Many districts use reading programs that incorporate computer-based practice. However, not all programs offer a science-based approach. In a recent article from Edweek, they report that there are five programs used in schools to teach reading that aren’t backed by any science-based evidence. These programs are:
The Units of Study for Teaching Reading (by the Teachers College)
Reading and Writing Project Journeys (Houghton Mifflin Harcourt)
Into Reading (Houghton Mifflin Harcourt)
Fountas & Pinnell’s Leveled Literacy Intervention (this is for early intervention)
Reading Recovery (also for early intervention)
According to the article in Edweek, “…frequently, these programs are teaching students to approach words in ways that could undermine the phonics instruction they are receiving. ”One of the concerns is related to the idea that students can use other clues to aid reading. This is aligned with the notion that using pictures to help decode words helps a student read. Unfortunately, guessing or not focusing solely on the letters of the word could lead to poor reading or reading a word inaccurately.As Edweek notes, “…The problem is that it trains kids to believe that they don’t always need to look at all of the letters that make up words to read them.” This isn’t to say that the programs used by a school are bad or even ineffective. Many children use the above programs and are fluent readers. Other children, though, could focus less on decoding and more on guessing, and this could, perhaps, exacerbate their reading struggles.
How Can AI Support Struggling Readers?
Let’s look first into the history of AI. Artificial intelligence (AI) and speech recognition have been around since the 1950s. “The first official example of our modern speech recognition technology was “Audrey,” a system designed by Bell Laboratories. In the early 1970s, the Department of Defense began to recognize the value of speech recognition technology for national security purposes. In the 1980s, speech recognition systems started making their way into children’s toys. At the same time, scientists began to move toward natural language processing (NLP). Instead of just using sounds, they focused on algorithms to program systems.Software today recognizes and responds using natural language to support humans. Today you will find voice-activated digital assistants at work and home. We have found that AI can help students who are struggling to read by providing the following:
Reading practice
Multisensory input
Learners choices
Comprehension checks
Sight word focus
Real-time continuous feedback and assessment
Tracking progress and creating reports on student learning progress
