Innovation and Language Education Laurene Christensen Knowledge Process Foundations December 9, 2004

Theories of Innovation  Near innovation  Sustaining innovation  Disruptive innovation  Context-creating innovation  Leapfrogging

Near-innovation in language education  Continuous improvement is seen as innovative, when in fact, it isn’t  Example: Using iPods as technology in the language classroom to record speech and play it back. It’s new and uses digital native technology, but doesn’t really add value.

Sustaining innovation in language education  Often technologically driven, these are innovations that improve the efficiency of a process (may not always be true innovation)  Example: current developments in translation software (uses speech recognition) (translation resource site)

Another example  learning language through artificial intelligence and computer gaming techniques  Rapid Tactical Language Training System—used to teach Arabic to US soldiers  (language bot)

Disruptive innovation in language education  Just-in-time innovations designed to cheaply fill an emerging need  Example: online language real-time chats/tutorials

Context-creating innovation and language education  Through the timely application of new knowledge in context, these innovations create new contexts (this may apply to all innovations, but some are more obvious)  Example, Berlitz has two new partnerships Corpedia/Hofstede: Succeeding in a Diverse Environment Lexicon Training Services: training for large corporations that employ Latinos

Leapfrogging and language education  Leapfrogging involves challenging the assumption that all stops on the “developmental continuum” are necessary and unavoidable.  Example: Teaching “remedial” English in content-based, credit-bearing classes

Current limitations  Diffusion of language innovations is lacking  Language education does not have a vision for knowledge and innovation  Language education has not addressed the digital immigrant/digital native divide  Language education is not prepared for the singularity  Language education is not prepared for the growing role of AI

What is lacking?  Emphasis on the role of tacit knowledge in language learning  Greater Innovation (all types)  Play/creativity  Increased comfort with technology as a tool for language learning  Vision

The future of language education can be said to be characterized by  Increasingly rapid rate of the development of new words  New linguistic structures to accommodate new knowledge  Innovation in knowledge and innovation diffusion  A close relationship with technology  Wide range of language learning contexts  Language learning for personal context development