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Writing to learn academic wordsassessment, cognition, and learning /

紀錄類型:	書目-電子資源 : Monograph/item
正題名/作者:	Writing to learn academic wordsby Breno B. Silva.
其他題名:	assessment, cognition, and learning /
作者:	Silva, Breno B.
出版者:	Cham :Springer International Publishing :2022.
面頁冊數:	xx, 268 p. :ill., digital ;24 cm.
Contained By:	Springer Nature eBook
標題:	Academic language.
電子資源:	https://doi.org/10.1007/978-3-031-06505-7
ISBN:	9783031065057$q(electronic bk.)

Writing to learn academic wordsassessment, cognition, and learning /
Silva, Breno B.

Writing to learn academic wordsassessment, cognition, and learning /[electronic resource] :by Breno B. Silva. - Cham :Springer International Publishing :2022. - xx, 268 p. :ill., digital ;24 cm. - Second language learning and teaching,2193-7656. - Second language learning and teaching..

1: The Importance of General and Academic Vocabulary -- 2: Incidental Lexical Learning -- 3: The Writing Cycle and Cognitive Processes that May Affect Learning -- 4: An Overview of the Research Project -- 5: Inferential statistics and linear mixed models -- 6: Study 1 The Assessment of Academic Vocabulary: Developing a Reliable Academic Placement Tool -- 7: Discussion of findings for Study 1 -- 8: Study 2 Lexical Learning through Writing Sentences and Timed essays -- 9: Study 3 Lexical Learning through Writing Sentences, Timed and Untimed essays -- 10: Discussion for Studies 2 and 3.

This book highlights the importance of English academic vocabulary for success at university and explores written tasks as effective pedagogical tools to promote the acquisition of academic words. The book reviews germane and recent SLA, psycholinguistic, corpus linguistics, and L2 writing research to underscore the challenges associated with the learning of academic words. Then, it reports on three empirical studies conducted in the Polish context. The first study develops a reliable tool to assess the knowledge of academic vocabulary of undergraduate learners. The second and third studies investigate the learning of academic words after the writing of sentences and argumentative essays, and discuss the role of cognition as a mediator of such learning. The book also provides an accessible introduction to linear mixed-effect models, a powerful, reliable, and flexible statistical technique that has been gaining popularity among SLA and psycholinguistics researchers.

ISBN: 9783031065057$q(electronic bk.)

Standard No.: 10.1007/978-3-031-06505-7doiSubjects--Topical Terms:

933636
Academic language.

LC Class. No.: P120.A24 / S55 2022

Dewey Class. No.: 378.0014

Writing to learn academic wordsassessment, cognition, and learning /
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505 0 $a 1: The Importance of General and Academic Vocabulary -- 2: Incidental Lexical Learning -- 3: The Writing Cycle and Cognitive Processes that May Affect Learning -- 4: An Overview of the Research Project -- 5: Inferential statistics and linear mixed models -- 6: Study 1 The Assessment of Academic Vocabulary: Developing a Reliable Academic Placement Tool -- 7: Discussion of findings for Study 1 -- 8: Study 2 Lexical Learning through Writing Sentences and Timed essays -- 9: Study 3 Lexical Learning through Writing Sentences, Timed and Untimed essays -- 10: Discussion for Studies 2 and 3.
520 $a This book highlights the importance of English academic vocabulary for success at university and explores written tasks as effective pedagogical tools to promote the acquisition of academic words. The book reviews germane and recent SLA, psycholinguistic, corpus linguistics, and L2 writing research to underscore the challenges associated with the learning of academic words. Then, it reports on three empirical studies conducted in the Polish context. The first study develops a reliable tool to assess the knowledge of academic vocabulary of undergraduate learners. The second and third studies investigate the learning of academic words after the writing of sentences and argumentative essays, and discuss the role of cognition as a mediator of such learning. The book also provides an accessible introduction to linear mixed-effect models, a powerful, reliable, and flexible statistical technique that has been gaining popularity among SLA and psycholinguistics researchers.
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