget for strategic data consultants, you can’t see all of your data.

I have met a few schools that revel in the moment of being different to all other schools in the way they view data. The reality is that every schools has the same data, or near to. Where the only advantage comes from is how fast schools can see into their data and then do something about what they see.

I think technology has lost sight of what it is supposed to be doing in education. It is supposed to be making a difference to teaching and lerning outcomes.

There are 26 days in January to think about the A-Z future of Education

There are 26 days in January to think about the A-Z future of Education

There are really only 26 days in January – well up to and including Australia Day when Australia wakes up. As Australia hits the reset button and starts work on Jan 28, we thought we would craft our predictions for the future of Education, one for each of the 26 days of January. One Letter a day to think about. In keeping with the famous 12 days of Christmas Carol, excluding the harmony, there are 26 challenges we all face in Education. Maybe there are more? I would love to hear your thoughts. You might even re-claim one of the 26 letters from me!

A – Access to the Internet is the foundational future of business and work. The NBN or private Enterprise will fix access for all, one day.
B – Books will remain in vogue for another few years, mainly because people don’t really read anymore, including on-screen, so why change?
C – Commercially printed educational content will reach a use by date of 1 Jan.2020 – there we called it!
D – Data is the high-emission, large footprint exhaust jettisoned from every online interaction. This data exhaust will recombine as the eco-fuel of personalised education and education strategies.
E – Educators will be accountable for student outcomes.
F – Free is not the future of online education.
G – Global access to education will determine the future of economic and social stability.
H – Heutagogy will be driven by shifting labour opportunities.
I –  Individualised, expert tutor instruction will replace low performing classrooms.
J – Juxtaposition and Just now strategies will help to calibrate personalised learning for students.
K – Knowledge will recombine and amplify from shared heuristic data analysis.
L – LMS systems are dead – they ended effective life years ago. No-one has told them yet.
M – MOOC tutoring and assessment services will re-bundle and deliver recognised and credentialed qualifications.
N – Numeracy remains a huge challenge for many Adults in the emerging nations of the world.
O – Outcomes of learning will self-align to labour-market needs, rather than ‘new’ bureaucratic curriculums.
P – Philanthropic funded endeavours will educate the world’s populations before governments and politicians do.
Q – Quantitative progress and visibility into the classroom will replace creative ‘sense-based’ reporting.
R – Research in education will be driven and measured by timely initiatives rather than decades of academic parlance.
S – Standardised testing will reduce. One size no longer fits all.
T – Technology will better assist teachers to help students rather than replace them. AI will get better at structured intelligence.
U – Universities will continue to overprice themselves through an insatiable appetite for money, averages, car parking fees and wealthy students.
V – Vocational Education Training will become so un-regulated, qualifications will be meaningless.
W – Written language and literacy capabilities will forever be in high demand.
X – Xerox copiers will pump out paper for another 20 years or until AI incorporates General Intelligence.
Y – Yielding to education system bureaucrats and politicians will end.
Z – Zealots will never get to teach soft-skills, mainly because they don’t have any themselves.

K-12 leaders and teachers want quicker insights and alerts from their learning data silos – delivered to them

K-12 leaders and teachers want quicker insights and alerts from their learning data silos – delivered to them

Schools create volumes of diverse data in school management, cloud and learning systems every day. Across multiple online systems and manual collection efforts, learning data grows at an exponential rate. Most times, key learning data is never unified. Sadly, this is the Greek tragedy of data in schools. The real hero, learning evidence, capable of helping every teacher personalise student growth and learning, is rendered powerless by its inability to be unified. The catastrophe? Teachers must work harder to understand each student’s learning need without unified assistance from existing data sources.

SIS, LMS and formative assessment platforms collect hundreds of thousands of learning data transactions. NAPLAN , PAT and ALLWELL contribute many more thousands of point-in-time learning records. Cloud delivered systems like O365, Google and Mathletics collect volumes of learning data hourly. Clearly data supply is not the issue, consolidated data delivery and visibility is. Here’s the hint; this is the main causal factor of the tragedy.

Right now, consolidated data delivery and visibility is still a big challenge for schools. How do schools leverage all the learning data they have ‘everywhere’ into a clever ‘thought-support’ capability for teachers? Can technology unify multiple data sources to augment insights and instincts? Can this information find leaders and teachers to answer their unique questions?  The answer to all of these questions is yes, when you approach the challenge the right way.

It’s critical that school leaders think about data strategies as a journey rather than a single destination or one off project.  No school ‘does analytics’ in one pass and if they do, they only have one, often disappointing, pass at it.

Implementing an active data strategy that lets teachers find opportunities and issues quicker, collect stronger data and then share all data, needs leadership support and guidance. You really can’t expect to move from ad hoc data use to automated data analytics in one pass.

Using learning data to quickly identify issues, understand trends and measure success is what teachers and leaders want. The framework to execute and support this must combine three important ingredients; organic interest, teacher PD and a technical ability to deliver. We believe delivering new initiatives the ‘last mile’ is the biggest risk that every ‘system’ initiative faces.

How do you deliver an integrated data capability and culture the last mile?

The most effective risk mitigation strategies focus on internal adoption, inclusion  in the process and efficacy, all more important than a cackle of data consultants.

Start by being tactical. We can recommend six points schools should consider when thinking about creating or extending an environment to start a data culture that uses data and evidence to support teaching and learning.

  1. Insist on agile and economic capabilities in preference to expensive bespoke analytic projects. When disparate data sources come together, it often takes a bit of time to learn where the relationships are and then where the true value is. Iterations need to be quick and economic to run and re-run. When your future state starts with a huge budget, the future can be fragile.

    If you over-engineer what you think you need, you will be disappointed. If you find yourself writing detailed specifications, hit reset.  Remember the data itself and the BI tool does not create any real IP. In this data capability context, the IP (intellectual property) is created from engagement, culture and efficacy around using data to improve teaching and learning.
    Always expect that 90% of the time, you will continue to rely on your cognitive intelligence to rationalise data stories and findings.
  2. Understand the dimensions, importance and weighting that should be applied to each of the data sources you have. Too much fuss is often made over obvious data, simply because it’s simple to access and easy to understand. Have a good think, learn from others. You can duplicate without having to replicate. You don’t want people off piste with half-truths.

  3. Think about how you could collect more granular data through better processes and how to bring this data into the mix. If you don’t collect data at the right level of granularity, the data is of limited use. Do you have gaps in your data collection processes?

  4. Ensure data insights and alerts find your leaders and teachers in their context, not the reverse. Gaining insights into data should not become a new burden or need further academic qualification. When learning data is easy to use, teachers use it.

  5. Deliver a simple teacher-driven ability to personalise inquiry and alert scenarios. Avoid building one size fits all chart strategies. Everyone must chant  ‘data must come to me’. Save everyone from being an over or underwhelmed user.

  6. Don’t get caught up re-working and transforming data, you will never stop once you start. Work and build data ‘as it is’ letting the system support the range of data diversity. Focus your time thinking about what you want to know leaving your data platform to cope with diversity.

If you are looking for a platform to transform your data silos into a single source of learning evidence, take a look at Literatu Learning Ledger and watch the simple explanatory video.        Video :  When Data met Sally

The crucial last-mile of learning ‘analytics’ delivery.

The crucial last-mile of learning ‘analytics’ delivery.

The last-mile of learning ‘analytics’ delivery.

Teachers make the biggest impact on learning when they have the right information, all the time. It’s 2018 last time I looked and this is a simple idea. Having an ‘all the time’ capability of access and insight across all teaching and learning data is what every educator wants, needs, deserves…. What are the options?

Teaching and learning data has become a critical input into school improvement programs. Knowing where more effective and efficient programs can be implemented needs clarity and speed of evidence to support teacher instincts. Getting a flexible and ‘current’ data capability into the hands of teachers remains atop of the most wanted and still elusive list for many schools. Whoops, I should have included the concept of economy as well.

Some schools have structured some of their school data into BI platforms. From what we see and hear, many of these schools are yet to deliver these ‘dashboard’ systems the last mile, that is right into the hands of every teacher in their specific teaching and learning context. Delivering the last mile is complete when teacher adoption and ownership drives the initiative. Delivering the last-mile to teachers is what we all need to focus on as well as the cost of doing so. By the way, BI is an acronym we use in a generic context rather than in reference to a product.

Many schools aligned to BI platforms have linked admin data like SIS systems that span many areas, even scheduled maintenance. As one Principal recounted, ” we have managed to build an expensive rear-view mirror that our drivers are not looking into. They actually wanted a new heads-up display.”

For people that don’t necessarily understand the ‘learning data’ conversation, they should think about how they learn and realise that every place where there’s a feedback loop likely presents opportunities to apply automated learning technology to collect and surface meaningful data. Save the innovation thought for teaching because there are now recombinant platforms that allow teachers to collect and surface meaningful data to support teaching. Literatu Learning Ledger is a great example.

Megabytes of meaningful and current learning data is found in dozens of surrounding systems like Canvas, Mathletics, Flourishing, Mathspace, Edrolo, Essential Assessment and the routine PAT series. Most of this data is not unified into a single view or BI initiative.  We have found over 30 learning and pastoral sources of data in schools, many critical if you ever wanted to look at a whole-of-student view, that simply don’t make it onto the BI radar. All of these integrations into BI would be expensive and laborious to maintain. Add a new data source and the BI data team starts again.

Personally, I think much of what BI is doing out there in schools is akin to what Powerpoint does in meetings. It makes a few points, has nice UI transitions and charts and pretty much sends everyone to sleep when the room is dim. Many teachers are conservationists at heart, saving their energy for the next big idea every time they hear the word ‘analytics’. Teachers know data is important to inform teaching and learning, they just don’t see pre-configured charts helping them improve student learning in their daily context. We do acknowledge that there is a layer of every school’s team that loves BI charts, we get that too.

Delivering data ‘the last mile’ means getting every teacher involved, cracking the ‘keep it simple’ mantra around access and personalising insights for each teacher. Value to the teacher must emerge through a whole-of-student view. The ‘last mile’ of delivery is where data has to really work for each educator.

The step up from BI, is AI where data works much harder and smarter. Do teachers see the average grade chart, (after they have just done the grading), or do they get an alert identifying where the learning gap is widening for specific skills? I think the later is their need and preference. These are the big challenges we are working hard to solve without introducing another thing to do or another system to learn. No one needs that. Teachers ask us for data that comes to them. That’s the difference we see as the one worth making.

We are on a mission to give each educator a unified whole-of-student view of engagement, performance, learning and growth in the simplest and most engaging way possible. Welcome to Learning Ledger. Ledger is alive and well and set to go for every school. We already have great data integrations that turn on with Ledger and a heap of opportunities to open more data sources along with personalised student and parent learning ledger views.

Join the Evolution!

“If data is not about improving learning and teaching in a class or student context, why are teachers looking at it?”

Mark Stanley Sept 12, 2018