Do you want to know how AI boosts literacy rates? But before we dive into that as a whole, let’s look at the importance of reading, and why it matters to children and adults so much.
Reading skills are the cornerstone of a child’s education. Reading is something that’s deeply ingrained into our very existence. Rare are the times when you leave the house without having to pause to read some signs on the street or other. Even when you look down at your phone to read text messages or check unread messages.
Point of the matter is, in the absence of secure reading attainment, children can easily fall behind in all areas of the curriculum. And when that happens, it’s going to be hard to make up for lost time.
Catching reading problems early on is very crucial. And being able to identify different reading difficulties in young kids and helping them address it certainly makes a big difference.
So what does AI have to do with all this?
Over the past few years, the world has become increasingly aware of the positive impact of artificial intelligence on people’s daily lives. AI helps doctors detect illness, assisting banks in preventing fraud, and a host of other things. However, make a small mention of AI in education, and the unwelcome image of a robot teacher comes to mind.
But one thing we all need to understand is, how AI boosts literacy rates is through aiding teachers. Not replacing teachers. Human teachers are irreplaceable. Tried and tested reading methods, like Dicker Reading method, are priceless.
Human educators have valuable human skills and years of experience under their belt. The purpose of AI in education systems is to help schools uncover patterns that they won’t otherwise detect.
Think about an AI tool that can help teachers spot which children are having reading difficulties just by tracking the way their eyes move across the page when they read aloud.
Seeing Machine Learning In-action
Here’s a great example of AI being used in action:
Mersey Vale relies on traditional reading comprehension tests and teacher assessments to evaluate pupils’ reading. A good example of AI innovation is Lexplore’s revolutionary eye-tracking technology. It adds new insights into students’ reading attainment.
Children whose eyes rest longer than usual on a single word and move more slowly along a line of text, find reading more challenging. By knowing this, you can give them targeted support, so you can help build their literacy skills farther.
The benefit of machine learning technology is that it gets better the more you use it. Tools can be trained how children read. It can only get more accurate in the future.
How AI Can Boost Literacy Rates
AI in education has the potential to help make students’ and educators’ lives more manageable. How AI boosts literacy rates: machines can complete pattern tasks that are mostly performed by humans.
In the meantime, educators have the freedom to focus on tasks that can’t be achieved by AI. Tasks that need emotional intelligence and experience to complete.
But how AI can be used in nuanced areas of education like literacy? There are many reading and literacy activities and assessments that teachers complete themselves that can be easily facilitated by AI.
Again, how AI boosts literacy rates? If repetitive activities like these can be automated, it lets educators spend time with their students who need more intensive academic interventions.
#1 Doing Question-Answer Relationships
This is a reading technique that helps students determine the difference between questions and answers that can be found directly in the text (“right there”), questions with answers that can be found in the text but require information synthesizing (“putting it together”), and questions that require the reader to make use of prior knowledge to find the answers (“doing it on your own”). Here, you can use machine learning to automate this activity.
#2 Informal reading inventory
This one is an assessment method. Students read a series of passages and answer questions. Educators observe students’ reading strategies, choose the relevant reading material, and ascertain three student reading levels.
And then they can be informed about students’ strengths and weaknesses. AI can be programmed to perform these tasks.
#3 Guided Reading and Summarizing Procedure (GRASP)
GRASP is a reading strategy and teacher guidance in which students read to collect information. Afterward, they try to remember the information as much as possible.
List what they remember after the reading, reread the material to add to, delete, and correct information. Afterward, students must organize information according to their details. These sorts of activities can be automated using AI, while still needing varying levels of teacher guidance.
Quickwrites are an informal writing technique that helps ascertain students’ prior knowledge of specific topics, monitor comprehension or summarize newly acquired knowledge. In this activity, students write what they know about a particular topic.
Afterward, it can be used to determine starting points for teaching, to evaluate student learning, and for planning future lessons.
At present, AI can be used to score student essays. So there’s certainly no reason why it can’t be used to analyze and assess this activity.
AI can fact-check students’ prior knowledge through trusted internet sources or a database. By providing insights into the level of familiarity a student has with a subject matter, teachers can create personalized learning paths for each student.