AI scoring vs human scoring for language tests: What's the difference?

Charlotte Guest
A girl sat at a desk with a laptop and notepad studying and taking notes
Reading time: 6 minutes

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.

The human touch in language proficiency testing and scoring

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.

One significant difference between human and AI scoring is how they handle context. Human scorers can understand the significance and implications of a particular word or phrase in a given context, while AI algorithms rely on predetermined rules and datasets.

The adaptability and learning capabilities of human brains contribute significantly to the effectiveness of scoring in language tests, mirroring how these brains adjust and learn from new information.

Advantages:

  • Nuanced understanding: Human scorers are adept at interpreting the complexities and nuances of language that AI might miss.
  • Contextual flexibility: Humans can consider context beyond the written or spoken word, understanding cultural and situational implications.

Disadvantages:

  • Subjectivity and inconsistency: Despite rigorous training, human-based scoring can introduce a level of subjectivity and variability, potentially affecting the fairness and reliability of scores.
  • Time and resource intensive: Human-based scoring is labor-intensive and time-consuming, often resulting in longer waiting times for results.
  • Human bias: Assessors, despite being highly trained and experienced, bring their own perspectives, preferences and preconceptions into the grading process. This can lead to variability in scoring, where two equally competent test takers might receive different scores based on the scorer's subjective judgment.

The rise of AI in language test scoring

With advancements in technology, AI-based scoring systems have started to play a significant role in language assessment. These systems utilize algorithms and natural language processing (NLP) techniques to evaluate test responses. AI scoring promises objectivity and efficiency, offering a standardized way to assess language and proficiency level.

Advantages:

  • Consistency: AI scoring systems provide a consistent scoring method, applying the same criteria across all test takers, thereby reducing the potential for bias.
  • 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

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    Setting realistic, measurable goals

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    Using the GSE Learning Objectives (LOs) in conjunction with an LLM (Large Language Model)* opens up a world of possibilities for creating focused activities at the right level for each student. Here are some key points on how this combination enhances personalized learning:

    • Individualized content: LLMs can generate targeted prompts and exercises based on the specific GSE LOs relevant to each student's proficiency level. This ensures that learners engage with content that is appropriate and aligned with their language goals.
    • Tailored language practice: By incorporating an LLM into lessons, teachers can provide students with interactive language practice that adapts to their needs. ChatGPT can simulate conversations, allowing students to apply their language skills and receive immediate feedback in a supportive environment.

    By combining the GSE LOs and harnessing the power of an LLM like ChatGPT, teachers can create personalized activities that cater to individual students' language needs, promote active learning, and foster continuous improvement.

    *Disclaimer:Teachers should check and verify the level based on their understanding of their students, as LLMs like ChatGPT may notassess levels accurately. While GSE Learning Objectives can assist, it's essential to check and adjust its outputs accordingly. This could involve consulting GSE Grammar and Vocabulary to confirm appropriate levels or utilizing the Text Analyzer to ensure the text aligns with the desired level.

    What comes next?

    Setting goals is just the start—tracking progress and adjusting those goals as needed is just as important. Throughout the year, teachers should regularly check in with students to make sure they’re on track. How can we monitor and adjust? Here are some tips.

    Teachers should schedule regular one-on-one sessions with students to review their progress. The GSE can clearly show students their progress.

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    Using the GSE can help students set clear, measurable goals and steadily progress throughout the year. By assessing where students are starting, setting specific GSE-based goals, creating personalized learning paths with AI, and continuously tracking progress, teachers can create a more dynamic and effective learning experience for their students. The new year is the perfect opportunity to help students improve their English and achieve their goals—and with these tools, teachers have everything they need to guide students toward success.

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    Learning Objectives

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    How the GSE can help teachers personalize activities

    By Leonor Corradi

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    Teaching is an art form that thrives on adaptation and personalization. When dealing with language instruction, ensuring that each student is engaged and effectively learning is of paramount importance. In my experience as a teacher, I have learned that we should always teach our students rather than the coursebook or the syllabus. I think most teachers would agree with this.

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    Utilizing the GSE in language teaching

    Let’s analyze this listening activity at A2 level for a group of adults:

    Audio script example:

    Emma: Are you working on the Media project?

    Vic: Yes. I may start working on a new project in a couple of weeks, but for now I’m writing the objectives for Media. Why?

    Emma: Well, Adam wants to see the photos for the project. He needs them for the ads.

    Vic: Oh, they’ll be ready next week. OK?

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    Vic: Well, I have to work on Saturday. We’re taking the Media pictures in the morning, but we’re just going to have fun at the beach in the afternoon.

    Emma: Nice!

    Vic: What about you? What are you doing this weekend?

    Emma: I’m going to a concert on Sunday at 3 pm.

    Vic: That sounds fun!

    Listen and write T (true) or F (false)

    1. Vic is working on a new project.

    2. Vic is working on Saturday morning.

    3. Emma is going to a concert on Sunday evening.

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    • Can identify simple information in a short video, provided that the visual supports this information and the delivery is slow and clear. (GSE 30)

    • Can identify basic factual information in short, simple dialogues or narratives on familiar everyday topics, if spoken slowly and clearly. (GSE 32)

    • Can understand the main information in short, simple dialogues about familiar activities, if spoken slowly and clearly.(GSE 33)

    • Can identify key information (e.g., places, times) from short audio recordings if spoken slowly and clearly. (GSE 33)

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