We may have come a long way since the days of filling the blackboard with Latin declensions, but the field of formal language teaching and learning is still relatively young. The demand for language instruction is surging: the British Council anticipates two billion people studying English by 2020—and that’s just English. While this field is growing dramatically, technology is changing nearly every industry out there, so without a doubt, technology will dramatically reshape what language learning looks like within our lifetime. Let’s take a look at some emerging technologies with the potential to transform the language-learning industry.
Virtual reality—like other items on this list—first debuted decades ago, but back then it was a hefty investment in a clunky headset, cord-bound to a CPU that would transport you to a digital world of wonder. Or if not wonder, at least a world of pixelated polygons. Today, things are different: our iPhones pack all the necessary tech components—magnetometer, gyroscope, etc.—and Facebook’s 360 Videos and YouTube 360 put actual VR (now often called “immersive video”) into our pockets and onto our feeds.
As for the connection to language learning, consider what the New York Times is doing with NYT VR: taking viewers from the inhospitable expanses of Antarctica to the heart of a battle with ISIS in Falluja. Once there, a voiceover and subtitles help to orient us, understand who’s who, what’s where.
But imagine that journey going in the other direction. Picture refugees studying English while they await relocation, transported to the new home that awaits them. A welcoming voice orients them on a virtual tour of their new home: “This is Rutland, Vermont. We are standing on the corner of West Street and South Main Street. You can see a CVS Pharmacy across the street. You can buy medicine there.” Immersive video has the potential to jumpstart the learning process before refugees even set foot on a plane.
Optimized Study Habits
Gamified “brain training” is everywhere. Needless to say, much of it is garbage, but it doesn’t have to be. Combined with good science, this trend holds some serious potential for language learners, which apps like Duolingo are already beginning to capitalize on.
Insights from cognitive psychology have shown us the the importance of spaced retrieval—quizzing at increasing intervals—to improve long-term vocabulary retention, and at recent conferences there has been a buzz around “spiraling” curriculum: spacing out retrieval while adding layers of rigor and engaging higher-order thinking skills. Combined with something like Google Calendar’s recent Goals feature—which analyzes your schedule and automatically pencils in times for you to work toward long-term goals—we might even be able to boost persistence in apps like these.
Which reminds me: “Siri, please cancel my Lumosity subscription.”
The teachers out there might be thinking, What? Bots? In a language classroom? Blasphemy! A few years ago I would have said the same. But the world is changing in some unforeseen ways, and the idea of chatbots in the language classroom isn’t nearly as scoff-worthy as it once was.
The biggest reason that chatbots are suddenly relevant to language learning isn’t that the tech has improved dramatically (though it has: some argue that bots are about to pass the Turing test). Rather, the reason bots now a place in language teaching is that they are suddenly a ‘population’ that students need to be able to communicate with.
Ten years ago, studying with a bot was an artificial learning task: a poor approximation of real-world communicative tasks. But today we regularly pick up the phone and are expected to talk to computers. Customer service chatbots are commonplace across the Web. Siri, Alexa, and Cortana have become household names—well, maybe not Cortana. But the point is that bots are now common interlocutors. Students are going to have to interact with them, so they have to be prepared for those interactions.
Until very recently, I would have argued that the net effects of videoconferencing upon language teaching was adverse. The explosion of Skype and Google Hangouts drove a proliferation of online tutoring programs touting one-on-one lessons with “native speakers” whose credentials are often dubious if not absent entirely. Hopefully it goes without saying that such programs should be approached with a wary eye.
Online group classes haven’t been much better. Your standard software options only allowed for a single speaker at a time, with all other participants listening. This inevitably leads to highly teacher-centered classes. In a physical class, a language teacher that rattled on at the front of the room for the whole lesson would be fired. But in online classes it’s hard to do much else.
That could be about to change. More advanced video-conferencing software, like Zoom, is emerging with tools that can better simulate the conditions for ideal language acquisition. At my startup online English school, Ginseng English, we’re capitalizing on a feature known as virtual breakout rooms. This allows a teacher to put students in pairs and small groups, maximizing student talking time, varying interaction types, and create a fully immersive environment, hallmarks of effective language classrooms.
Massive Audio-Visual Corpora
The fundamental questions of second language acquisition relate to how and why it differs from first language acquisition. Tech is yielding some fascinating new insights into first language acquisition, which could hold a great deal of potential in second language teaching as well.
At MIT, Professor Deb Roy has led The Human Speechome Project, for which he recorded three years of the language his son heard around his home. ROY mapped that data visually onto a 3D rendering of his home, painting a picture of child language development in an unprecedented level of detail. He shared the results of that project in a popular and fascinating TED Talk, The Birth of a Word.
Similar technology is being applied to address the “word gap”—the fact that kids in low-income families hear around 30-million fewer words than children of affluent parents—which is believed to put those kids at a life-long disadvantage. In the Providence Talks project, low-income parents are being given wearables that analyze their speech and give feedback to encourage richer child-directed speech, with some strong results to date.
It’s only a matter of time before similar studies are applied to second language acquisition, providing insights into acquisition patterns and teacher-speak that would have been impossible just a few years ago.
The internet is now well into its second incarnation, known as Web 2.0: The web is no longer a series of static pages that can be thought of simply as “destinations.” Sites now are dynamic, collaborative, often user-generated tools and work-spaces. We can collect data from multiple users and instantly generate sleek infographics. We can work together simultaneously and seamlessly on documents, artworks, cork-boards. The potential here is massive.
Imagine: A teacher asks the class, “What are some of the most difficult words for you to pronounce?” But she doesn’t then have to scramble to scribble the loudest suggestions on the board in whatever order she can manage. Instead, students submit their suggestions on their phones using Mentimeter, immediately populating a list projected on the board, and then are able to upvote others’ suggestions that are also challenging for them, all in a matter of about 60 seconds. Rather than spending the most class time on the first words that the loudest students have shouted, we can now focus on the words that the most students need to work on.