Technology and L2 Writing

Li, Zhi; Dursun, Ahmet; Hegelheimer, Volker

doi:10.1002/9781118914069.ch6

Cited by 25 publications

(14 citation statements)

References 37 publications

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“…On the other hand, [6] and [7] mentioned a few drawbacks with these tools, most specifically the automated writing evaluation (AWE) programs. AWE's impact on writing instruction and performance is inconclusive.…”

Section: Technology and Esl Writingmentioning

confidence: 99%

An Evaluation of Online and Automated English Writing Assistants: Collocations and Idioms Checkers

Grami

2020

Int. J. Emerg. Technol. Learn.

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In this paper, I attempt to investigate whether online writing checkers, including tools looking at grammar, punctuation, spelling and composition, do in fact help potential ESL writers, and if so, to which extent, in what areas, to what effect and at what cost. The small-scale study involves 23 university level ESL students who compose various texts as part of their training. Data was collected using pre and post writing samples, questionnaires and semi-structured interviews. The analysis used a descriptive statistical method, Likert-scale and correlations and qualitative analysis for the three methods respectively. The results are inconclusive as students reported different opinions. It was found however that students who are frequent users of features such as MS Word Thesaurus and Online Corpora are more likely to incorporate online writing checkers and therefore found them more helpful. It was also found that regardless of their effect, students always welcomed tools available that can provide feedback to their compositions. The writing software used, AccurIT, also showed improvements in students’ ability to write correct collocations.

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Section: Technology and Esl Writingmentioning

confidence: 99%

An Evaluation of Online and Automated English Writing Assistants: Collocations and Idioms Checkers

Grami

2020

Int. J. Emerg. Technol. Learn.

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“…First, examining L2 writing through digitally-mediated environments such as chats and wikis has become pivotal given the rise of learners’ engagement with digital tools to construct meaning in a number of settings (e.g. Elola & Oskoz, 2017; Li, Dursun & Hegelheimer, 2017; Li & Storch, 2017; Zheng, Yim & Warschauer, 2018). Along the lines of understanding digital tools, research has sparked in investigating the effects of interaction in face-to-face (FTF) and text-chat synchronous computer-mediated communication (SCMC) on L2 learning outcomes, with findings indicating that L2 development is also possible in SCMC mode (Ziegler, 2015; Kang, Sok & Han, 2019).…”

Section: Introductionmentioning

confidence: 99%

Heritage language learners’ written texts across pair types and interaction mode

Torres

2020

Language Teaching Research

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Task-based research has investigated the learning opportunities (e.g. language related episodes) that emerge during heritage and second language learner interactions during writing tasks. However, to date, it is unknown how these peer interactions involving heritage language learners contribute to written texts. Further, given the rise of social technologies in educational settings, a need exists to examine how interactions in digital platforms affect the production of written texts. To address these issues, 13 heritage-second language learner and 16 heritage–heritage learner pairs enrolled in advanced Spanish content courses completed two distinct versions of writing tasks. Participants were instructed that they were hired as business consultants for clothing and cellphone companies in Spain. While each participant wrote her or his own version, the pairs had to interact to compose formal business letters in Spanish to the CEO of each company justifying the hiring (Task A) or laying off (Task B) of employees. The main results first revealed that heritage–heritage pairs produced more syntactically complex business letters, as evidenced by a greater ratio of syntactic subordination along with a minor trend of greater morphosyntactic accuracy. Second, synchronous computer-mediated communication interactions led to a higher production of syntactic coordination, especially for the heritage-second language pairs. Findings are discussed in light of the interplay between learner factors and task environment.

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“…Nowadays, we are witnessing a wide variety of technologies that have a massive impact on second language writing (Hyland, 2003). According to Li et al (2017), they can be divided into three main categories: web 2.0, automated writing evaluation, and corpus-based tools. Unlike web 2.0 and corpus-based tools, there are limited studies regarding automated writing feedback, particularly in Saudi Arabia.…”

Section: The Significance Of the Studymentioning

confidence: 99%

Saudi Graduate Students’ Perceptions Toward Automated Writing Feedback for Improving Academic Writing

Alsaweed¹

2022

IJEL

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Over the last few years, we have witnessed a growth in the studies that focus on the feedback on writing in a second language, including computer-based feedback (Zhang & Hyland, 2018). Automated writing feedback refers to the immediate feedback generated by computers to correct or improve the text. The current study discusses the perceptions of Saudi graduate students toward using automated writing feedback to improve their academic writing. The design of the research is a quantitative survey study. A questionnaire consisting of 13 items is the instrument for data collection. The sample size is 46 (male and female) Saudi graduate students. By using descriptive statistics, the findings revealed positive perceptions of the use of automated writing feedback tools. The findings of this study could shed light on the importance of conducting more research on the impact of automated writing feedback in one particular writing aspect, such as organization, content, coherence, unity, or style.

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Technology and L2 Writing

Cited by 25 publications

References 37 publications

An Evaluation of Online and Automated English Writing Assistants: Collocations and Idioms Checkers

An Evaluation of Online and Automated English Writing Assistants: Collocations and Idioms Checkers

Heritage language learners’ written texts across pair types and interaction mode

Saudi Graduate Students’ Perceptions Toward Automated Writing Feedback for Improving Academic Writing

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