Why streaming is not the same as personalised learning
Streaming is common practice in Australia.
Streaming is common practice in Australia.
It’s all about grouping students according to their current achievement level to better target their learning needs. It allows teachers to address narrower ranges in the classroom, making it a more efficient — and on face value, effective — way to teach. This can be for specific lessons (regrouping) or as a whole class (streaming or tracking). Students get more targeted content, teachers are more efficient in their practice — everyone wins.
But they don’t, and that’s the problem.
Streaming might be commonplace, but it’s based on an assumption that research has proven is incorrect.
Grouping students according to level does not give them more targeted content and does not result in improved outcomes. A lot of the time, streaming can actually be detrimental to student growth.
There’s also no explicit approach to streaming and no policies in place to suggest it should be implemented, yet most schools are applying it in classrooms regardless.
It’s not the idea that students should be learning what they’re ready to learn that’s the problem. That’s exactly what we should be doing in our classrooms. But this should be achieved through personalised learning, not streaming. The two are very different.
If we break it down, personalised learning is achieved through good, granular data and teacher insights that inform individualised learning plans. That means that each individual student will be learning the content that they are ready for, regardless of the aged-based curriculum assigned to their year level or the levels of others in their classroom. They also learn along a continuum, building their knowledge without gaps that can prevent them from mastering new concepts later on.
Streaming on the other hand, assesses the achievement levels of each student and groups them with peers at similar levels. They access different content according to these streams, but not the content that each individual is ready for. Similarly, ‘setting’ is another popular approach that involves grouping students for specific classes, like maths or English.
The aim of both approaches is almost the same. Progress students with targeted content. But with so much research stacked against streaming, it’s time to understand why personalised learning should be the way forward.
We’ve explained how they are different in theory, but what does the research say about streaming in practice? There’s a lot of literature on the topic, but here’s what we think are the three of the biggest differences between streaming and personalised learning.
The biggest criticism of streaming is the social inequity of it. An international literature review by Johnston and Wildy (2016) found that a student’s socio-economic background is directly tied to how their academic outcomes are affected by streaming. The lower a student’s SES, the greater the negative impact is.
The students in the lower ability groups often have lower expectations placed upon them and in many cases will remain in that group, never moving up levels. Because these students are perceived to have a lower ability, they are often given less challenging tasks that are delivered in a slow step-by-step way that requires little thinking.
Research shows that this group of students will pick up on these low expectations and assume it’s a reflection of their abilities, often giving the teacher little enthusiasm or effort. The result is a cycle of low expectations, low self confidence, low excitement for the subject and little to no progress.
In a study focused on maths, students in lower groups were exposed to less content and reported more negative experiences than those in the highest ability class. This pattern was present regardless of the school, year level or gender.
In contrast, personalised learning is having the opposite effect. In 2018, the mean improvement rate for students in low SES schools using the Maths Pathway model was 2.61, compared to the still impressive improvement rate of 1.97 for learners in more privileged schools.
In other words, Maths Pathway students in disadvantaged schools are rapidly catching up, providing a clear pathway for disadvantaged students to achieve and excel.
This shows that personalised learning can have the exact effect intended. Progress for every student, regardless of SES, gender or starting level.
It’s not just the students at lower levels who are disadvantaged by streaming. On average, students who are in streaming or setting classes make slightly less progress than students who are in a mixed achievement class.
One study focused on streaming in Australian secondary schools found that overall streaming has a negative impact on the outcomes of all students, despite the level they start at.
Another study by Macqueen (2012) that focused on Australian primary school students explored the outcomes of between-class streaming by comparing the results of standardised literacy and numeracy tests of these students and those in mixed-achievement classes. There were no significant differences found between schools or classes for literacy, mathematics or writing.
Overall, both studies show that streaming is not an effective way to improve outcomes for most students. But, at Maths Pathway, personalised learning is having the opposite effect.
Students using our model are surpassing the standard growth rate of 1 year of curriculum completed in 12 months. In fact, they’re doubling the average growth Australian classes have of 0.6 years.
On average, Maths Pathway students have a growth rate of 1.25. Despite their school, gender or academic standing, these students are mastering content and making progress in maths.
Because personalised learning requires a deep understanding of the gaps and competencies of every student, teachers have real time, actionable data that provides a clear picture of what they’re ready to learn next. They can then meet students at their point of need ensuring their progress from wherever they happen to start from.
It isn’t just academic outcomes that are of concern when it comes to streaming.
One study looked at the effect of streaming on non-academic measures. It found that streaming can have a slightly positive effect on the wellbeing of students who are academically strong and a very negative effect on the wellbeing of weaker students.
Often students labelled by their peers and themselves as ‘dumb’ or ‘smart’ depending on their stream, which can really affect their confidence. For those grouped in the lower achievement classes, this can take away their chance of developing a growth mindset.
When it comes to grouping students for streaming, the assessments used often measure their current achievement level, but don’t provide more detailed data like knowledge gaps or mastery by key concept providing opportunities for remediation and extension. So students who are placed in lower groups don’t necessarily lack the ability to complete work across all strands or sub-strands, nor the capacity to problem solve, they simply lack pre-requisites to progress their understanding. But as we’ve mentioned, the lack of visibility and the misconceptions of streaming often mean they are not provided with these opportunities. Usually, these students get stuck and don’t reach their potential.
Targeting a student’s zone of proximal development through personalised learning does the opposite. Because students are learning the content they’re ready for they have the opportunity to experience growth and success in maths. For many students who have always struggled in the subject, this can be a huge turning point in developing a growth mindset and a chance to experience success. Finally they’re ‘getting’ it. They’re closing knowledge gaps that have prevented them from progressing.
It’s clear that personalised learning achieves everything that streaming tries and fails to do.
It ensures growth for students of all levels and consequently improves their learning outcomes. It is, however, important to note that personalised learning alone is not the solution.
Students should also receive timely feedback and experience peer learning, small group explicit teaching and whole-class activities such as Rich Learning tasks. Combined these practices make real change for students.
Many of us would look back at our own experiences learning maths at school and identify with some of the points above. We might have dreaded stepping into our maths classroom because we didn’t feel like a ‘maths person’.
No teacher wants their students to have that experience. We want every student to progress and achieve their potential in maths.
That’s why we need to reconsider our approach to maths teaching, including streaming in our classrooms. If personalised learning can provide better outcomes for every student, then why isn’t it in every classroom?
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