Explaining computerized English testing in plain English

ɫèAV Languages
a pair of hands typing at a laptop

Research has shown that automated scoring can give more reliable and objective results than human examiners when evaluating a person’s mastery of English. This is because an automated scoring system is impartial, unlike humans, who can be influenced by irrelevant factors such as a test taker’s appearance or body language. Additionally, automated scoring treats regional accents equally, unlike human examiners who may favor accents they are more familiar with. Automated scoring also allows individual features of a spoken or written test question response to be analyzed independent of one another, so that a weakness in one area of language does not affect the scoring of other areas.

was created in response to the demand for a more accurate, objective, secure and relevant test of English. Our automated scoring system is a central feature of the test, and vital to ensuring the delivery of accurate, objective and relevant results – no matter who the test-taker is or where the test is taken.

Development and validation of the scoring system to ensure accuracy

PTE Academic’s automated scoring system was developed after extensive research and field testing. A prototype test was developed and administered to a sample of more than 10,000 test takers from 158 different countries, speaking 126 different native languages. This data was collected and used to train the automated scoring engines for both the written and spoken PTE Academic items.

To do this, multiple trained human markers assess each answer. Those results are used as the training material for machine learning algorithms, similar to those used by systems like Google Search or Apple’s Siri. The model makes initial guesses as to the scores each response should get, then consults the actual scores to see well how it did, adjusts itself in a few directions, then goes through the training set over and over again, adjusting and improving until it arrives at a maximally correct solution – a solution that ideally gets very close to predicting the set of human ratings.

Once trained up and performing at a high level, this model is used as a marking algorithm, able to score new responses just like human markers would. Correlations between scores given by this system and trained human markers are quite high. The standard error of measurement between ɫèAV’s system and a human rater is less than that between one human rater and another – in other words, the machine scores are more accurate than those given by a pair of human raters, because much of the bias and unreliability has been squeezed out of them. In general, you can think of a machine scoring system as one that takes the best stuff out of human ratings, then acts like an idealized human marker.

ɫèAV conducts scoring validation studies to ensure that the machine scores are consistently comparable to ratings given by skilled human raters. Here, a new set of test-taker responses (never seen by the machine) are scored by both human raters and by the automated scoring system. Research has demonstrated that the automated scoring technology underlying PTE Academic produces scores comparable to those obtained from careful human experts. This means that the automated system “acts” like a human rater when assessing test takers’ language skills, but does so with a machine's precision, consistency and objectivity.

Scoring speaking responses with ɫèAV’s Ordinate technology

The spoken portion of PTE Academic is automatically scored using ɫèAV’s Ordinate technology. Ordinate technology results from years of research in speech recognition, statistical modeling, linguistics and testing theory. The technology uses a proprietary speech processing system that is specifically designed to analyze and automatically score speech from fluent and second-language English speakers. The Ordinate scoring system collects hundreds of pieces of information from the test takers’ spoken responses in addition to just the words, such as pace, timing and rhythm, as well as the power of their voice, emphasis, intonation and accuracy of pronunciation. It is trained to recognize even somewhat mispronounced words, and quickly evaluates the content, relevance and coherence of the response. In particular, the meaning of the spoken response is evaluated, making it possible for these models to assess whether or not what was said deserves a high score.

Scoring writing responses with Intelligent Essay Assessor™ (IEA)

The written portion of PTE Academic is scored using the Intelligent Essay Assessor™ (IEA), an automated scoring tool powered by ɫèAV’s state-of-the-art Knowledge Analysis Technologies™ (KAT) engine. Based on more than 20 years of research and development, the KAT engine automatically evaluates the meaning of text, such as an essay written by a student in response to a particular prompt. The KAT engine evaluates writing as accurately as skilled human raters using a proprietary application of the mathematical approach known as Latent Semantic Analysis (LSA). LSA evaluates the meaning of language by analyzing large bodies of relevant text and their meanings. Therefore, using LSA, the KAT engine can understand the meaning of text much like a human.

What aspects of English does PTE Academic assess?

Written scoring

Spoken scoring

  • Word choice
  • Grammar and mechanics
  • Progression of ideas
  • Organization
  • Style, tone
  • Paragraph structure
  • Development, coherence
  • Point of view
  • Task completion
  • Sentence mastery
  • Content
  • Vocabulary
  • Accuracy
  • Pronunciation
  • Intonation
  • Fluency
  • Expressiveness
  • Pragmatics

More blogs from ɫèAV

  • A teacher stood helping a student in a large classroomw with other students sat working

    How do different motivations change how students learn English?

    By Steffanie Zazulak
    Reading time: 4 minutes

    Students all over the globe learn English for many reasons. Some of these motivations may come from the students themselves – perhaps they are learning because they are travelling to an English-speaking area, or they want to be able to converse with English-speaking friends and colleagues. Other reasons for learning could include meeting school requirements, studying abroad, or progressing their careers.

    As well as different reasons to learn English, there are also different goals. Many students are still focused on becoming fluent in English, and we are seeing an increase in people who want to learn the language for specific reasons. For example, immersing themselves in a particular culture or simply being able to order from a menu while travelling abroad.

    Teachers are focusing on these personal needs to help students achieve their actual goals. It’s likely you’ve already spoken to your students about why they want to learn English. Understanding this is important as different motivations can influence a student’s attitude towards learning the language – and it may be necessary for you to adapt your teaching strategies for different groups of learners.

    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.”

    A motivation like Alice’s requires strong teacher support and peer motivation woven into structured learning. Alice can set her goals and with the GSE Learning Objectives map out what she needs to do to achieve them. Teacher encouragement and personal support – and easy access to digital coursework, a social community of others all learning English, and small classes that emphasise conversation – keep people like Alice engaged and motivated to achieve her language goals. “I cannot do it without them”, she says.

    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.”

    Academic learners like Subra need to see demonstrable results to help them stay motivated and guide them to the level of English they need to achieve to get the required score on high-stakes tests. With the clear GSE Learning Objectives and a placement test, academic learners can map out where they are right now and where they need to be in order to reach their academic goals. These learners need encouragement and validation of their progress from their teachers to help keep them on track.

    Understanding student motivations will help you teach to their specific needs, thus helping them to stay focused and motivated in achieving their goals.

  • A parent and their child laying on the floor drawing together on a large peice of paper

    Raising bilingual kids: Sharing your family language at home

    By Charlotte Guest
    Reading time: 3 minutes

    A shared language is central to many families, and this can carry extra meaning when your children are growing up in a country that speaks a different language. It's not just about words; it's about culture, identity and connection. If you'd like to teach your kids the language that holds a special place in your heart, here are some tips to get you started.

  • A group of students stood around a teacher on a laptop

    The ethical challenges of AI in education

    By
    Reading time: 5 minutes

    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

    Depending on the policies in your institution, if you can use AI in the classroom with your students, they will see that you know about different AI tools and their output. A useful idea is to generate a text as a class, and have students critically analyse the AI-generated text. What do they think was done well? What could be improved? What would they have done differently?

    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

    Sometimes, students might turn to AI if they don’t know where to start with a task or lack confidence in their language abilities. With this in mind, it’s important to help your students understand where their language abilities are and what they’re working towards, with tangible evidence of learning. This is where the GSE Learning Objectives can help.

    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.