LANGUAGE LEARNING & TECHNOLOGY
A refereed journal for L2 researchers and educators interested in the role of technology in advancing language learning and teaching.

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Showing 41 - 50 results of 72 for Plonsky

Self-regulated and collaborative personalised vocabulary learning approach in MALL. Language Learning & Technology
...Plonsky and Oswald (2014) regarding effect 10 Language Learning & Technology size for L2 research, the Cohen's d values obtained suggested a very small effect (Cohen's d = 0.18) for receptive...

by Qing Ma, Ming Ming Chiu
in Volume 28 Number 1, 2024

Special Issue of Special Issues: 20 Years of Language Learning & Technology
...Plonsky and Ziegler offer a two-part article that begins with an inventory of the findings from meta-analyses and synthesis reviews of CALL and SLA research. In this section, they conduct a review of...

by Philip Hubbard, Greg Kessler, Paige Ware
in Volume 20 Number 2, June 2016 Special Issue of Special Issues: 20 Years of Language Learning & Technology

The effects of captions on L2 learners’ comprehension of vlogs
...Plonsky and Oswald (2014). Follow-up univariate analyses indicated that students of each proficiency level significantly differed in their scores across the three vlogs (p < .001). In order to deter...

by Dukhayel Aldukhayel
in Volume 25 Number 2, June 2021

Exploring the relationship between L2 belongingness, personal L2 enjoyment, and willingness to communicate across language learning contexts
...Plonsky & Ghanbar, 2018), accounting for approximately 11.9% (Model 1) and 11.1% (Model 2) of variance in in-person L2 WTC as indicated by adjusted R² values. To probe the moderating role of person...

by Mehdi Solhi, Artem Zadorozhnyy, Ju Seong Lee
in Volume 30 Number 2, Special Issue: Emotional CALL

Integrating semiotic resources in CALL activity designs
...Plonsky (2015), double-coding 10 to 20 percent of the qualitative data is a standard research practice in applied linguistics. The results of data analysis conducted to answer the three research que...

by Ruslan Suvorov, Paul Gruba
in Volume 27 Number 2, February 2023 Special Issue: Semiotics in CALL

Comparing individual vs. collaborative processing of ChatGPT-generated feedback: Effects on L2 writing task improvement and learning
...Plonsky and Oswald (2014) and Gignac and Szodorai (2016). Results Descriptive statistics of rated draft writings, final products, and the corresponding task improvements are shown in Table 2. ...

by Da Yan
in Volume 28 Number 1, 2024

The use of lexical complexity for assessing difficulty in instructional videos
...Plonsky & Oswald, 2014). To prepare the dataset for regression modeling, we shuffled the entire dataset and created both training and testing sets through a 67/33 split approach (Han et al., 2011); ...

by Emad A Alghamdi, Paul Gruba, Ahmed Masrai, Eduardo Velloso
in Volume 27 Number 1, 2023

The effects of feedback type and explicit associative memory on the effectiveness of delayed corrective feedback in computer-mediated communication
...Plonsky and Oswald (2014). 3. Confidence intervals provide an alternative approach to assessing significance. If the confidence interval does not contain zero, the p-value will be less than 0.05 (La...

by Yucel Yilmaz, Gisela Granena, Laia Canals, Alexandra Malicka
in Volume 28 Number 1, 2024

Enhancing extensive reading with data-driven learning
...Plonsky & Oswald, 2014) it seemed clear to us that some in the experimental class had higher levels of proficiency in this area than those in the control class. Scores for the experimental and contr...

by Gregory Hadley, Maggie Charles
in Volume 21 Number 3, October 2017 Special Issue on Corpora in Language Learning and Teaching

The effects of face-to-face and computer-mediated recasts on L2 development
...Plonsky and Oswald (2014), the effect sizes were interpreted as small when r was close to .25, medium when r was close to .40, and large when r reached .60. 8 Language Learning & Technology ...

by Nektaria-Efstathia Kourtali
in Volume 26 Number 1, 2022