Data-driven learning (DDL)
The sphere of data-driven learning (DDL) aims to carry students’ investigative learning of grammar and vocabulary by using computer apps to help them pay attention to patterns in the target language. The most broadly-used type of such program is the concordancer allowing to select a unit, such as a stem, word, or phrase, and search for examples of it in a particular corpus. The results are usually presented in a series with the selected unit in the center and the local context in which it appears on either side [Hubbard, p. 8].
The DDL teaching approach is grounded in which students are presented with examples of naturally-occurring language, and they should discover any systematic patterns of this on their own, without being presented with grammatical rules, the meaning of lexical units, etc. [Igi-Global].
The DDL approach makes possible a new style of “grammatical consciousness-raising” via placing the student's discovery of grammar at the focus of learning language and by making it possible for that discovery to be grounded on evidence from authentic language use [Johns, p. 3].
⠀ Data driven learning. Igi-Global. Retrieved from: https://www.igi-global.com/dictionary/data-driven-learning-ddl/85102.
⠀ Hubbard, Philip. (2009). Computer-Assisted Language Learning. Retrieved from: http://hstrik.ruhosting.nl/wordpress/wp-content/uploads/2013/03/callcc-intro.pdf.
Johns, Tim (1991). Chapter 2: Should you be persuaded: Two examples of data-driven learning. Classroom Concordancing. Birmingham: ELR. URL : https://lexically.net/wordsmith/corpus_linguistics_links/Tim%20Johns%20and%20DDL.pdf