How to acquire a foreign language by reading? Part 2
How to make foreign language acquisition convenient for most students? Particularly, how to do it by reading?
Part 1: Acquire a foreign language with content you love.
Assumptions
Before jumping into it, let me clarify the assumptions that I lean on. Students really read something when it is genuinely interesting for them. They do it repeatedly and frequently; they do it with internal motivation and read with a deep focus. Also, let’s assume that one can acquire a foreign language by reading. At least develop the skill of understanding the messages in the target language (put aside speaking and writing skills). These assumptions combine in the concept of Self-Selected Pleasure Reading (SSPR). And in a broader sense this ties to Comprehensible Input theory — one acquires a foreign language by understanding (comprehending) the message (text, video, audio, etc.) in the target language.
But some factors prevent EFL students to acquire a foreign language by reading. For students with a poor vocabulary, the higher their age the less choice they have of comprehensible and interesting reading materials. What does a poor vocabulary mean? In the context of this article, when one does not know around 3,000 most frequently used words. These words cover about 90% of any content (source: Power of Words | Charles Browne | TEDxTokyoTeachers). The topics that are interesting for a teenager aren’t written with a simple vocabulary. And if one can’t understand around 90% of the text, they can’t comprehend the message (source: IRCEELT-2020 (Online) 1:25:40–1:27:00).
Existing platforms
There are already platforms that help students to read, e.g. commonlit.org and readworks.org. They have curated articles organized by grade levels and topics. Also, features like text-to-speech and quizzes, which help students with comprehension. But I doubt that these and similar platforms can ensure every student gets readers that are genuinely interesting for them and comprehensible, at the same time. These platforms are good at making comprehensible texts, but every student has different interests, and to have a personalized learning experience for each and everyone would require having 1:1 tutoring.
Don’t get me wrong, I do not intend to belittle the positive impact these platforms make or, for that matter, the merit of teachers. The problem is that I don’t see how the existing systems could address this issue — how to make reading comprehensible and genuinely interesting for every student?
We could try (and are) to get students interested in the content we have curated, but the world is out there. Students want to learn (read) about what they are experiencing, what they like and love, what is trending. And I can’t imagine how a teacher or even a team of professional reading content creators can keep up with the pace and volume of this avalanche of information and make readers for each and every student. Maybe it is just my ignorance, and there is a way. Let me know.
To highlight the main issue.
There is reading content that is interesting for any student. The problem is that it might not be comprehensible for them.
In a specific sense of the word comprehensible, that is for foreign language acquisition. I will try to describe here a technological solution for this problem. Before getting into it, I want to clarify that I don’t see this (or, for that matter, any other ed-tech) as a substitute for teachers. I consider this as a tool that students and teachers could use in combination with other activities and/or tools.
Comprehensible Reader Generator
Let’s call this tool Comprehensible Reader Generator (CRG). CRG is like a browser extension that works in the background while student surfs the internet. When they stumble upon an interesting article, CRG checks if they can read it. This tool has a feature to assess the Readability Index of a given text, but unlike existing indexes, this one takes into account the reading skills of the specific student. This means that any given text would have a different index depending on a person’s reading skills it is calculated for. So, let’s call it a Personalized Readability Index (PRI).
If the article’s PRI is in the student’s comprehensibility range (90% of the words are familiar to them) nothing else needs to be done. The student goes on to read it. But if it’s not, the article is rewritten by the program to fall into that range.
How is it rewritten? CRG uses something like GPT-3 to do that. The crucial detail is that, like with PRI, the program considers student’s vocabulary levels to make the text as comprehensible as possible. But not 100% comprehensible. Because if there are no new words, students won’t learn new vocabulary.
Also, familiar words are used strategically to make the student recall the ones they might be forgetting. Knowing words is not binary — you know them, or you don’t. It’s more like a continuum of how easily one can recall the word. How easily one can retrieve it from the long-term memory. In other words, students can practice Spaced Repetition in a more natural context than using cards.
CRG also works as an RSS subscription for topics one is interested in. People usually surf the part of the internet that is understandable for them. In other words, in their native language. So, to increase one’s exposure to English content, something like RSS is required. After finding an article, it does the same steps described above — checks the PRI, and if necessary, rewrites the article.
These are the main features of Comprehensible Reader Generator. Next, I’d like to make some clarifications.
Tool vs Game
Recall the software that you are using daily. Do you use it for something or for itself? A few examples, browsers — we use for getting on the internet, search engines — we use to search for stuff, presentation software — to make presentations, and so on. The opposite would be games — we play games for the sake of it.
Now let’s think about language learning software. I will bring two personals examples. Duolingo and WordUp are the ones I use more or less frequently. And, unfortunately, both of them feel more like games than like tools. Mostly, I use them with motivation to use the software itself, not for what they are intended for by the developers. So, in the case of Duolingo (I’m learning Japanese there), I use it to keep my streak (300 days as of today), to restore “cracked” skills, and sometimes to advance to the next level in a new skill or keep my place in a high league. Some time ago they added new Challenge activities, and it got me interested to get enough XP to complete the challenge. As you can see I mostly use Duolingo for the sake of it. Somewhere in my mind, yes, I do think it helps me to learn Japanese. But the day-to-day motivation to use it comes from the reasons mentioned above.
As for WordUp, I use it more rarely in situations when I stumble upon a new English word. I use WordUp to look up the definition and save the word to repeat it if I find it important. And, sometimes, I do the spaced repetition activity to recall the words added previously. I do this repetition rarely, somehow didn’t get into the habit of it. And WordUp also feels like a game than a tool.
To clarify, I like both Duolingo and WordUp. I have seen a bunch of language apps, and I still think that these two are some of the best. But to get back to my main point — I think the most effective language acquisition software would be the one that feels like a useful tool, not as an engaging game. The concept of the Comprehensible Reader Generator seems to have the potential to be a tool used daily.
Summarizers
There already are some tools that do something similar to what I have described here — Quillbot, Wordtune, and Resoomer. What they are lacking, in general, is to have EFL students in mind when developing the features. To give a specific example — they don’t take into account one’s vocabulary level when summarizing the text. But still, they are very close to the idea of CRG, and I’d love to see any of them develop in that direction.
So, yeah, basically, this is it. And for the ending, I’d like to share a few more thoughts on this tool.
Comprehensible Reader Generator + Variations
When rewriting the text, one way to do it might be like this Telescopictext. First, it would give a one-sentence TL;DR of the article written with familiar words (no new ones, or the ones that need repetition). If a student wants to learn more, they can click on interactive words and expand the story. And there, we can have new words and the ones that need recall to stick better in the long-term memory. This option has two benefits. First, it’s practical and saves time — you just read one sentence, get the gist of the article and move on. Second, it utilizes the concept of prior knowledge. The student is familiar with the content of the article from the first sentence, and corresponding knowledge in the long-term memory is activated. This way, they increase their chances to comprehend new words and recall the ones they learned before.
If you noticed, what you have read so far doesn’t describe a language learning tool. CRG does one thing — makes the text comprehensible. Students read what they are interested in; it just helps them do it. But, I believe students benefit from direct instruction as well. I won’t go into details here but imagine different pre-, during-, and post-reading strategies that might be built on CRG to help students with reading. Also, make teachers’ work easier.
Images and Videos
And for the final final thoughts, let’s look at other types of media. Modern AI is good not only with text but with images and videos. And these (images and videos) might help students; make content comprehensible and interesting. Few examples, in the case of images there is this DALL·E (video review) that can generate an image from the text description. As for the video, there are different ways of manipulating (rewrite, summarize) or generating a video.
If you have reached it so far, let me know what you think of this Comprehensible Reader Generator concept.
