Our Research & Development
Researched by Professor Ted Briscoe’s team in Cambridge University’s Computer Laboratory, productised by iLexIR Ltd and then delivered to learners world-wide by ELiT, with input and support from leading English language organisations Cambridge Assessment English and Cambridge University Press, Write & Improve is a new kind of tool that uses natural language processing and machine learning to assess and give guidance on text it has never seen before, and to do this indistinguishably from a human examiner.
Imagine a learner was able to submit a few paragraphs of text online and, in a matter of seconds, receive an accurate grade, sentence-by-sentence feedback on its linguistic quality and useful suggestions for improvement. Imagine too that with that feedback there is motivation to try to work out how to improve the writing, rewards for progress and the opportunity to share your improvement.
This is Cambridge English Write & Improve – an online learning system, or ‘computer tutor’, to help English language learners – and it’s built on information from almost 65 million words of written English gathered over a 20-year period from essays written by real exam candidates swith 148 different mother-tongues, living in 217 different countries or territories. Each essay has been transcribed and information gathered about the learner’s age, language and grade achieved. Crucially, errors (grammar, spelling, incorrect word sequences, and so on) have been annotated so that a computer can process the natural language used by the learner. This has then been refined with nearly two million new essays which have been submitted since Write & Improve launched – and so the automated assessment engine continues to learn and improve.
“About a billion people worldwide are studying English as a further language, with a projected peak in 2050 of about two billion,” says Briscoe. “There are 300 million people actively preparing for English exams at any one time. All of them will need multiple tests during this learning process.” Language testing affects the lives of millions of people every year; a successful test result could open the door to jobs, further education and even countries.
“Imagine that a such a tool can replace one of the most routine and time-consuming tasks a teacher faces. Automating the process and still delivering individual feedback makes sense. Humans are good teachers because they show understanding of people’s problems, but machines are good at dealing with routine things and large amounts of data, seeing patterns, and giving feedback that the teacher or the learner can use. These tools can free up the teacher’s time to focus on actual teaching.”