Understanding Language Teaching
Abstract
This book traces the historical development of major language teaching methods in terms of theoretical principles and classroom procedures, and provides a critical evaluation of each. Drawing from seminal, foundational texts and from critical commentaries made by various scholars, Kumaravadivelu examines the profession's current transition from method to postmethod and, in the process, elucidates the relationship between theory, research, and practice. The chief objective is to help readers see the pattern that connects language, learning, teaching methods, and postmethod perspectives.In this book, Kumaravadivelu:*brings together a critical vision of L2 learning and teaching--a vision founded at once on historical development and contemporary thought;*connects findings of up-to-date research in L2 learning with issues in L2 teaching thus making the reader aware of the relationship between theory, research and practice;*presents language teaching methods within a coherent framework of language-, learner-, and learning-centered pedagogies, thus helping the reader to see how they are related to each other;*shows how the three categories of methods evolved historically leading ultimately (and inevitably) to the emergence of a postmethod condition; and*provides the reader with a solid background in several interconnected areas of L2 pedagogy, such as concepts of competence, input factors, intake processes, interactional modifications, and instructional design.Understanding Languag…
Integrity signals
Registry
Cites
Statistics
Claims the paper makes
Claims other papers make about this one
Each is checked against this paper’s own text: does it say what the citing paper says it does?
Language teaching has been conceptualized as a profoundly humanistic and interpersonal endeavor in which the teacher's linguistic intuition, cultural knowledge, and affective sensitivity are deemed irreplaceable.
“Historically, language teaching has been conceptualized as a profoundly humanistic and interpersonal endeavor in which the teacher's linguistic intuition, cultural knowledge, and affective sensitivity are deemed irreplaceable (Kumaravadivelu, 2006).”
From Adoption and Integration of Artificial Intelligence in Foreign Language Teaching: Multi-Institutional Analysis of Higher Education (2026) · cites this paper as Kumaravadivelu, 2006
Cited by
Sorted by citations
Karadağ, E., Calışkan, N., Çiftçi, Ş. S., & Polat, M. (2026) · Journal of Narrative and Language Studies · doi:10.59045/nalans.2026.93
- Authors
- Kumaravadivelu, B.
- Corresponding author
- Kumaravadivelu, B.
- Venue
- Routledge eBooks
- Publisher
- Routledge
- Published
- 2006-04-21
- OpenAlex
- W4210362880
- Cited by
- 578
- References
- 0
- Citations by year
- 2026: 51 · 2025: 68 · 2024: 43 · 2023: 58 · 2022: 50 · 2021: 40 · 2020: 36 · 2019: 50 · 2018: 33 · 2017: 21 · 2016: 40 · 2015: 10 · 2014: 20 · 2013: 12 · 2012: 17
- FWCI
- 6.11
- Type
- book
- Language
- en
- Open access
- closed
- Locations
- Routledge eBooks (publishedVersion)
- Topics
- Social Sciences › Arts and Humanities › Language and Linguistics › EFL/ESL Teaching and Learning
- Social Sciences › Arts and Humanities › Literature and Literary Theory › Second Language Learning and Teaching
- Social Sciences › Education › Foreign Language Teaching Methods
- Keywords
- language teaching, history of language teaching, second language teaching, foreign language teaching, theory-practice integration, student-centered learning, second language acquisition, factor inputs, instructional design, competence concept
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review