Does progress in English slow as you get more advanced?

Ian Wood
A young woman sat in a library with headphones around her neck reading a book
Reading time: 4 minutes

Why does progression seem to slow down as an English learner moves from beginner to more advanced skills?

The journey of learning English

When presenting at ELT conferences, I often ask the audience – typically teachers and school administrators – “When you left home today, to start your journey here, did you know where you were going?” The audience invariably responds with a laugh and says yes, of course. I then ask, “Did you know roughly when you would arrive at your destination?” Again the answer is, of course, yes. “But what about your students on their English learning journey? Can they say the same?” At this point, the laughter stops.

All too often English learners find themselves without a clear picture of the journey they are embarking on and the steps they will need to take to achieve their goals. We all share a fundamental need for orientation, and in a world of mobile phone GPS we take it for granted. Questions such as: Where am I? Where am I going? When will I get there? are answered instantly at the touch of a screen. If you’re driving along a motorway, you get a mileage sign every three miles.

When they stop appearing regularly we soon feel uneasy. How often do English language learners see mileage signs counting down to their learning goal? Do they even have a specific goal?

Am I there yet?

The key thing about GPS is that it’s very precise. You can see your start point, where you are heading and tell, to the mile or kilometer, how long your journey will be. You can also get an estimated time of arrival to the minute. As Mike Mayor mentioned in his post about what it means to be fluent, the same can’t be said for understanding and measuring English proficiency. For several decades, the ELL industry got by with the terms ‘beginner’, ‘elementary’, ‘pre-intermediate’ and ‘advanced’ – even though there was no definition of what they meant, where they started and where they ended.

The CEFR has become widely accepted as a measure of English proficiency, bringing an element of shared understanding of what it means to be at a particular level in English. However, the wide bands that make up the CEFR can result in a situation where learners start a course of study as B1 and, when they end the course, they are still within the B1 band. That doesn’t necessarily mean that their English skills haven’t improved – they might have developed substantially – but it’s just that the measurement system isn’t granular enough to pick up these improvements in proficiency.

So here’s the first weakness in our English language GPS and one that’s well on the way to being remedied with the Global Scale of English (GSE). Because the GSE measures proficiency on a 10-90 scale across each of the four skills, students using assessment tools reporting on the GSE are able to see incremental progress in their skills even within a CEFR level. So we have the map for an English language GPS to be able to track location and plot the journey to the end goal.

‘The intermediate plateau’

When it comes to pinpointing how long it’s going to take to reach that goal, we need to factor in the fact that the amount of effort it takes to improve your English increases as you become more proficient. Although the bands in the CEFR are approximately the same width, the law of diminishing returns means that the better your English is to begin with, the harder it is to make further progress – and the harder it is to feel that progress is being made.

That’s why many an English language-learning journey gets abandoned on the intermediate plateau. With no sense of progression or a tangible, achievable goal on the horizon, the learner can become disoriented and demoralised.

To draw another travel analogy, when you climb 100 meters up a mountain at 5,000 meters above sea level the effort required is greater than when you climb 100 meters of gentle slope down in the foothills. It’s exactly the same 100 meter distance, it’s just that those hundred 100 meters require progressively more effort the higher up you are, and the steeper the slope. So, how do we keep learners motivated as they pass through the intermediate plateau?

Education, effort and motivation

We have a number of tools available to keep learners on track as they start to experience the law of diminishing returns. We can show every bit of progress they are making using tools that capture incremental improvements in ability. We can also provide new content that challenges the learner in a way that’s realistic.

Setting unrealistic expectations and promising outcomes that aren’t deliverable is hugely demotivating for the learner. It also has a negative impact on teachers – it’s hard to feel job satisfaction when your students are feeling increasingly frustrated by their apparent lack of progress.

Big data is providing a growing bank of information. In the long term this will deliver a much more precise estimate of effort required to reach higher levels of proficiency, even down to a recommendation of the hours required to go from A to B and how those hours are best invested. That way, learners and teachers alike would be able to see where they are now, where they want to be and a path to get there. It’s a fully functioning English language learning GPS system, if you like.

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    • In your right hand, write what you do when you feel frustrated.
    • In your right foot, write your favorite song.
    • In your left leg, write the name of the person you get good advice from.
    • In your right arm, write what makes you happy.
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    • allow students to practice and get instant feedback inside and outside of allocated teaching time

    • address the issue of teacher workload

    • create a virtuous combination between humans and machines, taking advantage of what humans do best and what machines do best. 

    • provide fair, fast and unbiased summative assessment scores in high-stakes testing.

    We hope this article has answered a few burning questions about how AI is used to assess speaking and writing in our language tests. An interesting quote from Fei-Fei Li, Chief scientist at Google and Stanford Professor describes AI like this:

    “I often tell my students not to be misled by the name ‘artificial intelligence’ — there is nothing artificial about it; A.I. is made by humans, intended to behave [like] humans and, ultimately, to impact human lives and human society.”

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