The role of guided induction in paper-based data-driven learning

Smart, Jonathan

doi:10.1017/s0958344014000081

Cited by 91 publications

(90 citation statements)

References 37 publications

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“…However, those who declare to be implementing DDL involve learners of all levels of language proficiency including those lower-level or secondary school students and design activities based on printed corpus materials without requiring learners to consult corpora directly. Later, Smart [8] claims that it can be regarded as DDL as long as it meets the following two requirements: the use of authentic corpus data as learning materials or reference resources; the design of student-centered exploratory learning activities. So far, there is no consensus on the exact definition of DDL, and researchers name it in different ways such as corpusbased learning and learner concordancing, etc.…”

Section: Theoretical Background Of Ddlmentioning

confidence: 99%

Data-driven Learning in Second Language Writing Class: A Survey of Empirical Studies

Luo

Zhou

2017

Int. J. Emerg. Technol. Learn.

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Abstract-Corpus technology is commonly used by researchers and professionals for language description; however it can also be employed by second or foreign language learners in what has come to be known as data-driven learning (DDL). DDL has been suggested as an effective approach to improve second language (L2) learners' writing competence. To popularize DDL approach among ordinary language teachers and learners, this paper offers an overview of empirical DDL research in writing published from 2010 to 2016, which can provide insights into how DDL approach is integrated into an actual writing classrooms and how much it can contribute to the development of L2 writing skill. The analysis of the surveyed studies reveals the great potentials of DDL activities in L2 writing class from different perspectives but it's also found that corpora are not superior to other traditional reference tools for some consultation purposes. For certain lexical problems, L2 learners are more willing to consult online dictionaries or other conventional tools. It is thus suggested to develop online platforms which could provide easy and free access to the userfriendly corpora along with other types of reference tools. The tendency of future studies is also predicted in the end.

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Section: Theoretical Background Of Ddlmentioning

confidence: 99%

Data-driven Learning in Second Language Writing Class: A Survey of Empirical Studies

Luo

Zhou

2017

Int. J. Emerg. Technol. Learn.

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“…Although Boulton (2010) argued that DDL does not fit well into teaching certain aspects of grammar, some studies (e.g., FrankenbergGarcia, 2012;Gaskell & Cobb, 2004;Gilmore, 2009;Quinn, 2014) found positive effects of DDL in terms of correcting typical L2 mistakes. Additionally, Rezaee et al (2014) and Smart (2014) favored DDL, claiming that it improves learners' knowledge of collocations and grammar knowledge as they frequently come across multiple examples juxtaposed line by line that are related to the use of an unknown word in different contexts (Thurstun & Candlin, 1998;Wu, Witten, & Franken, 2010).…”

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confidence: 99%

Vocabulary Learning through Data-driven Learning in an English as a Second Language Setting

Soruç

Tekin²

2017

EDUC SCI-THEOR PRACT

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The past twenty years have witnessed rapid advances in the field of corpus studies, with some studies, for instance, investigating the effectiveness of data-driven learning (DDL), through which students can discover and learn. However, empirical evidence on this approach to learning is still limited. Therefore, the present study, first, investigates whether DDL is effective in vocabulary learning compared to traditional instruction (TI), and, second, explores students' attitudes toward vocabulary learning when taught with either a DDL or a TI approach. The study was carried out at a secondary school in Kampala, Uganda, and compared students in a DDL group (N = 36) to those in a TI (control) group (N = 36). The pre-/posttest analyses revealed that, although both groups performed in the posttests better than the pretest, the DDL group achieved significantly higher scores than the TI group on both the immediate and the delayed posttest. Moreover, semi-structured interviews with six students corroborated the quantitative results, revealing that the students favored DDL, based on such expressions as "freedom," "comfortable," "relaxing," "technological," "feeling myself responsible," and so on. The paper gives some implications for the same teaching/learning situation and makes suggestions further research.

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“…Many have cautioned that it is important to provide adequate time, support, and guidance to students (e.g., Boulton, 2009;Smart, 2014;Vannestål & Lindquist, 2007). In order to take advantage of the great potential that DDL offers for vocabulary development, it is important to choose vocabulary words that are best suited to teaching with this method.…”

Section: The Problem Of Choosing Specialized Vocabulary For Ddl Activmentioning

confidence: 99%

“…Despite the strengths that DDL can offer to the classroom-integration of lexicon and grammar, consciousness-raising, inductive learning, and teaching grammar in discourse contexts-a significant criticism and recurring caution is that corpus data can be overwhelming or confusing to students (see, e.g., Smart, 2014;Vannestål & Lindquist, 2007). With a large corpus, student concordancing can uncover too many occurrences of a search term to process or make sense of.…”

Section: Addressing Ddl's Challengesmentioning

confidence: 99%

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An Analytical System for Determining Disciplinary Vocabulary for Data-Driven Learning: An Example from Civil Engineering

Otto¹

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Data-driven learning (DDL), an inductive teaching approach in which students learn through corpus interaction, has gained recent traction as way to teach specialized vocabulary in English for Specific Purposes (ESP) classes. There is little research, however, that addresses how to choose specialized vocabulary for teaching with DDL.This study addressed this gap in research by exploring the potential of a three-part analytical, corpus-based system for determining vocabulary to teach with DDL for a specific context of language use. This system included (1) identifying words that were significantly more frequent in a specialized expert corpus than in a corpus of general English, (2) narrowing to words that showed patterned differences in use between the specialized corpus and a student corpus, and (3) narrowing further to words with salient enough patterns of usage to teach with DDL. This three-part system was applied to the context of civil engineering in order to find vocabulary words to teach civil engineering students with low-proficiency writing skills at Portland State University.For the first step in my analytical system, I found 201 words that occurred significantly more frequently in civil engineering practitioner writing than in the Corpus of Contemporary American English and that met requirements for frequency, distribution, and other criteria. I tested the second and third steps on 45 of these words and identified 14 words that showed evidence of needing to be taught and being well suited to DDL.After reflecting on my process, I found that the analytical system was successful in meeting my goals for finding civil engineering vocabulary for data-driven activities. I ii also made several observations that may be useful for ESP teachers who are interested in applying this methodology for their classes, the most notable of which were:1. The system was especially useful for connecting words that are not explicitly civil engineering themed (e.g., encountered or using) to important writing functions that civil engineers perform.2. Although it provided a systematic basis for vocabulary teaching decisions, the process was generally time-consuming and required complex judgments, which indicated that it may only be worth performing if teachers plan to regularly incorporate DDL vocabulary instruction into their course.iii Acknowledgments

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The role of guided induction in paper-based data-driven learning

Cited by 91 publications

References 37 publications

Data-driven Learning in Second Language Writing Class: A Survey of Empirical Studies

Data-driven Learning in Second Language Writing Class: A Survey of Empirical Studies

Vocabulary Learning through Data-driven Learning in an English as a Second Language Setting

An Analytical System for Determining Disciplinary Vocabulary for Data-Driven Learning: An Example from Civil Engineering

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