Automated assessment, including the use of Artificial Intelligence (AI), is one of the latest education tech solutions. It speeds up exam marking times, removes human biases, and is as accurate and at least as reliable as human examiners. As innovations go, this one is a real game-changer for teachers and students.
However, it has understandably been met with many questions and sometimes skepticism in the ELT community – can computers really mark speaking and writing exams accurately?
The answer is a resounding yes. Students from all parts of the world already take AI-graded tests. aԻ Versanttests – for example – provide unbiased, fair and fast automated scoring for speaking and writing exams – irrespective of where the test takers live, or what their accent or gender is.
This article will explain the main processes involved in AI automated scoring and make the point that AI technologies are built on the foundations of consistent expert human judgments. So, let’s clear up the confusion around automated scoring and AI and look into how it can help teachers and students alike.
First of all, let’s distinguish between traditional automated scoring and AI. When we talk about automated scoring, generally, we mean scoring items that are either multiple-choice or cloze items. You may have to reorder sentences, choose from a drop-down list, insert a missing word- that sort of thing. These question types are designed to test particular skills and automated scoring ensures that they can be marked quickly and accurately every time.
While automatically scored items like these can be used to assess receptive skills such as listening and reading comprehension, they cannot mark the productive skills of writing and speaking. Every student's response in writing and speaking items will be different, so how can computers mark them?
This is where AI comes in.
We hear a lot about how AI is increasingly being used in areas where there is a need to deal with large amounts of unstructured data, effectively and 100% accurately – like in medical diagnostics, for example. In language testing, AI uses specialized computer software to grade written and oral tests.
The first step is to build an acoustic model for each language that can recognize speech and convert it into waveforms and text. While this technology used to be very unusual, most of our smartphones can do this now.
These acoustic models are then trained to score every single prompt or item on a test. We do this by using human expert raters to score the items first, using double marking. They score hundreds of oral responses for each item, and these ‘Standards’ are then used to train the engine.
Next, we validate the trained engine by feeding in many more human-marked items, and check that the machine scores are very highly correlated to the human scores. If this doesn’t happen for any item, we remove it, as it must match the standard set by human markers. We expect a correlation of between .95-.99. That means that tests will be marked between 95-99% exactly the same as human-marked samples.
This is incredibly high compared to the reliability of human-marked speaking tests. In essence, we use a group of highly expert human raters to train the AI engine, and then their standard is replicated time after time.
Our AI writing scoring uses a technology called . LSA is a natural language processing technique that can analyze and score writing, based on the meaning behind words – and not just their superficial characteristics.
Similarly to our speech recognition acoustic models, we first establish a language-specific text recognition model. We feed a large amount of text into the system, and LSA uses artificial intelligence to learn the patterns of how words relate to each other and are used in, for example, the English language.
Once the language model has been established, we train the engine to score every written item on a test. As in speaking items, we do this by using human expert raters to score the items first, using double marking. They score many hundreds of written responses for each item, and these ‘Standards’ are then used to train the engine. We then validate the trained engine by feeding in many more human-marked items, and check that the machine scores are very highly correlated to the human scores.
The benchmark is always the expert human scores. If our AI system doesn’t closely match the scores given by human markers, we remove the item, as it is essential to match the standard set by human markers.
One of the challenges human markers face in scoring speaking and written items is assessing many traits on a single item. For example, when assessing and scoring speaking, they may need to give separate scores for content, fluency and pronunciation.
In written responses, markers may need to score a piece of writing for vocabulary, style and grammar. Effectively, they may need to mark every single item at least three times, maybe more. However, once we have trained the AI systems on every trait score in speaking and writing, they can then mark items on any number of traits instantaneously – and without error.
A fundamental premise for any test is that no advantage or disadvantage should be given to any candidate. In other words, there should be no positive or negative bias. This can be very difficult to achieve in human-marked speaking and written assessments. In fact, candidates often feel they may have received a different score if someone else had heard them or read their work.
Our AI systems eradicate the issue of bias. This is done by ensuring our speaking and writing AI systems are trained on an extensive range of human accents and writing types.
We don’t want perfect native-speaking accents or writing styles to train our engines. We use representative non-native samples from across the world. When we initially set up our AI systems for speaking and writing scoring, we trialed our items and trained our engines using millions of student responses. We continue to do this now as new items are developed.
There is nothing wrong with hand-marking homework tests and exams. In fact, it is essential for teachers to get to know their students and provide personal feedback and advice. However, manually correcting hundreds of tests, daily or weekly, can be repetitive, time-consuming, not always reliable and takes time away from working alongside students in the classroom. The use of AI in formative and summative assessments can increase assessed practice time for students and reduce the marking load for teachers.
Language learning takes time, lots of time to progress to high levels of proficiency. The blended use of AI can:
address the increasing importance of formative assessmentto drive personalized learning and diagnostic assessment feedback
allow students to practice and get instant feedback inside and outside of allocated teaching time
address the issue of teacher workload
create a virtuous combination between humans and machines, taking advantage of what humans do best and what machines do best.
provide fair, fast and unbiased summative assessment scores in high-stakes testing.
We hope this article has answered a few burning questions about how AI is used to assess speaking and writing in our language tests. An interesting quote from Fei-Fei Li, Chief scientist at Google and Stanford Professor describes AI like this:
“I often tell my students not to be misled by the name ‘artificial intelligence’ — there is nothing artificial about it; A.I. is made by humans, intended to behave [like] humans and, ultimately, to impact human lives and human society.”
AI in formative and summative assessments will never replace the role of teachers. AI will support teachers, provide endless opportunities for students to improve, and provide a solution to slow, unreliable and often unfair high-stakes assessments.
At app, we have developed a range of assessments using AI technology.
The Versant tests are a great tool to help establish language proficiency benchmarks in any school, organization or business. They are specifically designed for placement tests to determine the appropriate level for the learner.
The is aimed at those who need to prove their level of English for a university place, a job or a visa. It uses AI to score tests and results are available within five days.
app English International Certificate (PEIC) also uses automated assessment technology. With a two-hour test available on-demand to take at home or at school (or at a secure test center). Using a combination of advanced speech recognition and exam grading technology and the expertise of professional ELT exam markers worldwide, our patented software can measure English language ability.
Read more about the use of AI in our learning and testing here, or if you're wondering which English test is right for your students make sure to check out our post 'Which exam is right for my students?'.
Learning English with music can enhance learning and create a more engaging and dynamic classroom environment. In a previous post, we discussed if music can help you learn a language; this post looks at how music can be incorporated into the classroom.
Using music in your classroom can help improve student motivation, focus, and retention of information. Here are some ways you can use music to enhance your classroom teaching:
Have you considered studying abroad? Moving to Canada to study? With more than 100 world-class universities across the country, there’s good reason to. From coast to coast to coast, it offers many international students a safe and supportive learning environment and the opportunity to work after graduation.
Want to learn more? In this guide, we cover ten things you should know about studying in Canada:
Workplaces are becoming more and more diverse, with employees hailing from various cultures and speaking different languages. This diversity bringsvaluable enrichmentbut can also bring communication and collaboration challenges.
That's why corporate language training is crucial. It bridges cultural divides, promotes understanding, and creates a harmonious work environment.Cultural divides in the workplace can arise from various factors, including language barriers. When diverse employees can't communicate effectively, misunderstandings and decreased productivity can occur.
Corporate language training plays a vital role in addressing this issue. It helps employees understand and appreciate different cultures, fostering unity and respect. Language training acts as a catalyst for positive workplace dynamics, driving businesses towards global goals.
Corporate language training greatly enhances communication, benefiting employees' expression of ideas and fostering understanding among team members.
Breaking down linguistic barriers promotes mutual respect, unity, and effective collaboration. It also prevents misunderstandings that may lead to conflicts, improving the overall workplace environment and fostering innovative ideas through successful teamwork.
Corporate language training plays a key role in fostering an inclusive and diverse atmosphere. Learning a new language provides insights into different cultures, promoting a deeper appreciation for diversity and reducing biases. This creates a more inclusive work environment where employees from diverse backgrounds feel understood and valued, fostering a sense of belonging and unity.
Language training also equips employees to engage with global customers and clients, reflecting the company's commitment to diversity. Corporate language training is instrumental in cultivating inclusion and diversity, enhancing corporate culture.
Corporate language training strengthens global business relations. As businesses expand worldwide, employees will interact face-to-face with diverse linguistic backgrounds. Knowledge of another language shows respect for other cultures, which is crucial for trust in business relationships.
The ability to connect across cultures is a game-changer for businesses, helping them build strong international relations. Investing in corporate language training not only benefits employees but also secures a company's global future.
A common language fosters seamless communication, enabling effective collaboration. It cultivates a coherent team dynamic where ideas flow and tasks are executed efficiently. This linguistic unity significantly boosts team performance. Reduced misunderstandings lead to increased productivity. Read our post on performance management for language learning in the workplace.
As the employees learn and gain confidence in their language skills, they engage, contribute, and excel, driving the team and the business forward.
If done correctly, corporate language training improves employee engagement and retention. Investing in employees' personal and professional development fosters a sense of value and belonging. Learning to speak a new language is challenging yet rewarding, promoting personal growth and cognitive skills.
Language training also brings employees together, fostering teamwork and unity. This increased engagement leads to higher job satisfaction, loyalty, and reduced turnover. Corporate language training is a strategic investment in employee engagement and retention, a key feature bridging linguistic divides in the modern corporate arena.
A competitive edge is crucial for business growth in today's global economy. Corporate language training contributes significantly to this edge, especially in global markets. Proficiency in multiple languages enables businesses to easily enter new markets, communicate effectively and build trust. Employees with language training represent their companies internationally, exhibiting cultural sensitivity.
Companies showcasing expertise, language proficiency, expertise and cultural understanding stand out, reflecting a global-minded ethos. Corporate language training enhances a corporation or company's presence, reputation, and success in the global market.
To implement effective corporate language training, organizations should assess how employees learn languages and current language proficiencies and identify gaps. A skills audit can assist in identifying areas requiring training, taking into account the languages spoken within the company and the skill levels necessary for business strategies.
Moreover, it allows for assessing employees' proficiency in various languages, encompassing written, spoken, and cultural understanding. This proactive approach ensures tailored and valuable language training for the organization and its employees, promoting skill development at all levels.
Understanding cultural nuances is crucial in corporate language training courses. It's not just about learning to speak the language but also grasping the cultural contexts. This includes knowing the etiquettes, conventions, and unspoken rules governing social interactions across cultures. Being mindful of these subtleties prevents misunderstandings, fosters better relationships, and facilitates smoother communication.
Effective corporate language training should include cultural education to equip employees with the cultural insights and skills to confidently navigate these complexities.
Aligning language training with business objectives is a strategic move that ensures relevant, effective, and valuable training.
In an international business context, objectives may include expanding into new markets, improving multilingual customer service, enhancing internal communication among a diverse workforce, or forming alliances with foreign partners.
By defining these objectives, corporations can tailor language learning programs to specific needs, maximizing ROI. For example, if a company aims to enter a new market with a dominant language, the training could focus on equipping employees with linguistic and cultural skills to communicate effectively with potential clients or partners. This alignment ensures successful training implementation and achievement of broader business goals.
