5 future skills our students will need

Ken Beatty
A silhouette of several buisness people stood by a desk, in the background are skyscrapers.

Elevator to the future: English skills

“Would it be safer to take the stairs?”

The question came to mind in Montreal last week when I visited a 1929 apartment building and came face-to-face with its equally ancient caged elevator. An elderly woman shooed me inside the polished brass and oak confection and, as we ascended, confided that there was still an elevator operator when she first moved into the building.

Ah, an elevator operator – it’s a career and skill set we’ve almost forgotten. But just as hard as it is for us to imagine doing a job that only involves opening and closing doors and pressing buttons, an elevator operator from 50 years ago would find it impossible to imagine much of today’s work. And, in turn, we may not be able to imagine the jobs our students will have in the coming years. Fortunately, imagining the education that will take our students there is less difficult.

To educate today’s students, we should heed the advice of Ali ibn Abi Talib (599-661 CE): “Do not raise your children the way your parents raised you; they were born for a different time”.

Today’s students are different in five key ways: visual learning, collaboration, critical and creative thinking, digital involvement, and control of their learning.

1. Developing visual literacy

Today’s learners grew up with the rich multimedia of computers and are used to exploring ideas independently. They’re less dependent on teachers for the information they want, and often find it in surprising ways. For example, avoiding dictionary definitions and instead doing image searches to understand new words.

What you can do

Develop students’ visual literacy. Do they know the differences between bar charts, pie charts and Gantt charts? Can they interpret the data in line graphs and Venn diagrams? Can they apply what they know to present and explain ideas in dynamic ways? Expose students to a range of visual formats, from illustrations to diagrams, and give them tasks where they have to use them.

2. Encouraging collaboration

Schools were traditionally organized around competition, aimed at separating the most able students from the least able. But teachers today can’t ignore those who seem less able; we need to be more like doctors, devoting the greater part of our time and resources to those who need it most. Our aim should be to bring everyone up to the same level.

What you can do

Collaboration involves offering more tasks where students can help each other, particularly getting more able and less able students to work together to benefit from peer teaching. More able students may resist, but remind them that one who teaches learns twice.

3. Facilitating critical and creative thinking

Critical thinking has become far more important than schools’ traditional focus on memorization. Employers expect that students will become problem solvers. Gone is the factory model of employees doing repetitive jobs; those are now more efficiently and effectively done by machines.

What you can do

Traditionally, teachers have asked questions for which they know the answer and for which there is only one answer. Try to ask more open-ended questions for which there may be multiple answers. Ask questions to which you don’t know the answer. Encourage creativity. Ask students to brainstorm, and then use analytical skills to determine the best answers.

4. Leveraging the digital environment

Today’s students are digital natives. They first learned to type on digital keyboards and, since then, have embraced phones as a key resource. English writer Samuel Johnson (1709-1784) said there were two kinds of knowledge: knowing a thing or knowing where to find it. For today’s students, finding information has never been easier.

What you can do

Many teachers dread phones in the classroom, but they are powerful computers that let students connect to online learning resources and learn what they want, when, and where they want. Steer students toward using their phones to improve their English but also teach them to be reflective about the sources of the information they choose to use.

5. Offering autonomy

Today’s students are too often referred to as clients, suggesting that the teacher-student relationship is no more than a business arrangement. It’s wrong to think so but, at the same time, we recognize that today’s students are savvy about assessing what they need to learn and how they would prefer to learn it. They have grown up with ideas about multiple intelligences (Gardner, 1993).

What you can do

Open a dialog with your students to see if they have learning preferences and whether these preferences can be accommodated in the classroom. Give more individual projects letting students choose topics based on their needs and interests.

Even among elevator operators, there were those who were better or worse at their jobs. Perhaps the greatest skill for students today is a sense that they need to take responsibility and examine the needs of any task or career that interests them, and figure out how to learn the skills that will get them there.

Reference

Gardner, H. (1993). Multiple intelligences: The theory in practice. New York: Basic Books.

More blogs from app

  • Hands typing at a laptop with symbols

    Can computers really mark exams? Benefits of ELT automated assessments

    By 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.