What is rapid prototyping and how can it apply to the ELT classroom?

Nicole Kyriacou
A teacher stood in front of her class with her students raising their hands
Reading time: 5 minutes

Tom Chi is an internet veteran with quite a resumé. His roles have been many and varied – from astrophysical researcher to Fortune 500 consultant and corporate executive, developing new hardware and software products and services.

He worked on Microsoft Outlook when it was in its infancy, was a major influence in taking Yahoo Search from 0 to 90 million users and is now Head of Product Experience at Google X – Alphabet’s secretive division focused on creating technological innovations for the future. It has produced the self-driving car and Google Glass, and its Project Loon aims to provide internet to every square inch of the earth.

At Google X, Tom was in a unique position – always having to think five, ten or even more years ahead in order to conceptualize and build the technology of the future. As you might imagine, this is far from an easy task; not only do the ideas have to be original, but they have to meet people’s future needs – something that is not easy to predict.

So, how does Tom and the others at Google X deliver their vision for the future using today's materials and technology?

That’s where Rapid Prototyping comes in. It’s a concept that allows teams to experiment, learn and adjust prototypes quickly and cheaply, so that projects (and products) get off the ground. Failure is seen as a starting block and an inevitable part of the learning process. Following his workshop, we are going to look further at rapid prototyping and how it can relate to the ELT classroom.

Integrating rapid prototyping into ELT teaching
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What are the rules of rapid prototyping?

According to Tom, rapid prototyping follows four main principles:

Rule #1:

You must find the quickest path to experience. Ideas are nothing until they have been tested; prototyping is the quickest path to go from guessing into direct experience. You will soon see an idea’s strengths, weaknesses and potential once you have tried it.

Rule #2:

Doing is the best kind of thinking. People are very good at imagining things, but until we try them, we won’t know what works and what doesn’t. By actually doing something, we’ll come up with new ideas, new challenges and new solutions.

Rule #3:

Prototyping follows a distinct pathway: from conjecture, to experimentation, to results and finally decision-making.

Prototyping rule #4:

Prototyping helps us reason in time and space: instead of lots of planning, imagination and guesswork, it makes us build something real, considering real use cases and real situations.

How does rapid prototyping affect progress?

The rapid-prototyping learning loop follows this pattern:

  1. Building a variation
  2. Testing with customers
  3. Observing results
  4. Adjusting from results

This process allows us to increase the chances of success in any given project dramatically. For example, if an idea has a 5% chance of success, by trying it 20 times there is a 64% chance of success and by trying it 50 times, there is a 92% chance of success.

Considering that each time an idea is prototyped, learning takes place, the chances of success are likely even higher with every trial.

But wait, what has rapid prototyping got to do with the ELT classroom?

Tom shows how a technology giant like Google can innovate and produce results quickly and efficiently through rapid prototyping – and all the while, he is explaining how much faster learning is when we experiment and do things.

Encouraging project-based work

Of course, our students are not innovating or building new products for tech companies, they are aiming to learn a language. But as Tom said, learning by doing is much faster and more effective than simply conjecturing and talking about theories.

Following his first rule of prototyping (find the quickest path to experience), we need to give students the experience of using the language as fast as possible. Project and task-based learning allows students to build their vocabulary, and test their grammar and overall communications skills in an authentic way.

This also covers Tom’s second rule (doing is the best type of thinking). If we can tap into our students’ creativity, we can allow them to experiment with language, discover what they know and what they don’t know, and then really work on learning the things they need for certain tasks.

When it comes to Tom’s third rule (conjecture, experimentation, results, decision-making), the teacher has more responsibility. We need to look at how we benchmark, measure and analyze our learner’s progress. Without a pathway, our students will not know how they are progressing and may easily lose motivation. The students therefore need to have a firm idea of their abilities, when they need to learn and how they are currently performing. We can then make decisions regarding individual class plans and syllabi.

Finally, by exposing our students to authentic materials, we cover Tom’s fourth rule (reason in time and space). Authentic readings, listenings and videos give learners the opportunity to work with real-world language, trying out what they are learning in authentic contexts. It helps them imagine using the language outside of the safe environment of the classroom too, giving them the challenge they need to push them into learning faster.

Fostering a growth mindset

The very fact that Tom’s team is able to imagine and prototype what seem like impossible ideas – that then have the potential to change the world – is awe-inspiring.

We can all learn from his vision, tenacity and methodology. At the heart of the experimentation and learning at Google X lies a growth mindset.

If we help our students develop a growth mindset, they will see failure as an opportunity to learn, as well as a challenge as a chance to grow, and feedback as a constructive way to improve.

Learning is a dynamic process. As teachers, it’s important for us to look outside the world of education to find inspiration and ideas. We hope this has sparked your curiosity and added a dash of inspiration for your future classes.

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    Teaching English to different groups of learners

    Let’s meet some different groups of students, learn a little more about their motivations and explore whether different motivations alter how students learn English. You may recognise some of these learners in your classes.

    1. Adult learners

    These students are learning English for pleasure or personal reasons. It might be because of travel, social or family reasons or perhaps because a better grasp of English might assist them with their careers. There are also adult learners who could be learning English as an immigration requirement.

    For example, 23-year-old Alice decided to learn English so she could meet people and have more meaningful interactions with her English-speaking neighbours. She says: “I was very shy and not very confident in speaking to people, but learning English helped me connect with others and meet new people. I have changed a lot.”

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    2. Professional learners

    These learners are typically in a more formal type of English programme and are learning the language to achieve specific career milestones, such as a promotion. Their employer might even be paying for their learning or they might be reimbursed for the cost of their lessons.

    Vincenzo is 33 and works as a Product Manager in Milan for an international organization with offices around the world. He says: “I asked to take English classes as part of my professional development. My company chose an English provider and gave me a choice of group or one-to-one classes. I chose one-to-one classes as I’m easily distracted.”

    Professional learners like Vincenzo succeed using a blended learning model of learning in class and at home that they can tailor around their lives. They have a strong motivation to succeed – that’s why learning at home works for them – but step-by-step progress provided by the GSE Learning Objectives is also important to keep this motivation alive. “I met with my teacher once a week where we would work on mistakes I would make while speaking English. He would also give me extra practice materials, like interesting games and videos to listen to in my own time, to help me really get a better understanding of the language,” Vincenzo says.

    3. Academic learners

    Learning English is a requirement for many school programmes and students will continue this at college or university. Many of these students will be learning English with a formal course that offers practice tests for high-stakes exams.

    Seventeen-year-old Subra is from Malaysia and learns English at school. Some of her family live in Australia and she is considering studying abroad to attend a University that specializes in health care. When she was young, she learned in a traditional classroom backed with tests that helped her see how she was progressing. Now she uses technology, such as her Android Huawei phone to practise her English but still needs the validation of regular testing to know she is on track.

    Subrasays: “I am used to studying for tests as I prepared hard for exams to get into middle school and senior school, which was totally determined by test results.”

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    AI is revolutionising every industry, and language learning is no exception. AI tools can provide students with unprecedented access to things like real-time feedback, instant translation and AI-generated texts, to name but a few.

    AI can be highly beneficial to language education by enhancing our students’ process of learning, rather than simply being used by students to ‘demonstrate’ a product of learning. However, this is easier said than done, and given that AI is an innovative tool in the classroom, it is crucial that educators help students to maintain authenticity in their work and prevent AI-assisted ‘cheating’. With this in mind, striking a balance between AI integration and academic integrity is critical.

    How AI impacts language learning

    Generative AI tools such as ChatGPT and Gemini have made it easier than ever for students to refine and develop their writing. However, these tools also raise concerns about whether submitted texts are student-produced, and if so, to what extent. If students rely on text generation tools instead of their own skills, our understanding of our students’ abilities may not reflect their true proficiency.

    Another issue is that if students continue to use AI for a skill they are capable of doing on their own, they’re likely to eventually lose that skill or become significantly worse at it.

    These points create a significant ethical dilemma:

    • How does AI support learning, or does it (have the potential to) replace the learning process?
    • How can educators differentiate between genuine student ability and AI-assisted responses?

    AI-integration strategies

    There are many ways in which educators can integrate AI responsibly, while encouraging our learners to do so too.

    1.Redesign tasks to make them more ‘AI-resistant’

    No task can be completely ‘AI-resistant’, but there are ways in which teachers can adapt coursebook tasks or take inspiration from activities in order to make them less susceptible to being completed using AI.

    For example:

    • Adapt writing tasks to be hyperlocal or context-specific. Generative AI is less likely to be able to generate texts that are context-bound. Focus on local issues and developments, as well as school or classroom-related topics. A great example is having students write a report on current facilities in their classroom and suggestions for improving the learning environment.
    • Focus on the process of writing rather than the final product. Have students use mind maps to make plans for their writing, have them highlight notes from this that they use in their text and then reflect on the steps they took once they’ve written their piece.
    • Use multimodal learning. Begin a writing task with a class survey, debate or discussion, then have students write up their findings into a report, essay, article or other task type.
    • Design tasks with skill-building at the core. Have students use their critical thinking skills to analyse what AI produces, creatively adapt its output and problem solve by fact-checking AI-generated text.

    2.Use AI so that students understand you know how to use it

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    You can also discuss the ethical implications of AI in education (and other industries) with your students, to understand their view on it and better see in what situations they might see AI as a help or a hindrance.

    3.Use the GSE Learning Objectives to build confidence in language abilities

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    The Global Scale of English (GSE) provides detailed, skill-specific objectives at every proficiency level, from 10 to 90. These can be used to break down complex skills into achievable steps, allowing students to see exactly what they need to do to improve their language abilities at a granular level.

    • Start by sharing the GSE Learning Objectives with students at the start of class to ensure they know what the expectations and language goals are for the lesson. At the end of the lesson, you can then have students reflect on their learning and find evidence of their achievement through their in-class work and what they’ve produced or demonstrated.
    • Set short-term GSE Learning Objectives for the four key skills – speaking, listening, reading and writing. That way, students will know what they’re working towards and have a clear idea of their language progression.