The Global Scale of English and planning: A perfect partnership

Leonor Corradi
A teacher helping a student at a table

As a teacher, I realized that planning had become an 'automatic pilot' routine from which I did not learn much. Like many others, I thought scales such as the Global Scale of English (GSE) or the Common European Framework of Reference are just that; references that are beyond the realities of their lessons.

However, I've seen that the GSE is a very powerful resource to help us at the level of planning.

If you're using a coursebook you may have noticed that, after completing one of the books in the series, students move up one level, such as from elementary to pre-intermediate or from intermediate to upper-intermediate.

We all understand what it means to be an elementary or intermediate student. These levels are usually defined in terms of structures – conditional sentences, passive voice, and tenses – Simple Past, Future Continuous, etc.

But why do students want to learn English? Using it means being able to listen or read and understand, interact with others, and communicate in writing. Even if it is parents who enroll their children in language institutes, what they want is for them to use the language. We can see a mismatch between how levels are defined and students' aims to study English.

Here's how the GSE can help English language teachers

First, you need the right scale for your group – Pre-primary, Young Learners, Adults, Professionals or Academic, which can be downloaded at:

/languages/why-pearson/the-global-scale-of-english/resources.html

Focus on your students' level. There you will see all the learning objectives that students need to achieve to complete the level at which they are and move on in their learning journey.

What are learning objectives?They are can-do statements that clearly describe what students are expected to achieve as the result of instruction. In other words, these objectives guide teachers in our planning to help students learn.

When we plan our lessons, rather than working at lesson level only, we should reflect on how the activities proposed are referenced against the learning objectives of the level. We may see that some activities need some adapting in order to focus on the selected learning outcomes.

At the level of planning as well, I also use the GSE to analyze the activities proposed in the materials I am using. Let me tell you what I do. Let's take listening, for instance. You may use the downloaded scales or the Teacher Toolkit that the GSE provides. Let's run through how this works.

Image of the GSE Teacher Toolkit

Here's the link to the Toolkit:

  • In the 'Learning Objectives' tab, choose the learner: Pre-primary, young learners, etc.
  • Then move the slides at either end of the scale so that you only work on the range you are teaching.
  • After that, select the skill you want to focus on, in this case Listening, and click on 'Show results'. You'll get a list of the LOs for listening at the selected range. You can download it as a pdf or Excel document.
  • Next, analyze the listening activity proposed in the materials used. Are the items in the activity at the right level? May the students need guidance or support? Are they required to extract information, an operation that may be beyond their level? Are there learning objectives that are not present at all?

After the analysis, I sometimes decide to add objectives, which I write on the board or will add support and guidance to the items in the activity. Occasionally, I divide the items into A and B categories, with A being at the right level and less demanding than B items.

I share this with learners and challenge them to complete some of the B items. But since they know they are more challenging, they're less likely to get frustrated if they cannot find the right answer. Also, as these tasks are more demanding, I might play the audio more often or chunk it and stop at each chunk.

You may think this is time-demanding, which is true, but it's time well invested, not wasted. On the one hand, I'm helping students reach their target level. On the other, I am tailoring all activities, personalizing them. What's not to like about this?

Since starting using the GSE myself and with groups of English teachers, I have seen improvements in students. They know what it takes to move on in their learning process and feel more responsible and committed to it. It's their decision, not mine. Another realization is that this type of reflection directly impacts my teaching methods. It makes me more reflective and focused on my students' needs and it has changed lesson planning into a learning practice.

About the author

Leonor Corradi is an English teacher based in Argentina. She is a former member of the Foreign Languages Team at the National Ministry of Education in Argentina, in charge of English and coordinator of state plurilingual schools in the City of Buenos Aires. She has extensive experience as a materials designer and coursebook writer and is an academic consultant for different educational institutions such as the British Council, and Ministries of Education in Latin America.

She has run professional development courses for teachers and has presented extensively at national and international conferences. She is the author of the Curriculum for Foreign Languages for the City of Buenos Aires (2001, English) and has been an ELTons Judge since 2014. Leonor has been a member of the Global Scale of English (GSE) Advisory Board since 2014 and is a GSE Ambassador.

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    Can computers really mark exams? Benefits of ELT automated assessments

    Por app Languages

    Automated assessment, including the use of Artificial Intelligence (AI), is one of the latest education tech solutions. It speeds up exam marking times, removes human biases, and is as accurate and at least as reliable as human examiners. As innovations go, this one is a real game-changer for teachers and students. 

    However, it has understandably been met with many questions and sometimes skepticism in the ELT community – can computers really mark speaking and writing exams accurately? 

    The answer is a resounding yes. Students from all parts of the world already take AI-graded tests.  aԻ Versanttests – for example – provide unbiased, fair and fast automated scoring for speaking and writing exams – irrespective of where the test takers live, or what their accent or gender is. 

    This article will explain the main processes involved in AI automated scoring and make the point that AI technologies are built on the foundations of consistent expert human judgments. So, let’s clear up the confusion around automated scoring and AI and look into how it can help teachers and students alike. 

    AI versus traditional automated scoring

    First of all, let’s distinguish between traditional automated scoring and AI. When we talk about automated scoring, generally, we mean scoring items that are either multiple-choice or cloze items. You may have to reorder sentences, choose from a drop-down list, insert a missing word- that sort of thing. These question types are designed to test particular skills and automated scoring ensures that they can be marked quickly and accurately every time.

    While automatically scored items like these can be used to assess receptive skills such as listening and reading comprehension, they cannot mark the productive skills of writing and speaking. Every student's response in writing and speaking items will be different, so how can computers mark them?

    This is where AI comes in. 

    We hear a lot about how AI is increasingly being used in areas where there is a need to deal with large amounts of unstructured data, effectively and 100% accurately – like in medical diagnostics, for example. In language testing, AI uses specialized computer software to grade written and oral tests. 

    How AI is used to score speaking exams

    The first step is to build an acoustic model for each language that can recognize speech and convert it into waveforms and text. While this technology used to be very unusual, most of our smartphones can do this now. 

    These acoustic models are then trained to score every single prompt or item on a test. We do this by using human expert raters to score the items first, using double marking. They score hundreds of oral responses for each item, and these ‘Standards’ are then used to train the engine. 

    Next, we validate the trained engine by feeding in many more human-marked items, and check that the machine scores are very highly correlated to the human scores. If this doesn’t happen for any item, we remove it, as it must match the standard set by human markers. We expect a correlation of between .95-.99. That means that tests will be marked between 95-99% exactly the same as human-marked samples. 

    This is incredibly high compared to the reliability of human-marked speaking tests. In essence, we use a group of highly expert human raters to train the AI engine, and then their standard is replicated time after time.  

    How AI is used to score writing exams

    Our AI writing scoring uses a technology called . LSA is a natural language processing technique that can analyze and score writing, based on the meaning behind words – and not just their superficial characteristics. 

    Similarly to our speech recognition acoustic models, we first establish a language-specific text recognition model. We feed a large amount of text into the system, and LSA uses artificial intelligence to learn the patterns of how words relate to each other and are used in, for example, the English language. 

    Once the language model has been established, we train the engine to score every written item on a test. As in speaking items, we do this by using human expert raters to score the items first, using double marking. They score many hundreds of written responses for each item, and these ‘Standards’ are then used to train the engine. We then validate the trained engine by feeding in many more human-marked items, and check that the machine scores are very highly correlated to the human scores. 

    The benchmark is always the expert human scores. If our AI system doesn’t closely match the scores given by human markers, we remove the item, as it is essential to match the standard set by human markers.

    AI’s ability to mark multiple traits 

    One of the challenges human markers face in scoring speaking and written items is assessing many traits on a single item. For example, when assessing and scoring speaking, they may need to give separate scores for content, fluency and pronunciation. 

    In written responses, markers may need to score a piece of writing for vocabulary, style and grammar. Effectively, they may need to mark every single item at least three times, maybe more. However, once we have trained the AI systems on every trait score in speaking and writing, they can then mark items on any number of traits instantaneously – and without error. 

    AI’s lack of bias

    A fundamental premise for any test is that no advantage or disadvantage should be given to any candidate. In other words, there should be no positive or negative bias. This can be very difficult to achieve in human-marked speaking and written assessments. In fact, candidates often feel they may have received a different score if someone else had heard them or read their work.

    Our AI systems eradicate the issue of bias. This is done by ensuring our speaking and writing AI systems are trained on an extensive range of human accents and writing types. 

    We don’t want perfect native-speaking accents or writing styles to train our engines. We use representative non-native samples from across the world. When we initially set up our AI systems for speaking and writing scoring, we trialed our items and trained our engines using millions of student responses. We continue to do this now as new items are developed.

    The benefits of AI automated assessment

    There is nothing wrong with hand-marking homework tests and exams. In fact, it is essential for teachers to get to know their students and provide personal feedback and advice. However, manually correcting hundreds of tests, daily or weekly, can be repetitive, time-consuming, not always reliable and takes time away from working alongside students in the classroom. The use of AI in formative and summative assessments can increase assessed practice time for students and reduce the marking load for teachers.

    Language learning takes time, lots of time to progress to high levels of proficiency. The blended use of AI can:

    • address the increasing importance of formative assessmentto drive personalized learning and diagnostic assessment feedback 

    • 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.”

    AI in formative and summative assessments will never replace the role of teachers. AI will support teachers, provide endless opportunities for students to improve, and provide a solution to slow, unreliable and often unfair high-stakes assessments.

    Examples of AI assessments in ELT

    At app, we have developed a range of assessments using AI technology.

    Versant

    The Versant tests are a great tool to help establish language proficiency benchmarks in any school, organization or business. They are specifically designed for placement tests to determine the appropriate level for the learner.

    PTE Academic

    The  is aimed at those who need to prove their level of English for a university place, a job or a visa. It uses AI to score tests and results are available within five days. 

    app English International Certificate (PEIC)

    app English International Certificate (PEIC) also uses automated assessment technology. With a two-hour test available on-demand to take at home or at school (or at a secure test center). Using a combination of advanced speech recognition and exam grading technology and the expertise of professional ELT exam markers worldwide, our patented software can measure English language ability.