Assessing linguistic complexity features in L2 writing: Understanding effects of topic familiarity and strategic planning within the realm of task readiness

Tabari, Mahmoud Abdi; Wang, Yizhou

doi:10.1016/j.asw.2022.100605

Cited by 21 publications

(6 citation statements)

References 46 publications

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“…The increase in MLT further supported Robinson's (2001Robinson's ( , 2005 CH, as learners engaging in more complex tasks were required to process and produce language in intricate and sophisticated ways. This prompted them to employ higher-level cognitive processes, contributing to the development of more complex sentence structures and longer, more elaborate sentences (Abdi Tabari & Wang, 2022).…”

Section: Discussionmentioning

confidence: 99%

“…In this study, we used natural language processing (NLP) tools, including Coh‐Metrix (McNamara et al., 2014) and the syntactic complexity analyzer (Lu, 2010), to examine syntactic complexity and provide an accurate representation of the construct. We followed Mazgutova and Kormos’ (2015) and Abdi Tabari and Wang's (2022) classifications of linguistic complexity and ensured that the target metrics were not redundant and that the constructs were distinct and valid. This helped us avoid two common problems observed in previous studies—namely, redundancy of measurement (Norris & Ortega, 2009) and circularity of reasoning (Bulté & Housen, 2012).…”

Section: Methodsmentioning

confidence: 99%

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Withdrawn: Exploring the associations among task complexity, task motivation, task engagement, and linguistic complexity in L2 writing

2024

The Modern Language Journal

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The interactions among cognitive, affective, and linguistic factors have received scant attention in task‐based writing research. To address this gap, this study aims to examine the relationships among task complexity, task motivation, task engagement, and syntactic complexity in second language (L2) writing. One hundred L2 learners enrolled in an English‐as‐a‐second‐language (ESL) writing course at a university in the United States performed simple and complex versions of an argumentative writing task at a 1‐week interval. After each task performance, participants completed questionnaires examining their task motivation. Task engagement was measured through time on task and length of production. The essays were analyzed using specific syntactic complexity measures. The results showed that the participants dedicated more time to the complex task and displayed higher motivation levels in two orientations (identified and intention). Furthermore, they produced fewer words when faced with a complex task. Additionally, task complexity influenced only one dimension of syntactic complexity. Finally, time on task predicted two dimensions of syntactic complexity (mean length of T‐unit and mean number of complex nominals per clause). These results emphasize the need to consider cognitive, affective, and linguistic factors in task‐based writing research. By doing so, educators can develop writing tasks that effectively engage ESL learners, enhance their motivation, and promote their linguistic growth.

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Section: Discussionmentioning

confidence: 99%

Section: Methodsmentioning

confidence: 99%

Withdrawn: Exploring the associations among task complexity, task motivation, task engagement, and linguistic complexity in L2 writing

2024

The Modern Language Journal

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“…They found that the group that completed more complex tasks (using more than one source of passages instead of one source of reading passage) changed in some ways of syntactic complexity (average length of clause, subordination, and average number of modifiers per noun phrase), lexical diversity, and causal cohesion, and had worse grammatical accuracy but no change in lexical sophistication. Abdi Tabari and Wang (2022) thought of topic familiarity as a factor inside the task. They studied how topic familiarity (and strategic planning) affected language performance of L2 test takers in terms of task readiness.…”

Section: Prior Studies On the Effect Of Task Complexitymentioning

confidence: 99%

A Longitudinal Analysis of the Variability of Cognitive Complexity in IELTS Academic Writing Prompts: a mixed-method study

Khademi

2024

Preprint

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Cognitive complexity of writing prompts may affect the linguistic performance of test takers in writing assessment, as evidenced by previous research. In this mixed method study, we aim to explore if and to what extent the perceived cognitive complexity of IELTS Writing Task II prompts has changed over time. We use official IELTS prompts for this study collected over test administrations years 1996 to 2022. For each test year, two prompts were randomly selected (total of 20 prompts for ten years) and were structured in a survey. Experienced IELTS teachers and assessment experts (n = 19) rated the perceived cognitive complexity of each prompt on 1-8 Likert scale. An intra-class correlation (ICC) coefficient showed a high degree of inter-rater reliability among the raters (r = 0.88, p = 0.00). A time series analysis showed that the perceived year-on-year cognitive complexity of the prompts showed significant negative change (b = -0.073, p=0.00). In the qualitative part of the study, the prompts with the lowest and highest cognitive complexity mean ratings were presented to the raters and inquired what made those prompts easy or difficult for test takers.

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“…By virtue of complexity metrics, researchers have investigated the relationship between linguistic complexity and various task, context, or learner‐related factors (e.g., Seyyedi et al., 2013;Tabari & Wang, 2022; Yoon, 2021). One specific learner‐related factor that has received increasing attention is learners’ L1 backgrounds.…”

Section: Literature Reviewmentioning

confidence: 99%

Effects of speaker types and L1 backgrounds on the linguistic complexity of learners’ writing

Wang,

Wang

et al. 2023

Int J App Linguistics

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This study investigated the differences in linguistic complexity between different types of English users, including native speakers (NS), English as a foreign language (EFL) learners, and English as a second language (ESL) learners in terms of Kolmogorov complexity. Furthermore, we explored how first language backgrounds affect linguistic complexity. Our dataset contains 2272 argumentative essays produced by English NSs and upper‐intermediate learners from four ESL and six EFL countries/regions. Results showed that significant differences existed between the writings of NS, EFL, and ESL regarding overall and syntactic complexity. Specifically, the rank of overall complexity (NS > ESL > EFL) indicates that learners from countries/regions with higher exposure to English tend to produce overall more complex writings. Concerning syntactic complexity, EFL learners produce the most complex writings, while NS produces the least complex, indicating that essays written by EFL learners contain the most fixed word order patterns. In contrast, no significant difference was detected in morphological complexity among the NS, ESL, and EFL groups, suggesting that native and upper‐intermediate non‐NSs exhibit a similar range of morphological forms in their writings. Additionally, our results showed a larger effect of first language backgrounds over English speaker types on linguistic complexity, thus informing teachers to implement targeted writing instructions for learners from different countries.

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Assessing linguistic complexity features in L2 writing: Understanding effects of topic familiarity and strategic planning within the realm of task readiness

Cited by 21 publications

References 46 publications

Withdrawn: Exploring the associations among task complexity, task motivation, task engagement, and linguistic complexity in L2 writing

Withdrawn: Exploring the associations among task complexity, task motivation, task engagement, and linguistic complexity in L2 writing

A Longitudinal Analysis of the Variability of Cognitive Complexity in IELTS Academic Writing Prompts: a mixed-method study

Effects of speaker types and L1 backgrounds on the linguistic complexity of learners’ writing

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