Week #28 Data to Drive Learning Design

𝗗𝗮𝘁𝗮 to 𝗗𝗿𝗶𝘃𝗲 Learning 𝗗𝗲𝘀𝗶𝗴𝗻: 𝗛𝗼𝘄 𝗘𝘃𝗶𝗱𝗲𝗻𝗰𝗲 𝗜𝗺𝗽𝗿𝗼𝘃𝗲𝘀 𝗜𝗻𝘀𝘁𝗿𝘂𝗰𝘁𝗶𝗼𝗻

Impactful instruction and powerful learning is not guesswork. Nowhere is this more powerfully realised than in the purposeful use of data to inform practice.

But “data” doesn’t just mean numbers. It means insight. And it only matters if it changes what we do.

𝗪𝗵𝗮𝘁 𝗗𝗮𝘁𝗮 𝗧𝗲𝗹𝗹𝘀 𝗨𝘀

Data helps us move beyond assumption. An athlete, pupil, or colleague may “seem engaged” in discussion, but objective evidence via quizzing or deeper processing questioning identifies gaps in knowledge and application.

From the work of Evidence Based Education and the Education Endowment Foundation, we know that effective use of data:

— Surfaces misconceptions early, so they can be addressed before they create encoded memories which are false.

— Identifies learning gaps, helping us target instruction.

— Informs feedback so that it moves from general to specific and individualised to a player, unit (midfielders), in or out-of-possession.

Whether it's assessment data, observational trends, or even well-structured learner voice, data must become an active player in learning design.

𝗘𝘃𝗶𝗱𝗲𝗻𝗰𝗲 𝗶𝗻 𝗔𝗰𝘁𝗶𝗼𝗻

The EEF’s guidance on assessment is clear: data is only useful when it is valid, reliable, and acted upon. It is about collecting regular and useful data to objectively assess quality and application of learning over time.

InnerDrive also reminds us through their work on metacognition that self-assessment data, when correctly applied and modelled by the coach or teacher/instructor, offers powerful insight into how learners see their progress and plan their next steps.

And Evidence Based Education’s ‘Assessment Lead Programme’ has shown that high-quality assessment design supports instructors to make inferences about learning that are more trustworthy and more timely to enhance learning.

In short: good data leads to good decisions.

𝗖𝗿𝗮𝗳𝘁𝗲𝗱 𝗜𝗻𝘁𝗲𝗻𝘁𝗶𝗼𝗻: 𝗗𝗲𝘀𝗶𝗴𝗻𝗶𝗻𝗴 𝗙𝗿𝗼𝗺 𝗜𝗻𝘀𝗶𝗴𝗵𝘁

We don't gather data for its own sake. We gather it so that it shapes what happens next.

A Crafted coach, instructor, teacher builds instructional decisions from a foundation of informed clarity:

— They notice patterns from formative assessment to adjust pace and pitch in real time.

— They reflect on retrieval data to refine what needs more practice and spacing.

— They draw from student reflections to align task design with cognitive load and prior knowledge.

This isn’t about chasing spreadsheets. It’s about learning design around what learners actually need.

𝗪𝗲 𝗗𝗼𝗻’𝘁 𝗠𝗲𝗮𝘀𝘂𝗿𝗲 𝘁𝗼 𝗟𝗮𝗯𝗲𝗹. 𝗪𝗲 𝗠𝗲𝗮𝘀𝘂𝗿𝗲 𝘁𝗼 𝗟𝗲𝗮𝗿𝗻.

We need to flip the script. Data should not come at the end of the process. It should shape the everyday learning design of coaches and learning leaders.

🔎 Diagnostic – What do my learners actually understand?

🎯 Formative – What’s working, and where do we need to go next?

When data leads to adjusted action, that’s when it earns its place.

𝗜𝗻 𝗣𝗿𝗮𝗰𝘁𝗶𝗰𝗲

On the training pitch:
A coach tracks decision-making errors from match footage. Rather than repeating drills, the team re-runs the same game with added constraints, discussing tactical choices during the session to connect autonomy and choice to the task. Video feedback is paired with player reflections, activating insight learning.

In the classroom:
A teacher reviews low-stakes quiz results after a science topic. 70% of students miss a question on the functions of the skeleton. Instead of moving on, she re-teaches the concept using a different model, then builds it into the next two retrieval activities to strengthen schema and recall. That’s data driving instruction.

Let’s take greater care to tangibly demonstrate what we know. Then, l𝘦𝘵’𝘴 𝘥𝘰 𝘮𝘰𝘳𝘦 𝘸𝘪𝘵𝘩 𝘸𝘩𝘢𝘵 𝘸𝘦 𝘬𝘯𝘰𝘸.