Today was the fourth day of ALTA’s Machine Learning for ELT Summer School in Crete and we focused on psychometric testing for the first part of the day and then vocabulary acquisition later in the afternoon. As with other days, this summary is the information as I understood it. I welcome all corrections, clarifications and comments.
This week ELTjam are at the ALTA Machine Learning Summer School in Crete and you can read regular updates of what’s happening here on the blog. Today, Day 3, we had an insight into the human element to the Write & Improve product, both in terms of the annotation done to the the text by human annotators, and the insights that teachers can get into their learners’ progress. This post is a summary of the day and a list of questions it would be great if we could collectively answer!
All this week ELTjam are at the Machine Learning for ELT Conference in Crete. This post looks at the Day 2 action, including more detail on automated error correction techniques, error correction related to content words, the importance of Learner Experience Design (LXD) with all this theory, and finally a look at the Write & Improve product from ALTA.
This week is the ALTA’s Machine Learning for Digital ELT Summer School here in Crete, and ELTjam will be blogging (hopefully each day) from the event. This is a summary of the input from Day 1, where we discussed natural language processing, automated essay assessment and error detection and correction. A big day!
We believe that artificial intelligence (AI), machine learning and natural language processing are going to have a massive impact on ELT, and probably more rapidly than many might expect. A fascinating example of this is a new product from Cambridge called Write & Improve, which aims to provide automated help with writing. Diane Nicholls is one of the team behind the product, and we asked her to tell us more about it. In this in-depth interview, Diane talks about how the system works and, perhaps even more interestingly, how it was developed and what was learned in the process. We think it encapsulates a lot of where ELT is heading – both in what the product itself is trying to do, but also in the way the project has brought together the worlds of ELT, academic research and technology in a way we haven’t seen before.
It’s been a while since we did this, but after a year as … interesting … as 2016, we thought we’d have a go at coming up with some predictions for the year ahead. The rules were simple: two predictions each from me, Nick, Tim and Jo. Then in 12 months, we can all look back and wonder just what we were thinking.