With the holiday season approaching, it’s good to add some fun into teaching to keep your students engaged and motivated. We’ve created 12 simple classroom activities and tips that you can carry out with your primary class to encourage them to be good.
Can computers really mark exams? Benefits of ELT automated assessments
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. PTE Academic and Versant tests – 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.
AI versus traditional automated scoring
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.
How AI is used to score speaking exams
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.
How AI is used to score writing exams
Our AI writing scoring uses a technology called latent semantic analysis. 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.
AI’s ability to mark multiple traits
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.
AI’s lack of bias
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.
The benefits of AI automated assessment
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 assessment to 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.
Examples of AI assessments in ELT
At Pearson, 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 Pearson Test of English Academic 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.
English Benchmark is also scored using the same automated assessment technology. This test, which is taken on a tablet, is aimed at young learners and takes the form of a fun, game-like test. Covering the skills of speaking, listening, reading and writing, it measures the student’s ability and suggests follow-up activities and next teaching steps.
More blogs from Pearson
In the fast-paced world of business, there is one undeniable fact that holds true: employees are the key to success. Their commitment and expertise propel organizations towards their objectives, which is why investing in a learning culture is essential. The advantages are numerous and include improved staff retention, increased productivity and the goal of higher employee engagement.
You may have heard the term learning management system (LMS) at work or perhaps during your time in education. For many, this throws out images of clunky, outdated systems that clumsily distribute course materials and are tough to use. But that is no longer the case. Modern LMS's are far more user-friendly, and it's time to relearn what you thought you knew about these tools.
In this ultimate guide, we will look at everything you need to know about learning management systems and why they are so beneficial.
What is a learning management system?
The idea is that these LMS platforms offer one central place for users to manage and access courses and learning materials. Depending on the user, this could be anything from self-paced e-courses to classroom training.
This can help facilitate a range of training, studying and skills development, as well as assessments, exams and certification management.
Who uses LMS's and why?
There are many great uses for learning management systems but these are used primarily by businesses and educational establishments. Here are some of the most common use cases for these platforms:
HR and management - The HR and management team might implement these across the business to help with learning and development and make sure that organizational goals are being hit
Employee onboarding - Those starting a new job may be given training via an LMS; this can make the onboarding process much quicker and simpler
Compliance training - Lots of roles require compliance training, for example health and safety training, and this is a great way for businesses to stay up to date and ensure everyone complies with regulations
Customer support - Some businesses use learning management systems to onboard customers or clients. This might include sharing user manuals and product guides. Plus, sales professionals might also use them to train new partners or clients in using their services or platforms.
Classroom learning - Lecturers and teachers can create and share course materials and align content and tests from one place. These can also be used to put a twist on traditional classroom learning.
Blended learning - Schools, colleges and universities may use these for online lessons and blended learning, particularly for remote students
Volunteer training - Charities and non-profits may also use an LMS to educate volunteers and keep them motivated about the cause
Of course, these platforms can and will be used in other ways, but these are some of the most common and beneficial uses for LMS's.
Who has access to LMS's?
In most cases, learning management systems will have two primary user groups: administrators and learners.
Administrators are the people who create, manage and deliver e-learning. They may use these platforms to upload their own learning materials, or they may select courses and materials from an existing list given by the provider.
On the other hand, learners are the professionals or students who will use these platforms to train, study and gain new skills. Many modern LMS's allow multiple learners to train or access materials at the same time.
However, there is a third and final group that we have yet to mention: the parents of students using LMS's, particularly outside of school hours. In some cases, parents may have access to these systems to support students, track their progress or look at feedback from the teacher.
Key features in modern LMS's
There are a variety of learning management systems out there and some are more advanced than others. That being said, many modern platforms will share similar features to ensure they stay competitive. Some of these key features may include:
Authoring tools that allow administrators to upload or build their own courses
Access to subject matter experts who can contribute to learning and development activities
Automated workflows that allow for the creation of personalized learning journeys
A resources library that holds all relevant learning materials, such as guides, video clips and courses
Quizzes and surveys for a more fun and engaging way to assess learners
Compliance features, such as automatic reminders that notify learners when it is time to retrain
Certificates and diplomas that give learners recognition as they study and meet their targets
Insights and analysis for individual progress and results, allowing administrators to identify gaps or areas where support is needed
Compatibility with mobile devices for studying on the go
Integrations with other internal systems and software
This is by no means a complete list and different platforms will have different functionality. However, these are some of the most common and beneficial features of many modern LMSs.
The benefits of using learning management systems
Saving time and money
First and foremost, an LMS can be an excellent way for businesses to save time and money on training.
Of course there is an initial investment in the platform, but training can be expensive and time-consuming, particularly if it must take place in a location outside of the workplace. Therefore, this can be the more cost-effective solution. Not to mention, the materials are quick to access and can save time and effort.
Ensuring compliance training is completed
These platforms are an excellent way to ensure that all mandatory training is completed on time and to the highest standard. For example, industry-specific training such as fire safety or cybersecurity training.
Provide accurate data
Administrators can access data and insights into their employee's learning. This can be a great way to see where more support is needed and to identify any skills gaps that need to be filled. Similarly, teachers can get to grips with how well their students are doing and if they need extra help in any subjects or areas.
Improves the learning experience
Whether in school or the workplace, LMS's can be a great way to improve the learning process. It allows users to study and access learning materials from one accessible location. Plus, through a multimedia approach, they can use guides, videos and more to help them learn. This can ensure they engage with the materials and stay motivated.
Finally, an LMS can make communication between students, teachers, employees and employers far simpler. For example, automated reminders keep everyone in the loop and ensure all training is completed on time. But more than that, there is one central place to communicate, review feedback and access the same materials.