The role of AI in English assessment

Pearson Languages
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Digital assessment is becoming more and more widespread in recent years. But what’s the role of digital assessment in teaching today? We’d like to give you some insight into digital assessment and automated scoring.

Just a few years ago, there may have been doubts about the role of AI in English assessment and the ability of a computer to score language tests accurately. But today, thousands of teachers worldwide use automated language tests to assess their students’ language proficiency.

For example, Pearson’s suite of Versant tests have been delivering automated language assessments for nearly 25 years. And since its launch in 1996, over 350 million tests have been scored. The same technology is used in Pearson’s Benchmark and Level tests.

So what makes automated scoring systems so reliable?

Huge data sets of exam answers and results are used to train artificial intelligence machine learning technology to score English tests the same way that human markers do. This way, we’re not replacing human judgment; we’re just teaching computers to replicate it.

Of course, computers are much more efficient than humans. They don’t mind monotonous work and don’t make mistakes (the standard marking error of an AI-scored test is lower than that of a human-scored test). So we can get unbiased, accurate, and consistent scores.

The top benefits of automated scoring are speed, reliability, flexibility, and free from bias.

Speed

The main advantage computers have over humans is that they can quickly process complex information. Digital assessments can often provide an instant score turnaround. We can get accurate, reliable results within minutes. And that’s not just for multiple-choice answers but complex responses, too.

The benefit for teachers and institutions is that they can have hundreds, thousands, or tens of thousands of learners taking a test simultaneously and instantly receive a score.

The sooner you have scores, the sooner you can make decisions about placement and students’ language level or benchmark a learner’s strengths and weaknesses and make adjustments to learning that drive improvement and progress.

Flexibility

The next biggest benefit of digital assessment is flexible delivery models. This has become increasingly more important since online learning has become more prominent.

Accessibility became key: how can your institution provide access to assessment for your learners, if you can’t deliver tests on school premises?

The answer is digital assessment.

For example, Versant, our web-based test can be delivered online or offline, on-site or off-site. All test-takers need is a computer and a headset with a microphone. They can take the test anywhere, any time of day, any day of the week, making it very flexible to fit into someone's schedule or situation. 

Free from bias

Impartiality is another important benefit of AI-based scoring. The AI engine used to score digital proficiency tests is completely free from bias. It doesn’t get tired, and it doesn’t have good and bad days like human markers do. And it doesn’t have a personality.

While some human markers are more generous and others are more strict, AI is always equally fair. Thanks to this, automated scoring provides consistent, standardized scores, no matter who’s taking the test.

If you’re testing students from around the world, with different backgrounds, they will be scored solely on their level of English, in a perfectly objective way.

Additional benefits of automated scoring are security and cost.

Security

Digital assessments are more difficult to monitor than in-person tests, so security is a valid concern. One way to deal with this is remote monitoring.

Remote proctoring adds an extra layer of security, so test administrators can be confident that learners taking the test from home don’t cheat.

For example, our software captures a video of test takers, and the AI detection system automatically flags suspicious test-taker behavior. Test administrators can access the video anytime for audits and reviews, and easily find suspicious segments highlighted by our AI.

Here are a few examples of suspicious behavior that our system might flag:

Image monitoring:

  • A different face or multiple faces appearing in the frame
  • Camera blocked

Browser monitoring:

  • Navigating away from the test window or changing tabs multiple times

Video monitoring:

  • Test taker moving out of camera view
  • More than one person in the camera view
  • Looking away from the camera multiple times

Cost

Last but not least, the cost of automated English certifications are a benefit. Indeed, automated scoring can be a more cost-effective way of monitoring tests, primarily because it saves time and resources.

Pearson English proficiency assessments are highly scalable and don’t require extra time from human scorers, no matter how many test-takers you have.

Plus, there’s no need to spend time and money on training markers or purchasing equipment.

AI is helping to lead the way with efficient, accessible, fair and cost-effective English test marking/management. Given time it should develop even further, becoming even more advanced and being of even more help within the world of English language learning and assessments. 

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    When entering the world of language proficiency tests, test takers are often faced with a dilemma: Should they opt for tests scored by humans or those assessed by artificial intelligence (AI)? The choice might seem trivial at first, but understanding the differences between AI scoring and human language test scoring can significantly impact preparation strategy and, ultimately, determine test outcomes.

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    Historically, language tests have been scored by human assessors. This method leverages the nuanced understanding that humans have of language, including idiomatic expressions, cultural references, and the subtleties of tone and even writing style, akin to the capabilities of the human brain. Human scorers can appreciate the creative and original use of language, potentially rewarding test takers for flair and originality in their answers. Scorers are particularly effective at evaluating progress or achievement tests, which are designed to assess a student's language knowledge and progress after completing a particular chapter, unit, or at the end of a course, reflecting how well the language tester is performing in their language learning studies.

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    • Nuanced understanding: Human scorers are adept at interpreting the complexities and nuances of language that AI might miss.
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    Disadvantages:

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    • Speed: AI can process and score tests much faster than human scorers can, leading to quicker results turnaround.
    • Great for more nervous testers: Not everyone likes having to take a test in front of a person, so AI removes that extra stress.

    Disadvantages:

    • Lack of nuance recognition: AI may not fully understand subtle nuances, creativity, or complex structures in language the way a human scorer can.
    • Dependence on data: The effectiveness of AI scoring is heavily reliant on the data it has been trained on, which can limit its ability to interpret less common responses accurately.

    Making the choice

    When deciding between tests scored by humans or AI, consider the following factors:

    • Your strengths: If you have a creative flair and excel at expressing original thoughts, human-scored tests might appreciate your unique approach more. Conversely, if you excel in structured language use and clear, concise expression, AI-scored tests could work to your advantage.
    • Your goals: Consider why you're taking the test. Some organizations might prefer one scoring method over the other, so it's worth investigating their preferences.
    • Preparation time: If you're on a tight schedule, the quicker turnaround time of AI-scored tests might be beneficial.

    Ultimately, both scoring methods aim to measure and assess language proficiency accurately. The key is understanding how each approach aligns with your personal strengths and goals.

    The bias factor in language testing

    An often-discussed concern in both AI and human language test scoring is the issue of bias. With AI scoring, biases can be ingrained in the algorithms due to the data they are trained on, but if the system is well designed, bias can be removed and provide fairer scoring.

    Conversely speaking, human scorers, despite their best efforts to remain objective, bring their own subconscious biases to the evaluation process. These biases might be related to a test taker's accent, dialect, or even the content of their responses, which could subtly influence the scorer's perceptions and judgments. Efforts are continually made to mitigate these biases in both approaches to ensure a fair and equitable assessment for all test takers.

    Preparing for success in foreign language proficiency tests

    Regardless of the scoring method, thorough preparation remains, of course, crucial. Familiarize yourself with the test format, practice under timed conditions, and seek feedback on your performance, whether from teachers, peers, or through self-assessment tools.

    The distinctions between AI scoring and human in language tests continue to blur, with many exams now incorporating a mix of both to have students leverage their respective strengths. Understanding and interpreting written language is essential in preparing for language proficiency tests, especially for reading tests. By understanding these differences, test takers can better prepare for their exams, setting themselves up for the best possible outcome.

    Will AI replace human-marked tests?

    The question of whether AI will replace markers in language tests is complex and multifaceted. On one hand, the efficiency, consistency and scalability of AI scoring systems present a compelling case for their increased utilization. These systems can process vast numbers of tests in a fraction of the time it takes markers, providing quick feedback that is invaluable in educational settings. On the other hand, the nuanced understanding, contextual knowledge, flexibility, and ability to appreciate the subtleties of language that human markers bring to the table are qualities that AI has yet to fully replicate.

    Both AI and human-based scoring aim to accurately assess language proficiency levels, such as those defined by the Common European Framework of Reference for Languages or the Global Scale of English, where a level like C2 or 85-90 indicates that a student can understand virtually everything, master the foreign language perfectly, and potentially have superior knowledge compared to a native speaker.

    The integration of AI in language testing is less about replacement and more about complementing and enhancing the existing processes. AI can handle the objective, clear-cut aspects of language testing, freeing markers to focus on the more subjective, nuanced responses that require a human touch. This hybrid approach could lead to a more robust, efficient and fair assessment system, leveraging the strengths of both humans and AI.

    Future developments in AI technology and machine learning may narrow the gap between AI and human grading capabilities. However, the ethical considerations, such as ensuring fairness and addressing bias, along with the desire to maintain a human element in education, suggest that a balanced approach will persist. In conclusion, while AI will increasingly play a significant role in language testing, it is unlikely to completely replace markers. Instead, the future lies in finding the optimal synergy between technological advancements and human judgment to enhance the fairness, accuracy and efficiency of language proficiency assessments.

    Tests to let your language skills shine through

    Explore Pearson's innovative language testing solutions today and discover how we are blending the best of AI technology and our own expertise to offer you reliable, fair and efficient language proficiency assessments. We are committed to offering reliable and credible proficiency tests, ensuring that our certifications are recognized for job applications, university admissions, citizenship applications, and by employers worldwide. Whether you're gearing up for academic, professional, or personal success, our tests are designed to meet your diverse needs and help unlock your full potential.

    Take the next step in your language learning journey with Pearson and experience the difference that a meticulously crafted test can make.

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    Understanding dialects in the English language

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    What exactly is a regional dialect?

    At its core, a dialect is a variation of a language spoken by a particular group of people. However, the distinction between dialects and a different language can often be subjective. These variations can occur due to geographical, social class, ethnic, or historical reasons. While all speakers of a language share the same basic grammar rules and vocabulary, those speaking different dialects might use unique words and slang or have distinct pronunciations, highlighting the lack of an objective difference between dialects and languages.

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    An example of dialect variation can be seen in the Italian language, which boasts a wide range of regional dialects, showcasing linguistic diversity with multiple dialects spoken across Italy.

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    • Cultural contexts: Understanding the dialects of a language, especially regional dialects, can provide language learners with a richer cultural understanding and a more nuanced perspective of the language’s speakers. This exploration into regional dialects reveals the arbitrary distinction between 'standard' and 'nonstandard' dialects, which is often based on social, political, cultural, or historical considerations.
    • Social dynamics: Dialects can reflect social distinctions, historical migrations and contact with other languages, offering clues about social hierarchies, historical conflicts and integrations.
    • Language evolution: Studying dialects reveals how languages change over time, adapting to societies' needs, migrations and innovations.