The future of language learning:
Recent developments in machine learning and the innumerable projects on applications of machine learning such as the Apple Siri, Microsoft Cortana and Google Now make us ponder and wonder on the future of language learning. Google has just thrown open its AI engine TensorFlow and we can expect a flood of machine learning applications to facilitate human communication. Automatic translation is continuously improving.
We assess language acquisition in terms of levels, such as the 9 IELTS Band scores or the 6 levels of CEFR or other alternative scales.
But the critical question is how fast can one move from one level to the next higher one. This is clearly not a sudden ‘quantum’ jump represented by what in Mathematics is called a Heaviside step function or ‘theta’ function which is a discontinuous function whose value is zero for negative argument and one for positive argument.
The learning curve is a S shaped sigmoid curve, represented by three parameters a,b and c, where a represents the asymptotic value, b the displacement and c the rate. More details are given in resource no.5 below.
The challenge is to use Josh Kaufmann’s approach of following a steeper learning curve, by actually measuring the learning curve, and use mobile Apps such as Duolingo, immersive learning experiences on Oculus Rift or tools of learning analytics to personalise the learning curve to desired levels.
Another aspect of interest is the anticipation of the future of human language.
For the first time ever, the Oxford Dictionaries Word of the Year is a pictograph: , officially called the ‘Face with Tears of Joy’ emoji. There were other strong contenders from a range of fields, but was chosen as the ‘word’ that best reflected the ethos, mood, and preoccupations of 2015.
Ad blocker and dark web were two of the short listed terms directly connected to information technology.
We can therefore imagine a future ‘constructed’ language spanning both human and computer communication and adoption of terms from other languages, a re-birth of ‘esperanto for the 4th Industrial Revolution’ promoting unforeseen efficiency in a human intelligent machines ecosystem. Esperanto is still a language in the CEFR system.
It is clear that we are at very interesting times, where we can draw analogies to the past, but the way forward is like a journey into outer space.
Resources for further exploration and better understanding:
1. Language Technology : a first overview : http://www.dfki.de/~hansu/LT.pdf
2. The coming merge of human and machine intelligence : http://now.tufts.edu/articles/coming-merge-human-and-machine-intelligence
3. Esperanto : the 32nd language conforming to CEFR :https://en.m.wikipedia.org/wiki/Esperanto
4. Time to learn a new language: https://drsaraheaton.wordpress.com/2011/02/20/how-long-does-it-take-to-learn-a-new-language/
5. All about learning curves : http://www.galorath.com/images/uploads/LearningCurves1.pdf
6: Learn Immersive teaches languages in virtual reality : http://www.gizmag.com/learn-immersive-language-virtual-reality/35128/
7: Learning a foreign language in a virtual environment : http://www.winchesterthurston.org/page.cfm?p=2509
8: Apple’s Siri versus Microsoft’s Cortana on an iPhone : http://time.com/4156795/siri-cortana-microsoft-voice-assistant-apple-iphone/
9: A post on rapid skill acquisition, summarising Josh Kaufmann’s first 3 chapters : http://www.stafforini.com/blog/summary-of-the-first-20-hours-by-josh-kaufman/
10:
The first 20 hours — how to learn anything | Josh Kaufman – YouTube
https://www.youtube.com › watch
