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.
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.
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.
When deciding between tests scored by humans or AI, consider the following factors:
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.
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.
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.
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.
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English is one of the most widely-spoken languages in the world, but how much do you know about the language? Here are 11 facts about Englishthat you might not know.
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.
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.
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.
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.
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.
Kirsty Murray taught English for a year at a collège (the French equivalent of a secondary school) in Villers-Cotterêts: a town in the north of France known for being the birthplace of Alexandre Dumas. She taught mixed-ability groups of 11- to 16-year-olds, with classes ranging in size from 10 to 35 students. Here, she shares the five lessons she learned from the experience.
