Abstract
In this chapter we discuss novel ways of teaching English using new technology. The chapter begins with a brief history of language pedagogy and why current practice, especially in the area of grammar teaching, has not always been satisfactory. We then describe the creation of a number of apps for the teaching of the English language, specifically the interactive Grammar of English (iGE), Academic Writing in English (AWE) and English Spelling and Punctuation (ESP). These apps use corpora to source example sentences dynamically and to populate exercises.
Keywords
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.
AWE and ESP were funded by a UCL Teaching Innovation Grant, and iGE was developed as a spin-off from the AHRC-funded projects Creating a Web-Based Platform for English Language Teaching and Learning (AH/H015787/1) and Extending the Englicious Platform for Primary English (AH/L004550/1). We gratefully acknowledge this support.
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- 1.
The three apps can be accessed online via the Survey of English Usage: http://www.ucl.ac.uk/english-usage/apps. A fourth app, Grammar Practice for KS2 (GP-KS2), is also available.
- 2.
The British comic group Monty Python made fun of the drill-based approach in a sketch in which a foreigner walks into a shop holding a Hungarian phrase book, and says to the shopkeeper: ‘I will not buy this record; it is scratched’. The shopkeeper replies: ‘No, no, no, this is a tobacconist’s’. The visitor, experiencing an aha-Erlebnis, then says: ‘Ahh, I will not buy this tobacconist’s; it is scratched’.
- 3.
See http://www.ucl.ac.uk/internet-grammar. IGE was funded by JISC JTAP-49.
- 4.
This method is commonly used to rank items by user-ratings on websites.
- 5.
- 6.
However, see also iGE in the classroom, http://www.ucl.ac.uk/english-usage/apps/ige/classroom.htm.
- 7.
For child learning apps it may be appropriate to employ frequency statistics from age-appropriate corpora and also pre-screen the vocabulary in other ways.
- 8.
This was further complicated after the first 100 words, as from this point on frequency differences between test words are rather smaller and less reliable. We therefore chose to additionally classify these words into four 25-word groups by their expected context (‘Academic’, ‘Business’ and so on).
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Mehl, S., Wallis, S., Aarts, B. (2016). Language Learning at Your Fingertips: Deploying Corpora in Mobile Teaching Apps. In: Corrigan, K., Mearns, A. (eds) Creating and Digitizing Language Corpora. Palgrave Macmillan, London. https://doi.org/10.1057/978-1-137-38645-8_8
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